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MPO4 Lines – Modal Engine █ OVERVIEW MPO4 Lines – Modal Engine is an advanced multi-line modal oscillator for TradingView, designed to detect momentum shifts, trend strength, and reversal points through candle-based pressure analysis with multiple fast lines and a reference slow line. It features divergence detection on Fast Line A, overbought/oversold return signals, dynamic coloring modes, and layered gradient visualizations for enhanced clarity and decision-making. █ CONCEPT The indicator is built upon the Market Pressure Oscillator (MPO) and serves as its expanded evolution, aimed at enabling broader market analysis through multiple lines with varying parameters. It calculates modal pressure using candle body size and direction, weighted against average body size over a lookback period, then normalized and smoothed via EMA. It generates four distinct oscillator lines: a heavily smoothed Slow Line (trend reference), two Fast Lines (A & B) for momentum and support/resistance, and an optional Line 4 for additional confirmation. Divergence is calculated solely on Fast Line A, with visual gradients between lines and bands for intuitive interpretation. █ WHY USE IT? - Multi-Layer Momentum: Combines slow trend reference with dual fast lines for precise entry/exit timing. - Divergence Precision: Bullish/bearish divergences on Fast Line A with labeled confirmation. - OB/OS Return Signals: Clear buy/sell markers when Fast Line A exits oversold/overbought zones. - Dynamic Visuals: Gradient fills, line-to-line shading, and band gradients for instant market state recognition. - Flexible Coloring: Slow Line color by direction or zero-position; fast lines by sign. - Full Customization: Independent lengths, smoothing, visibility, and transparency — by adjusting the lengths of different lines, you can tailor results for various strategies; for example, enabling Line 4 and tuning its length allows trading based on crossovers between different lines. █ HOW IT WORKS? - Candle Pressure Calculation: Body = math.abs(close - open); avgBody = ta.sma(body, len). Direction = +1 (bull), –1 (bear), 0 (neutral). Weight = body / avgBody. Contribution = direction × weight. - Rolling Sum & Normalization: Sums contributions over lookback, normalizes to ±100 scale (÷ (len × 2) × 100). Smoothing: Applies primary EMA (smoothLen), with extra EMA on Slow Line for stability. Line Structure: - Slow Line = calcCPO(len1=20, smoothLen1=5) → extra EMA (5) - Fast Line A = calcCPO(len2=6, smoothLen2=7) - Fast Line B = calcCPO(len3=6, smoothLen3=10) - Line 4 = calcCPO(len4=14, smoothLen4=1) Divergence Detection: Uses ta.pivothigh/low on price and Fast Line A (pivotLength left/right). Bullish: lower price low + higher osc low. Bearish: higher price high + lower osc high. Valid within 5–60 bar window. Signals: - Buy: Fast Line A crosses above oversold (–30) - Sell: Fast Line A crosses below overbought (+30) - Slow Line color flip (direction or zero-cross) - Divergence labels ("Bull" / "Bear") - Band Coloring as Momentum Signal: When Fast Line A ≤ Fast Line B → Overbought band turns red (bearish pressure building) When Fast Line A > Fast Line B → Oversold band turns green (bullish pressure building) This dynamic coloring serves as visual confirmation of momentum shift following fast line crossovers Visualization: - Gradients: Fast B → Zero (multi-layer fade), Fast A ↔ B fill, OB/OS bands - Dynamic colors: Green/red based on sign or trend - Zero line + dashed OB/OS thresholds Alerts: Trigger on OB/OS returns, Slow Line changes, and divergences. █ SETTINGS AND CUSTOMIZATION - Line Visibility: Toggle Slow, Fast A, Fast B, Line 4 independently. Line Lengths: - Slow Line: Base (20), Primary EMA (5), Extra EMA (5) - Fast A: Lookback (6), EMA (7) - Fast B: Lookback (6), EMA (10) - Line 4: Lookback (14), EMA (1) - Slow Line Coloring Mode: “Direction” (trend-based) or “Position vs Zero”. - Bands & Thresholds: Overbought (+30), Oversold (–30), step 0.1. - Signals: Enable Fast A OB/OS return markers (default: on). - Divergence: Enable/disable, Pivot Length (default: 2, min 1). - Colors & Appearance: Full control over bullish/bearish hues for all lines, zero, bands, divergence, and text. Gradients & Transparency: - Fast B → Zero: 75 (default) - Fast A ↔ B fill: 50 - Band gradients: 40 - Toggle each gradient independently █ USAGE EXAMPLES The indicator allows users to configure various strategies manually, though no built-in alerts exist for them. Entry signals can include color of fast lines, crossovers between different lines, alignment of colors across lines, or consistency in direction. - Trend Confirmation: Slow Line above zero + green = bullish bias; below + red = bearish. - Entry Timing: Buy on Fast A crossing above –30 (circle marker), especially if Slow Line is rising or near zero. - Reversal Setup: Bullish divergence (“Bull” label) + Fast A in oversold + green gradient band = high-probability long. - Scalping: Fast A vs Fast B crossover in direction of Slow Line trend. - Noise Reduction: Increase extraSmoothLen on Slow Line █ USER NOTES - Best combined with volume, support/resistance, or trend channels. - Adjust lookback and smoothing to asset volatility. - Divergence delay = pivotLength; plan entries accordingly.

Indicateur Pine Script®

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COT Index THE HIDDEN INTELLIGENCE IN FUTURES MARKETS What if you could see what the smartest players in the futures markets are doing before the crowd catches on? While retail traders chase momentum indicators and moving averages, obsess over Japanese candlestick patterns, and debate whether the RSI should be set to fourteen or twenty-one periods, institutional players leave footprints in the sand through their mandatory reporting to the Commodity Futures Trading Commission. These footprints, published weekly in the Commitment of Traders reports, have been hiding in plain sight for decades, available to anyone with an internet connection, yet remarkably few traders understand how to interpret them correctly. The COT Index indicator transforms this raw institutional positioning data into actionable trading signals, bringing Wall Street intelligence to your trading screen without requiring expensive Bloomberg terminals or insider connections. The uncomfortable truth is this: Most retail traders operate in a binary world. Long or short. Buy or sell. They apply technical analysis to individual positions, constrained by limited capital that forces them to concentrate risk in single directional bets. Meanwhile, institutional traders operate in an entirely different dimension. They manage portfolios dynamically weighted across multiple markets, adjusting exposure based on evolving market conditions, correlation shifts, and risk assessments that retail traders never see. A hedge fund might be simultaneously long gold, short oil, neutral on copper, and overweight agricultural commodities, with position sizes calibrated to volatility and portfolio Greeks. When they increase gold exposure from five percent to eight percent of portfolio allocation, this rebalancing decision reflects sophisticated analysis of opportunity cost, risk parity, and cross-market dynamics that no individual chart pattern can capture. This portfolio reweighting activity, multiplied across hundreds of institutional participants, manifests in the aggregate positioning data published weekly by the CFTC. The Commitment of Traders report does not show individual trades or strategies. It shows the collective footprint of how actual commercial hedgers and large speculators have allocated their capital across different markets. When mining companies collectively increase forward gold sales to hedge thirty percent more production than last quarter, they are not reacting to a moving average crossover. They are making strategic allocation decisions based on production forecasts, cost structures, and price expectations derived from operational realities invisible to outside observers. This is portfolio management in action, revealed through positioning data rather than price charts. If you want to understand how institutional capital actually flows, how sophisticated traders genuinely position themselves across market cycles, the COT report provides a rare window into that hidden world. But understand what you are getting into. This is not a tool for scalpers seeking confirmation of the next five-minute move. This is not an oscillator that flashes oversold at market bottoms with convenient precision. COT analysis operates on a timescale measured in weeks and months, revealing positioning shifts that precede major market turns but offer no precision timing. The data arrives three days stale, published only once per week, capturing strategic positioning rather than tactical entries. If you need instant gratification, if you trade intraday moves, if you demand mechanical signals with ninety percent accuracy, close this document now. COT analysis rewards patience, position sizing discipline, and tolerance for being early. It punishes impatience, overleveraging, and the expectation that any single indicator can substitute for market understanding. The premise is deceptively simple. Every Tuesday, large traders in futures markets must report their positions to the CFTC. By Friday afternoon, this data becomes public. Academic research spanning three decades has consistently shown that not all market participants are created equal. Some traders consistently profit while others consistently lose. Some anticipate major turning points while others chase trends into exhaustion. Bessembinder and Chan (1992) demonstrated in their seminal study that commercial hedgers, those with actual exposure to the underlying commodity or financial instrument, possess superior forecasting ability compared to speculators. Their research, published in the Journal of Finance, found statistically significant predictive power in commercial positioning, particularly at extreme levels. This finding challenged the efficient market hypothesis and opened the door to a new approach to market analysis based on positioning rather than price alone. Think about what this means. Every week, the government publishes a report showing you exactly how the most informed market participants are positioned. Not their opinions. Not their predictions. Their actual money at risk. When agricultural producers collectively hold their largest short hedge in five years, they are not making idle speculation. They are locking in prices for crops they will harvest, informed by private knowledge of weather conditions, soil quality, inventory levels, and demand expectations invisible to outside observers. When energy companies aggressively hedge forward production at current prices, they reveal information about expected supply that no analyst report can capture. This is not technical analysis based on past prices. This is not fundamental analysis based on publicly available data. This is behavioral analysis based on how the smartest money is actually positioned, how institutions allocate capital across portfolios, and how those allocation decisions shift as market conditions evolve. WHY SOME TRADERS KNOW MORE THAN OTHERS Building on this foundation, Sanders, Boris and Manfredo (2004) conducted extensive research examining the behaviour patterns of different trader categories. Their work, which analyzed over a decade of COT data across multiple commodity markets, revealed a fascinating dynamic that challenges much of what retail traders are taught. Commercial hedgers consistently positioned themselves against market extremes, buying when speculators were most bearish and selling when speculators reached peak bullishness. The contrarian positioning of commercials was not random noise but rather reflected their superior information about supply and demand fundamentals. Meanwhile, large speculators, primarily hedge funds and commodity trading advisors, exhibited strong trend-following behaviour that often amplified market moves beyond fundamental values. Small traders, the retail participants, consistently entered positions late in trends, frequently near turning points, making them reliable contrary indicators. Wang (2003) extended this research by demonstrating that the predictive power of commercial positioning varies significantly across different commodity sectors. His analysis of agricultural commodities showed particularly strong forecasting ability, with commercial net positions explaining up to fifteen percent of return variance in subsequent weeks. This finding suggests that the informational advantages of hedgers are most pronounced in markets where physical supply and demand fundamentals dominate, as opposed to purely financial markets where information asymmetries are smaller. When a corn farmer hedges six months of expected harvest, that decision incorporates private observations about rainfall patterns, crop health, pest pressure, and local storage capacity that no distant analyst can match. When an oil refinery hedges crude oil purchases and gasoline sales simultaneously, the spread relationships reveal expectations about refining margins that reflect operational realities invisible in public data. The theoretical mechanism underlying these empirical patterns relates to information asymmetry and different participant motivations. Commercial hedgers engage in futures markets not for speculative profit but to manage business risks. An agricultural producer selling forward six months of expected harvest is not making a bet on price direction but rather locking in revenue to facilitate financial planning and ensure business viability. However, this hedging activity necessarily incorporates private information about expected supply, inventory levels, weather conditions, and demand trends that the hedger observes through their commercial operations (Irwin and Sanders, 2012). When aggregated across many participants, this private information manifests in collective positioning. Consider a gold mining company deciding how much forward production to hedge. Management must estimate ore grades, recovery rates, production costs, equipment reliability, labor availability, and dozens of other operational variables that determine whether locking in prices at current levels makes business sense. If the industry collectively hedges more aggressively than usual, it suggests either exceptional production expectations or concern about sustaining current price levels or combination of both. Either way, this positioning reveals information unavailable to speculators analyzing price charts and economic data. The hedger sees the physical reality behind the financial abstraction. Large speculators operate under entirely different incentives and constraints. Commodity Trading Advisors managing billions in assets typically employ systematic, trend-following strategies that respond to price momentum rather than fundamental supply and demand. When crude oil rallies from sixty dollars to seventy dollars per barrel, these systems generate buy signals. As the rally continues to eighty dollars, position sizes increase. The strategy works brilliantly during sustained trends but becomes a liability at reversals. By the time oil reaches ninety dollars, trend-following funds are maximally long, having accumulated positions progressively throughout the rally. At this point, they represent not smart money anticipating further gains but rather crowded money vulnerable to reversal. Sanders, Boris and Manfredo (2004) documented this pattern across multiple energy markets, showing that extreme speculator positioning typically marked late-stage trend exhaustion rather than early-stage trend development. Small traders, the retail participants who fall below reporting thresholds, display the weakest forecasting ability. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns, meaning their aggregate positioning served as a reliable contrary indicator. The explanation combines several factors. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, entering trends after mainstream media coverage when institutional participants are preparing to exit. Perhaps most importantly, they trade with emotion, buying into euphoria and selling into panic at precisely the wrong times. At major turning points, the three groups often position opposite each other with commercials extremely bearish, large speculators extremely bullish, and small traders piling into longs at the last moment. These high-divergence environments frequently precede increased volatility and trend reversals. The insiders with business exposure quietly exit as the momentum traders hit maximum capacity and retail enthusiasm peaks. Within weeks, the reversal begins, and positions unwind in the opposite sequence. FROM RAW DATA TO ACTIONABLE SIGNALS The COT Index indicator operationalizes these academic findings into a practical trading tool accessible through TradingView. At its core, the indicator normalizes net positioning data onto a zero to one hundred scale, creating what we call the COT Index. This normalization is critical because absolute position sizes vary dramatically across different futures contracts and over time. A commercial trader holding fifty thousand contracts net long in crude oil might be extremely bullish by historical standards, or it might be quite neutral depending on the context of total market size and historical ranges. Raw position numbers mean nothing without context. The COT Index solves this problem by calculating where current positioning stands relative to its range over a specified lookback period, typically two hundred fifty-two weeks or approximately five years of weekly data. The mathematical transformation follows the methodology originally popularized by legendary trader Larry Williams, though the underlying concept appears in statistical normalization techniques across many fields. For any given trader category, we calculate the highest and lowest net position values over the lookback period, establishing the historical range for that specific market and trader group. Current positioning is then expressed as a percentage of this range, where zero represents the most bearish positioning ever seen in the lookback window and one hundred represents the most bullish extreme. A reading of fifty indicates positioning exactly in the middle of the historical range, suggesting neither extreme optimism nor pessimism relative to recent history (Williams and Noseworthy, 2009). This index-based approach allows for meaningful comparison across different markets and time periods, overcoming the scaling problems inherent in analyzing raw position data. A commercial index reading of eighty-five in gold carries the same interpretive meaning as an eighty-five reading in wheat or crude oil, even though the absolute position sizes differ by orders of magnitude. This standardization enables systematic analysis across entire futures portfolios rather than requiring market-specific expertise for each contract. The lookback period selection involves a fundamental tradeoff between responsiveness and stability. Shorter lookback periods, perhaps one hundred twenty-six weeks or approximately two and a half years, make the index more sensitive to recent positioning changes. However, it also increases noise and produces more false signals. Longer lookback periods, perhaps five hundred weeks or approximately ten years, create smoother readings that filter short-term noise but become slower to recognize regime changes. The indicator settings allow users to adjust this parameter based on their trading timeframe, risk tolerance, and market characteristics. UNDERSTANDING CFTC DATA STRUCTURES The indicator supports both Legacy and Disaggregated COT report formats, reflecting the evolution of CFTC reporting standards over decades of market development. Legacy reports categorize market participants into three broad groups: commercial traders (hedgers with underlying business exposure), non-commercial traders (large speculators seeking profit without commercial interest), and non-reportable traders (small speculators below reporting thresholds). Each category brings distinct motivations and information advantages to the market (CFTC, 2020). The Disaggregated reports, introduced in September 2009 for physical commodity markets, provide finer granularity by splitting participants into five categories (CFTC, 2009). Producer and merchant positions capture those actually producing, processing, or merchandising the physical commodity. Swap dealers represent financial intermediaries facilitating derivative transactions for clients. Managed money includes commodity trading advisors and hedge funds executing systematic or discretionary strategies. Other reportables encompasses diverse participants not fitting the main categories. Small traders remain as the fifth group, representing retail participation. This enhanced categorization reveals nuances invisible in Legacy reports, particularly distinguishing between different types of institutional capital and their distinct behavioural patterns. The indicator automatically detects which report type is appropriate for each futures contract and adjusts the display accordingly. Importantly, Disaggregated reports exist only for physical commodity futures. Agricultural commodities like corn, wheat, and soybeans have Disaggregated reports because clear producer, merchant, and swap dealer categories exist. Energy commodities like crude oil and natural gas similarly have well-defined commercial hedger categories. Metals including gold, silver, and copper also receive Disaggregated treatment (CFTC, 2009). However, financial futures such as equity index futures, Treasury bond futures, and currency futures remain available only in Legacy format. The CFTC has indicated no plans to extend Disaggregated reporting to financial futures due to different market structures and participant categories in these instruments (CFTC, 2020). THE BEHAVIORAL FOUNDATION Understanding which trader perspective to follow requires appreciation of their distinct trading styles, success rates, and psychological profiles. Commercial hedgers exhibit anticyclical behaviour rooted in their fundamental knowledge and business imperatives. When agricultural producers hedge forward sales during harvest season, they are not speculating on price direction but rather locking in revenue for crops they will harvest. Their business requires converting volatile commodity exposure into predictable cash flows to facilitate planning and ensure survival through difficult periods. Yet their aggregate positioning reveals valuable information because these hedging decisions incorporate private information about supply conditions, inventory levels, weather observations, and demand expectations that hedgers observe through their commercial operations (Bessembinder and Chan, 1992). Consider a practical example from energy markets. Major oil companies continuously hedge portions of forward production based on price levels, operational costs, and financial planning needs. When crude oil trades at ninety dollars per barrel, they might aggressively hedge the next twelve months of production, locking in prices that provide comfortable profit margins above their extraction costs. This hedging appears as short positioning in COT reports. If oil rallies further to one hundred dollars, they hedge even more aggressively, viewing these prices as exceptional opportunities to secure revenue. Their short positioning grows increasingly extreme. To an outside observer watching only price charts, the rally suggests bullishness. But the commercial positioning reveals that the actual producers of oil find these prices attractive enough to lock in years of sales, suggesting skepticism about sustaining even higher levels. When the eventual reversal occurs and oil declines back to eighty dollars, the commercials who hedged at ninety and one hundred dollars profit while speculators who chased the rally suffer losses. Large speculators or managed money traders operate under entirely different incentives and constraints. Their systematic, momentum-driven strategies mean they amplify existing trends rather than anticipate reversals. Trend-following systems, the most common approach among large speculators, by definition require confirmation of trend through price momentum before entering positions (Sanders, Boris and Manfredo, 2004). When crude oil rallies from sixty dollars to eighty dollars per barrel over several months, trend-following algorithms generate buy signals based on moving average crossovers, breakouts, and other momentum indicators. As the rally continues, position sizes increase according to the systematic rules. However, this approach becomes a liability at turning points. By the time oil reaches ninety dollars after a sustained rally, trend-following funds are maximally long, having accumulated positions progressively throughout the move. At this point, their positioning does not predict continued strength. Rather, it often marks late-stage trend exhaustion. The psychological and mechanical explanation is straightforward. Trend followers by definition chase price momentum, entering positions after trends establish rather than anticipating them. Eventually, they become fully invested just as the trend nears completion, leaving no incremental buying power to sustain the rally. When the first signs of reversal appear, systematic stops trigger, creating a cascade of selling that accelerates the downturn. Small traders consistently display the weakest track record across academic studies. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns in his analysis across multiple commodity markets. This result means that whatever small traders collectively do, the opposite typically proves profitable. The explanation for small trader underperformance combines several factors documented in behavioral finance literature. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, learning about commodity trends through mainstream media coverage that arrives after institutional participants have already positioned. Perhaps most importantly, retail traders are more susceptible to emotional decision-making, buying into euphoria and selling into panic at precisely the wrong times (Tharp, 2008). SETTINGS, THRESHOLDS, AND SIGNAL GENERATION The practical implementation of the COT Index requires understanding several key features and settings that users can adjust to match their trading style, timeframe, and risk tolerance. The lookback period determines the time window for calculating historical ranges. The default setting of two hundred fifty-two bars represents approximately one year on daily charts or five years on weekly charts, balancing responsiveness with stability. Conservative traders seeking only the most extreme, highest-probability signals might extend the lookback to five hundred bars or more. Aggressive traders seeking earlier entry and willing to accept more false positives might reduce it to one hundred twenty-six bars or even less for shorter-term applications. The bullish and bearish thresholds define signal generation levels. Default settings of eighty and twenty respectively reflect academic research suggesting meaningful information content at these extremes. Readings above eighty indicate positioning in the top quintile of the historical range, representing genuine extremes rather than temporary fluctuations. Conversely, readings below twenty occupy the bottom quintile, indicating unusually bearish positioning (Briese, 2008). However, traders must recognize that appropriate thresholds vary by market, trader category, and personal risk tolerance. Some futures markets exhibit wider positioning swings than others due to seasonal patterns, volatility characteristics, or participant behavior. Conservative traders seeking high-probability setups with fewer signals might raise thresholds to eighty-five and fifteen. Aggressive traders willing to accept more false positives for earlier entry could lower them to seventy-five and twenty-five. The key is maintaining meaningful differentiation between bullish, neutral, and bearish zones. The default settings of eighty and twenty create a clear three-zone structure. Readings from zero to twenty represent bearish territory where the selected trader group holds unusually bearish positions. Readings from twenty to eighty represent neutral territory where positioning falls within normal historical ranges. Readings from eighty to one hundred represent bullish territory where the selected trader group holds unusually bullish positions. The trading perspective selection determines which participant group the indicator follows, fundamentally shaping interpretation and signal meaning. For counter-trend traders seeking reversal opportunities, monitoring commercial positioning makes intuitive sense based on the academic research discussed earlier. When commercials reach extreme bearish readings below twenty, indicating unprecedented short positioning relative to recent history, they are effectively betting against the crowd. Given their informational advantages demonstrated by Bessembinder and Chan (1992), this contrarian stance often precedes major bottoms. Trend followers might instead monitor large speculator positioning, but with inverted logic compared to commercials. When managed money reaches extreme bullish readings above eighty, the trend may be exhausting rather than accelerating. This seeming paradox reflects their late-cycle participation documented by Sanders, Boris and Manfredo (2004). Sophisticated traders thus use speculator extremes as fade signals, entering positions opposite to speculator consensus. Small trader monitoring serves primarily as a contrary indicator for all trading styles. Extreme small trader bullishness above seventy-five or eighty typically warns of retail FOMO at market tops. Extreme small trader bearishness below twenty or twenty-five often marks capitulation bottoms where the last weak hands have sold. VISUALIZATION AND USER INTERFACE The visual design incorporates multiple elements working together to facilitate decision-making and maintain situational awareness during active trading. The primary COT Index line plots in bold with adjustable line width, defaulting to two pixels for clear visibility against busy price charts. An optional glow effect, controlled by a simple toggle, adds additional visual prominence through multiple plot layers with progressively increasing transparency and width. A twenty-one period exponential moving average overlays the index line, providing trend context for positioning changes. When the index crosses above its moving average, it signals accelerating bullish sentiment among the selected trader group regardless of whether absolute positioning is extreme. Conversely, when the index crosses below its moving average, it signals deteriorating sentiment and potentially the beginning of a reversal in positioning trends. The EMA provides a dynamic reference line for assessing positioning momentum. When the index trades far above its EMA, positioning is not only extreme in absolute terms but also building with momentum. When the index trades far below its EMA, positioning is contracting or reversing, which may indicate weakening conviction even if absolute levels remain elevated. The data table positioned at the top right of the chart displays eleven metrics for each trader category, transforming the indicator from a simple index calculation into an analytical dashboard providing multidimensional market intelligence. Beyond the COT Index itself, users can monitor positioning extremity, which measures how unusual current levels are compared to historical norms using statistical techniques. The extremity metric clarifies whether a reading represents the ninety-fifth or ninety-ninth percentile, with values above two standard deviations indicating genuinely exceptional positioning. Market power quantifies each group's influence on total open interest. This metric expresses each trader category's net position as a percentage of total market open interest. A commercial entity holding forty percent of total open interest commands significantly more influence than one holding five percent, making their positioning signals more meaningful. Momentum and rate of change metrics reveal whether positions are building or contracting, providing early warning of potential regime shifts. Position velocity measures the rate of change in positioning changes, effectively a second derivative providing even earlier insight into inflection points. Sentiment divergence highlights disagreements between commercial and speculative positioning. This metric calculates the absolute difference between normalized commercial and large speculator index values. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals. The table also displays concentration metrics when available, showing how positioning is distributed among the largest handful of traders in each category. High concentration indicates a few dominant players controlling most of the positioning, while low concentration suggests broad-based participation across many traders. THE ALERT SYSTEM AND MONITORING The alert system, comprising five distinct alert conditions, enables systematic monitoring of dozens of futures markets without constant screen watching. The bullish and bearish COT signal alerts trigger when the index crosses user-defined thresholds, indicating the selected trader group has reached extreme positioning worthy of attention. These alerts fire in real-time as new weekly COT data publishes, typically Friday afternoon following the Tuesday measurement date. Extreme positioning alerts fire at ninety and ten index levels, representing the top and bottom ten percent of the historical range, warning of particularly stretched readings that historically precede reversals with high probability. When commercials reach a COT Index reading below ten, they are expressing their most bearish stance in the entire lookback period. The data staleness alert notifies users when COT reports have not updated for more than ten days, preventing reliance on outdated information for trading decisions. Government shutdowns or federal holidays can interrupt the normal Friday publication schedule. Using stale signals while believing them current creates dangerous false confidence. The indicator's watermark information display positioned in the bottom right corner provides essential context at a glance. This persistent display shows the symbol and timeframe, the COT report date timestamp, days since last update, and the current signal state. A trader analyzing a potential short entry in crude oil can glance at the watermark to instantly confirm positioning context without interrupting analysis flow. LIMITATIONS AND REALISTIC EXPECTATIONS Practical application requires understanding both the indicator's considerable strengths and inherent limitations. COT data inherently lags price action by three days, as Tuesday positions are not published until Friday afternoon. This delay means the indicator cannot catch rapid intraday reversals or respond to surprise news events. Traders using the COT Index for timing entries must accept this latency and focus on swing trading and position trading timeframes where three-day lags matter less than in day trading or scalping. The weekly publication schedule similarly makes the indicator unsuitable for short-term trading strategies requiring immediate feedback. The COT Index works best for traders operating on weekly or longer timeframes, where positioning shifts measured in weeks and months align with trading horizon. Extreme COT readings can persist far longer than typical technical indicators suggest, testing the patience and capital reserves of traders attempting to fade them. When crude oil enters a sustained bull market driven by genuine supply disruptions, commercial hedgers may maintain bearish positioning for many months as prices grind higher. A commercial COT Index reading of fifteen indicating extreme bearishness might persist for three months while prices continue rallying before finally reversing. Traders without sufficient capital and risk tolerance to weather such drawdowns will exit prematurely, precisely when the signal is about to work (Irwin and Sanders, 2012). Position sizing discipline becomes paramount when implementing COT-based strategies. Rather than risking large percentages of capital on individual signals, successful COT traders typically allocate modest position sizes across multiple signals, allowing some to take time to mature while others work more quickly. The indicator also cannot overcome fundamental regime changes that alter the structural drivers of markets. If gold enters a true secular bull market driven by monetary debasement, commercial hedgers may remain persistently bearish as mining companies sell forward years of production at what they perceive as favorable prices. Their positioning indicates valuation concerns from a production cost perspective, but cannot stop prices from rising if investment demand overwhelms physical supply-demand balance. Similarly, structural changes in market participation can alter the meaning of positioning extremes. The growth of commodity index investing in the two thousands brought massive passive long-only capital into futures markets, fundamentally changing typical positioning ranges. Traders relying on COT signals without recognizing this regime change would have generated numerous false bearish signals during the commodity supercycle from 2003 to 2008. The research foundation supporting COT analysis derives primarily from commodity markets where the commercial hedger information advantage is most pronounced. Studies specifically examining financial futures like equity indices and bonds show weaker but still present effects. Traders should calibrate expectations accordingly, recognizing that COT analysis likely works better for crude oil, natural gas, corn, and wheat than for the S&P 500, Treasury bonds, or currency futures. Another important limitation involves the reporting threshold structure. Not all market participants appear in COT data, only those holding positions above specified minimums. In markets dominated by a few large players, concentration metrics become critical for proper interpretation. A single large trader accounting for thirty percent of commercial positioning might skew the entire category if their individual circumstances are idiosyncratic rather than representative. GOLD FUTURES DURING A HYPOTHETICAL MARKET CYCLE Consider a practical example using gold futures during a hypothetical but realistic market scenario that illustrates how the COT Index indicator guides trading decisions through a complete market cycle. Suppose gold has rallied from fifteen hundred to nineteen hundred dollars per ounce over six months, driven by inflation concerns following aggressive monetary expansion, geopolitical uncertainty, and sustained buying by Asian central banks for reserve diversification. Large speculators, operating primarily trend-following strategies, have accumulated increasingly bullish positions throughout this rally. Their COT Index has climbed progressively from forty-five to eighty-five. The table display shows that large speculators now hold net long positions representing thirty-two percent of total open interest, their highest in four years. Momentum indicators show positive readings, indicating positions are still building though at a decelerating rate. Position velocity has turned negative, suggesting the pace of position building is slowing. Meanwhile, commercial hedgers have responded to the rally by aggressively selling forward production and inventory. Their COT Index has moved inversely to price, declining from fifty-five to twenty. This bearish commercial positioning represents mining companies locking in forward sales at prices they view as attractive relative to production costs. The table shows commercials now hold net short positions representing twenty-nine percent of total open interest, their most bearish stance in five years. Concentration metrics indicate this positioning is broadly distributed across many commercial entities, suggesting the bearish stance reflects collective industry view rather than idiosyncratic positioning by a single firm. Small traders, attracted by mainstream financial media coverage of gold's impressive rally, have recently piled into long positions. Their COT Index has jumped from forty-five to seventy-eight as retail investors chase the trend. Television financial networks feature frequent segments on gold with bullish guests. Internet forums and social media show surging retail interest. This retail enthusiasm historically marks late-stage trend development rather than early opportunity. The COT Index indicator, configured to monitor commercial positioning from a contrarian perspective, displays a clear bearish signal given the extreme commercial short positioning. The table displays multiple confirming metrics: positioning extremity shows commercials at the ninety-sixth percentile of bearishness, market power indicates they control twenty-nine percent of open interest, and sentiment divergence registers sixty-five, indicating massive disagreement between commercial hedgers and large speculators. This divergence, the highest in three years, places the market in the historically high-risk category for reversals. The interpretation requires nuance and consideration of context beyond just COT data. Commercials are not necessarily predicting an imminent crash. Rather, they are hedging business operations at what they collectively view as favorable price levels. However, the data reveals they have sold unusually large quantities of forward production, suggesting either exceptional production expectations for the year ahead or concern about sustaining current price levels or combination of both. Combined with extreme speculator positioning indicating a crowded long trade, and small trader enthusiasm confirming retail FOMO, the confluence suggests elevated reversal risk even if the precise timing remains uncertain. A prudent trader analyzing this situation might take several actions based on COT Index signals. Existing long positions could be tightened with closer stop losses. Profit-taking on a portion of long exposure could lock in gains while maintaining some participation. Some traders might initiate modest short positions as portfolio hedges, sizing them appropriately for the inherent uncertainty in timing reversals. Others might simply move to the sidelines, avoiding new long entries until positioning normalizes. The key lesson from case study analysis is that COT signals provide probabilistic edges rather than deterministic predictions. They work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five percent win rate with proper risk management produces substantial profits over time, yet still means forty-five percent of signals will be premature or wrong. Traders must embrace this probabilistic reality rather than seeking the impossible goal of perfect accuracy. INTEGRATION WITH TRADING SYSTEMS Integration with existing trading systems represents a natural and powerful use case for COT analysis, adding a positioning dimension to price-based technical approaches or fundamental analytical frameworks. Few traders rely exclusively on a single indicator or methodology. Rather, they build systems that synthesize multiple information sources, with each component addressing different aspects of market behavior. Trend followers might use COT extremes as regime filters, modifying position sizing or avoiding new trend entries when positioning reaches levels historically associated with reversals. Consider a classic trend-following system based on moving average crossovers and momentum breakouts. Integration of COT analysis adds nuance. When large speculator positioning exceeds ninety or commercial positioning falls below ten, the regime filter recognizes elevated reversal risk. The system might reduce position sizing by fifty percent for new signals during these high-risk periods (Kaufman, 2013). Mean reversion traders might require COT signal confluence before fading extended moves. When crude oil becomes technically overbought and large speculators show extreme long positioning above eighty-five, both signals confirm. If only technical indicators show extremes while positioning remains neutral, the potential short signal is rejected, avoiding fades of trends with underlying institutional support (Kaufman, 2013). Discretionary traders can monitor the indicator as a continuous awareness tool, informing bias and position sizing without dictating mechanical entries and exits. A discretionary trader might notice commercial positioning shifting from neutral to progressively more bullish over several months. This trend informs growing positive bias even without triggering mechanical signals. Multi-timeframe analysis represents another powerful integration approach. A trader might use daily charts for trade execution and timing while monitoring weekly COT positioning for strategic context. When both timeframes align, highest-probability opportunities emerge. Portfolio construction for futures traders can incorporate COT signals as an additional selection criterion. Markets showing strong technical setups AND favorable COT positioning receive highest allocations. Markets with strong technicals but neutral or unfavorable positioning receive reduced allocations. ADVANCED METRICS AND INTERPRETATION The metrics table transforms simple positioning data into multidimensional market intelligence. Position extremity, calculated as the absolute deviation from the historical mean normalized by standard deviation, helps identify truly unusual readings versus routine fluctuations. A reading above two standard deviations indicates ninety-fifth percentile or higher extremity. Above three standard deviations indicates ninety-ninth percentile or higher, genuinely rare positioning that historically precedes major events with high probability. Market power, expressed as a percentage of total open interest, reveals whose positioning matters most from a mechanical market impact perspective. Consider two scenarios in gold futures. In scenario one, commercials show a COT Index reading of fifteen while their market power metric shows they hold net shorts representing thirty-five percent of open interest. This is a high-confidence bearish signal. In scenario two, commercials also show a reading of fifteen, but market power shows only eight percent. While positioning is extreme relative to this category's normal range, their limited market share means less mechanical influence on price. The rate of change and momentum metrics highlight whether positions are accelerating or decelerating, often providing earlier warnings than absolute levels alone. A COT Index reading of seventy-five with rapidly building momentum suggests continued movement toward extremes. Conversely, a reading of eighty-five with decelerating or negative momentum indicates the positioning trend is exhausting. Position velocity measures the rate of change in positioning changes, effectively a second derivative. When velocity shifts from positive to negative, it indicates that while positioning may still be growing, the pace of growth is slowing. This deceleration often precedes actual reversal in positioning direction by several weeks. Sentiment divergence calculates the absolute difference between normalized commercial and large speculator index values. When commercials show extreme bearish positioning at twenty while large speculators show extreme bullish positioning at eighty, the divergence reaches sixty, representing near-maximum disagreement. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals. The mechanism is intuitive. Extreme divergence indicates the informed hedgers and momentum-following speculators have positioned opposite each other with conviction. One group will prove correct and profit while the other proves incorrect and suffers losses. The resolution of this disagreement through price movement often involves volatility. The table also displays concentration metrics when available. High concentration indicates a few dominant players controlling most of the positioning within a category, while low concentration suggests broad-based participation. Broad-based positioning more reliably reflects collective market intelligence and industry consensus. If mining companies globally all independently decide to hedge aggressively at similar price levels, it suggests genuine industry-wide view about price valuations rather than circumstances specific to one firm. DATA QUALITY AND RELIABILITY The CFTC has maintained COT reporting in various forms since the nineteen twenties, providing nearly a century of positioning data across multiple market cycles. However, data quality and reporting standards have evolved substantially over this long period. Modern electronic reporting implemented in the late nineteen nineties and early two thousands significantly improved accuracy and timeliness compared to earlier paper-based systems. Traders should understand that COT reports capture positions as of Tuesday's close each week. Markets remain open three additional days before publication on Friday afternoon, meaning the reported data is three days stale when received. During periods of rapid market movement or major news events, this lag can be significant. The indicator addresses this limitation by including timestamp information and staleness warnings. The three-day lag creates particular challenges during extreme volatility episodes. Flash crashes, surprise central bank interventions, geopolitical shocks, and other high-impact events can completely transform market positioning within hours. Traders must exercise judgment about whether reported positioning remains relevant given intervening events. Reporting thresholds also mean that not all market participants appear in disaggregated COT data. Traders holding positions below specified minimums aggregate into the non-reportable or small trader category. This aggregation affects different markets differently. In highly liquid contracts like crude oil with thousands of participants, reportable traders might represent seventy to eighty percent of open interest. In thinly traded contracts with only dozens of active participants, a few large reportable positions might represent ninety-five percent of open interest. Another data quality consideration involves trader classification into categories. The CFTC assigns traders to commercial or non-commercial categories based on reported business purpose and activities. However, this process is not perfect. Some entities engage in both commercial and speculative activities, creating ambiguity about proper classification. The transition to Disaggregated reports attempted to address some of these ambiguities by creating more granular categories. COMPARISON WITH ALTERNATIVE APPROACHES Several alternative approaches to COT analysis exist in the trading community beyond the normalization methodology employed by this indicator. Some analysts focus on absolute position changes week-over-week rather than index-based normalization. This approach calculates the change in net positioning from one week to the next. The emphasis falls on momentum in positioning changes rather than absolute levels relative to history. This method potentially identifies regime shifts earlier but sacrifices cross-market comparability (Briese, 2008). Other practitioners employ more complex statistical transformations including percentile rankings, z-score standardization, and machine learning classification algorithms. Ruan and Zhang (2018) demonstrated that machine learning models applied to COT data could achieve modest improvements in forecasting accuracy compared to simple threshold-based approaches. However, these gains came at the cost of interpretability and implementation complexity. The COT Index indicator intentionally employs a relatively straightforward normalization methodology for several important reasons. First, transparency enhances user understanding and trust. Traders can verify calculations manually and develop intuitive feel for what different readings mean. Second, academic research suggests that most of the predictive power in COT data comes from extreme positioning levels rather than subtle patterns requiring complex statistical methods to detect. Third, robust methods that work consistently across many markets and time periods tend to be simpler rather than more complex, reducing the risk of overfitting to historical data. Fourth, the complexity costs of implementation matter for retail traders without programming teams or computational infrastructure. PSYCHOLOGICAL ASPECTS OF COT TRADING Trading based on COT data requires psychological fortitude that differs from momentum-based approaches. Contrarian positioning signals inherently mean betting against prevailing market sentiment and recent price action. When commercials reach extreme bearish positioning, prices have typically been rising, sometimes for extended periods. The price chart looks bullish, momentum indicators confirm strength, moving averages align positively. The COT signal says bet against all of this. This psychological difficulty explains why COT analysis remains underutilized relative to trend-following methods. Human psychology strongly predisposes us toward extrapolation and recency bias. When prices rally for months, our pattern-matching brains naturally expect continued rally. The recent price action dominates our perception, overwhelming rational analysis about positioning extremes and historical probabilities. The COT signal asking us to sell requires overriding these powerful psychological impulses. The indicator design attempts to support the required psychological discipline through several features. Clear threshold markers and signal states reduce ambiguity about when signals trigger. When the commercial index crosses below twenty, the signal is explicit and unambiguous. The background shifts to red, the signal label displays bearish, and alerts fire. This explicitness helps traders act on signals rather than waiting for additional confirmation that may never arrive. The metrics table provides analytical justification for contrarian positions, helping traders maintain conviction during inevitable periods of adverse price movement. When a trader enters short positions based on extreme commercial bearish positioning but prices continue rallying for several weeks, doubt naturally emerges. The table display provides reassurance. Commercial positioning remains extremely bearish. Divergence remains high. The positioning thesis remains intact even though price action has not yet confirmed. Alert functionality ensures traders do not miss signals due to inattention while also not requiring constant monitoring that can lead to emotional decision-making. Setting alerts for COT extremes enables a healthier relationship with markets. When meaningful signals occur, alerts notify them. They can then calmly assess the situation and execute planned responses. However, no indicator design can completely overcome the psychological difficulty of contrarian trading. Some traders simply cannot maintain short positions while prices rally. For these traders, COT analysis might be better employed as an exit signal for long positions rather than an entry signal for shorts. Ultimately, successful COT trading requires developing comfort with probabilistic thinking rather than certainty-seeking. The signals work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five or sixty percent win rate with proper risk management produces substantial profits over years, yet still means forty to forty-five percent of signals will be premature or wrong. COT analysis provides genuine edge, but edge means probability advantage, not elimination of losing trades. EDUCATIONAL RESOURCES AND CONTINUOUS LEARNING The indicator provides extensive built-in educational resources through its documentation, detailed tooltips, and transparent calculations. However, mastering COT analysis requires study beyond any single tool or resource. Several excellent resources provide valuable extensions of the concepts covered in this guide. Books and practitioner-focused monographs offer accessible entry points. Stephen Briese published The Commitments of Traders Bible in two thousand eight, offering detailed breakdowns of how different markets and trader categories behave (Briese, 2008). Briese's work stands out for its empirical focus and market-specific insights. Jack Schwager includes discussion of COT analysis within the broader context of market behavior in his book Market Sense and Nonsense (Schwager, 2012). Perry Kaufman's Trading Systems and Methods represents perhaps the most rigorous practitioner-focused text on systematic trading approaches including COT analysis (Kaufman, 2013). Academic journal articles provide the rigorous statistical foundation underlying COT analysis. The Journal of Futures Markets regularly publishes research on positioning data and its predictive properties. Bessembinder and Chan's earlier work on systematic risk, hedging pressure, and risk premiums in futures markets provides theoretical foundation (Bessembinder, 1992). Chang's examination of speculator returns provides historical context (Chang, 1985). Irwin and Sanders provide essential skeptical perspective in their two thousand twelve article (Irwin and Sanders, 2012). Wang's two thousand three article provides one of the most empirical analyses of COT data across multiple commodity markets (Wang, 2003). Online resources extend beyond academic and book-length treatments. The CFTC website provides free access to current and historical COT reports in multiple formats. The explanatory materials section offers detailed documentation of report construction, category definitions, and historical methodology changes. Traders serious about COT analysis should read these official CFTC documents to understand exactly what they are analyzing. Commercial COT data services such as Barchart provide enhanced visualization and analysis tools beyond raw CFTC data. TradingView's educational materials, published scripts library, and user community provide additional resources for exploring different approaches to COT analysis. The key to mastering COT analysis lies not in finding a single definitive source but rather in building understanding through multiple perspectives and information sources. Academic research provides rigorous empirical foundation. Practitioner-focused books offer practical implementation insights. Direct engagement with data through systematic backtesting develops intuition about how positioning dynamics manifest across different market conditions. SYNTHESIZING KNOWLEDGE INTO PRACTICE The COT Index indicator represents the synthesis of academic research, trading experience, and software engineering into a practical tool accessible to retail traders equipped with nothing more than a TradingView account and willingness to learn. What once required expensive data subscriptions, custom programming capabilities, statistical software, and institutional resources now appears as a straightforward indicator requiring only basic parameter selection and modest study to understand. This democratization of institutional-grade analysis tools represents a broader trend in financial markets over recent decades. Yet technology and data access alone provide no edge without understanding and discipline. Markets remain relentlessly efficient at eliminating edges that become too widely known and mechanically exploited. The COT Index indicator succeeds only when users invest time learning the underlying concepts, understand the limitations and probability distributions involved, and integrate signals thoughtfully into trading plans rather than applying them mechanically. The academic research demonstrates conclusively that institutional positioning contains genuine information about future price movements, particularly at extremes where commercial hedgers are maximally bearish or bullish relative to historical norms. This informational content is neither perfect nor deterministic but rather probabilistic, providing edge over many observations through identification of higher-probability configurations. Bessembinder and Chan's finding that commercial positioning explained modest but significant variance in future returns illustrates this probabilistic nature perfectly (Bessembinder and Chan, 1992). The effect is real and statistically significant, yet it explains perhaps ten to fifteen percent of return variance rather than most variance. Much of price movement remains unpredictable even with positioning intelligence. The practical implication is that COT analysis works best as one component of a trading system rather than a standalone oracle. It provides the positioning dimension, revealing where the smart money has positioned and where the crowd has followed, but price action analysis provides the timing dimension. Fundamental analysis provides the catalyst dimension. Risk management provides the survival dimension. These components work together synergistically. The indicator's design philosophy prioritizes transparency and education over black-box complexity, empowering traders to understand exactly what they are analyzing and why. Every calculation is documented and user-adjustable. The threshold markers, background coloring, tables, and clear signal states provide multiple reinforcing channels for conveying the same information. This educational approach reflects a conviction that sustainable trading success comes from genuine understanding rather than mechanical system-following. Traders who understand why commercial positioning matters, how different trader categories behave, what positioning extremes signify, and where signals fit within probability distributions can adapt when market conditions change. Traders mechanically following black-box signals without comprehension abandon systems after normal losing streaks. The research foundation supporting COT analysis comes primarily from commodity markets where commercial hedger informational advantages are most pronounced. Agricultural producers hedging crops know more about supply conditions than distant speculators. Energy companies hedging production know more about operating costs than financial traders. Metals miners hedging output know more about ore grades than index funds. Financial futures markets show weaker but still present effects. The journey from reading this documentation to profitable trading based on COT analysis involves several stages that cannot be rushed. Initial reading and basic understanding represents the first stage. Historical study represents the second stage, reviewing past market cycles to observe how positioning extremes preceded major turning points. Paper trading or small-size real trading represents the third stage to experience the psychological challenges. Refinement based on results and personal psychology represents the fourth stage. Markets will continue evolving. New participant categories will emerge. Regulatory structures will change. Technology will advance. Yet the fundamental dynamics driving COT analysis, that different market participants have different information, different motivations, and different forecasting abilities that manifest in their positioning, will persist as long as futures markets exist. While specific thresholds or optimal parameters may shift over time, the core logic remains sound and adaptable. The trader equipped with this indicator, understanding of the theory and evidence behind COT analysis, realistic expectations about probability rather than certainty, discipline to maintain positions through adverse volatility, and patience to allow signals time to develop possesses genuine edge in markets. The edge is not enormous, markets cannot allow large persistent inefficiencies without arbitraging them away, but it is real, measurable, and exploitable by those willing to invest in learning and disciplined application. REFERENCES Bessembinder, H. (1992) Systematic risk, hedging pressure, and risk premiums in futures markets, Review of Financial Studies, 5(4), pp. 637-667. Bessembinder, H. and Chan, K. (1992) The profitability of technical trading rules in the Asian stock markets, Pacific-Basin Finance Journal, 3(2-3), pp. 257-284. Briese, S. (2008) The Commitments of Traders Bible: How to Profit from Insider Market Intelligence. Hoboken: John Wiley & Sons. Chang, E.C. (1985) Returns to speculators and the theory of normal backwardation, Journal of Finance, 40(1), pp. 193-208. Commodity Futures Trading Commission (CFTC) (2009) Explanatory Notes: Disaggregated Commitments of Traders Report. Available at: www.cftc.gov (Accessed: 15 January 2025). Commodity Futures Trading Commission (CFTC) (2020) Commitments of Traders: About the Report. Available at: www.cftc.gov (Accessed: 15 January 2025). Irwin, S.H. and Sanders, D.R. (2012) Testing the Masters Hypothesis in commodity futures markets, Energy Economics, 34(1), pp. 256-269. Kaufman, P.J. (2013) Trading Systems and Methods. 5th edn. Hoboken: John Wiley & Sons. Ruan, Y. and Zhang, Y. (2018) Forecasting commodity futures prices using machine learning: Evidence from the Chinese commodity futures market, Applied Economics Letters, 25(12), pp. 845-849. Sanders, D.R., Boris, K. and Manfredo, M. (2004) Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports, Energy Economics, 26(3), pp. 425-445. Schwager, J.D. (2012) Market Sense and Nonsense: How the Markets Really Work and How They Don't. Hoboken: John Wiley & Sons. Tharp, V.K. (2008) Super Trader: Make Consistent Profits in Good and Bad Markets. New York: McGraw-Hill. Wang, C. (2003) The behavior and performance of major types of futures traders, Journal of Futures Markets, 23(1), pp. 1-31. Williams, L.R. and Noseworthy, M. (2009) The Right Stock at the Right Time: Prospering in the Coming Good Years. Hoboken: John Wiley & Sons. FURTHER READING For traders seeking to deepen their understanding of COT analysis and futures market positioning beyond this documentation, the following resources provide valuable extensions: Academic Journal Articles: Fishe, R.P.H. and Smith, A. (2012) Do speculators drive commodity prices away from supply and demand fundamentals?, Journal of Commodity Markets, 1(1), pp. 1-16. Haigh, M.S., Hranaiova, J. and Overdahl, J.A. (2007) Hedge funds, volatility, and liquidity provision in energy futures markets, Journal of Alternative Investments, 9(4), pp. 10-38. Kocagil, A.E. (1997) Does futures speculation stabilize spot prices? Evidence from metals markets, Applied Financial Economics, 7(1), pp. 115-125. Sanders, D.R. and Irwin, S.H. (2011) The impact of index funds in commodity futures markets: A systems approach, Journal of Alternative Investments, 14(1), pp. 40-49. Books and Practitioner Resources: Murphy, J.J. (1999) Technical Analysis of the Financial Markets: A Guide to Trading Methods and Applications. New York: New York Institute of Finance. Pring, M.J. (2002) Technical Analysis Explained: The Investor's Guide to Spotting Investment Trends and Turning Points. 4th edn. New York: McGraw-Hill. Federal Reserve and Research Institution Publications: Federal Reserve Banks regularly publish working papers examining commodity markets, futures positioning, and price discovery mechanisms. The Federal Reserve Bank of San Francisco and Federal Reserve Bank of Kansas City maintain active research programs in this area. Online Resources: The CFTC website provides free access to current and historical COT reports, explanatory materials, and regulatory documentation. Barchart offers enhanced COT data visualization and screening tools. TradingView's community library contains numerous published scripts and educational materials exploring different approaches to positioning analysis.

Indicateur Pine Script®

Quantum Market Harmonics [QMH]# Quantum Market Harmonics - TradingView Script Description ## 📊 OVERVIEW Quantum Market Harmonics (QMH) is a comprehensive multi-dimensional trading indicator that combines four independent analytical frameworks to generate high-probability trading signals with quantifiable confidence scores. Unlike simple indicator combinations that display multiple tools side-by-side, QMH synthesizes temporal analysis, inter-market correlations, behavioral psychology, and statistical probabilities into a unified confidence scoring system that requires agreement across all dimensions before generating a confirmed signal. --- ## 🎯 WHAT MAKES THIS SCRIPT ORIGINAL ### The Core Innovation: Weighted Confidence Scoring Most indicators provide binary signals (buy/sell) or display multiple indicators separately, leaving traders to interpret conflicting information. QMH's originality lies in its weighted confidence scoring system that: 1. **Combines Four Independent Methods** - Each framework (described below) operates independently and contributes points to an overall confidence score 2. **Requires Multi-Dimensional Agreement** - Signals only fire when multiple frameworks align, dramatically reducing false positives 3. **Quantifies Signal Strength** - Every signal includes a numerical confidence rating (0-100%), allowing traders to filter by quality 4. **Adapts to Market Conditions** - Different market regimes activate different component combinations ### Why This Combination is Useful Traditional approaches suffer from: - **Single-dimension bias**: RSI shows oversold, but trend is still down - **Conflicting signals**: MACD says buy, but volume is weak - **No prioritization**: All signals treated equally regardless of strength QMH solves these problems by requiring multiple independent confirmations and weighting each component's contribution to the final signal. This multi-dimensional approach mirrors how professional traders analyze markets - not relying on one indicator, but waiting for multiple pieces of evidence to align. --- ## 🔬 THE FOUR ANALYTICAL FRAMEWORKS ### 1. Temporal Fractal Resonance (TFR) **What It Does:** Analyzes trend alignment across four different timeframes simultaneously (15-minute, 1-hour, 4-hour, and daily) to identify periods of multi-timeframe synchronization. **How It Works:** - Uses `request.security()` with `lookahead=barmerge.lookahead_off` to retrieve confirmed price data from each timeframe - Calculates "fractal strength" for each timeframe using this formula: ``` Fractal Strength = (Rate of Change / Standard Deviation) × 100 ``` This creates a momentum-to-volatility ratio that measures trend strength relative to noise - Computes a Resonance Index when all four timeframes show the same directional bias - The index averages the absolute strength values when all timeframes align **Why This Method:** Fractal Market Hypothesis suggests that price patterns repeat across different time scales. When trends align from short-term (15m) to long-term (Daily), the probability of trend continuation increases substantially. The momentum/volatility ratio filters out low-conviction moves where volatility dominates direction. **Contribution to Confidence Score:** - TFR Bullish = +25 points - TFR Bearish = +25 points (to bearish confidence) - No alignment = 0 points --- ### 2. Cross-Asset Quantum Entanglement (CAQE) **What It Does:** Analyzes correlation patterns between the current asset and three reference markets (Bitcoin, US Dollar Index, and Volatility Index) to identify both normal correlation behavior and anomalous breakdowns that often precede significant moves. **How It Works:** - Retrieves price data from BTC (BINANCE:BTCUSDT), DXY (TVC:DXY), and VIX (TVC:VIX) using confirmed bars - Calculates Pearson correlation coefficient between the main asset and each reference: ``` Correlation = Covariance(X,Y) / (StdDev(X) × StdDev(Y)) ``` - Computes an Intermarket Pressure Index by weighting each reference asset's momentum by its correlation strength: ``` Pressure = (Corr₁ × ROC₁ + Corr₂ × ROC₂ + Corr₃ × ROC₃) / 3 ``` - Detects "correlation breakdowns" when average correlation drops below 0.3 **Why This Method:** Markets don't operate in isolation. Inter-market analysis (developed by John Murphy) recognizes that: - Crypto assets often correlate with Bitcoin - Risk assets inversely correlate with VIX (fear gauge) - Dollar strength affects commodity and crypto prices When these normal correlations break down, it signals potential regime changes. The term "quantum" reflects the interconnected nature of these relationships - like quantum entanglement where distant particles influence each other. **Contribution to Confidence Score:** - CAQE Bullish (positive pressure, stable correlations) = +25 points - CAQE Bearish (negative pressure, stable correlations) = +25 points (to bearish) - Correlation breakdown = Warning marker (potential reversal zone) --- ### 3. Adaptive Market Psychology Matrix (AMPM) **What It Does:** Classifies the current market emotional state into six distinct categories by analyzing the interaction between momentum (RSI), volume behavior, and volatility acceleration (ATR change). **How It Works:** The system evaluates three metrics: 1. **RSI (14-period)**: Measures overbought/oversold conditions 2. **Volume Analysis**: Compares current volume to 20-period average 3. **ATR Rate of Change**: Detects volatility acceleration Based on these inputs, the market is classified into: - **Euphoria**: RSI > 80, volume spike present, volatility rising (extreme bullish emotion) - **Greed**: RSI > 70, normal volume (moderate bullish emotion) - **Neutral**: RSI 40-60, declining volatility (balanced state) - **Fear**: RSI 40-60, low volatility (uncertainty without panic) - **Panic**: RSI < 30, volume spike present, volatility rising (extreme bearish emotion) - **Despair**: RSI < 20, normal volume (capitulation phase) **Why This Method:** Behavioral finance principles (Kahneman, Tversky) show that markets follow predictable emotional cycles. Extreme psychological states often mark reversal points because: - At Euphoria/Greed peaks, everyone bullish has already bought (no buyers left) - At Panic/Despair bottoms, everyone bearish has already sold (no sellers left) AMPM provides contrarian signals at these extremes while respecting trends during Fear and Greed intermediate states. **Contribution to Confidence Score:** - Psychology Bullish (Panic/Despair + RSI < 35) = +15 points - Psychology Bearish (Euphoria/Greed + RSI > 65) = +15 points - Neutral states = 0 points --- ### 4. Time-Decay Probability Zones (TDPZ) **What It Does:** Creates dynamic support and resistance zones based on statistical probability distributions that adapt to changing market volatility, similar to Bollinger Bands but with enhancements for trend environments. **How It Works:** - Calculates a 20-period Simple Moving Average as the basis line - Computes standard deviation of price over the same period - Creates four probability zones: - **Extreme Upper**: Basis + 2.5 standard deviations (≈99% probability boundary) - **Upper Zone**: Basis + 1.5 standard deviations - **Lower Zone**: Basis - 1.5 standard deviations - **Extreme Lower**: Basis - 2.5 standard deviations (≈99% probability boundary) - Dynamically adjusts zone width based on ATR (Average True Range): ``` Adjusted Upper = Upper Zone + (ATR × adjustment_factor) Adjusted Lower = Lower Zone - (ATR × adjustment_factor) ``` - The adjustment factor increases during high volatility, widening the zones **Why This Method:** Traditional support/resistance levels are static and don't account for volatility regimes. TDPZ zones are probability-based and mean-reverting: - Price has ≈99% probability of staying within extreme zones in normal conditions - Touches to extreme zones represent statistical outliers (high-probability reversal opportunities) - Zone expansion/contraction reflects volatility regime changes - ATR adjustment prevents false signals during unusual volatility The "time-decay" concept refers to mean reversion - the further price moves from the basis, the higher the probability of eventual return. **Contribution to Confidence Score:** - Price in Lower Extreme Zone = +15 points (bullish reversal probability) - Price in Upper Extreme Zone = +15 points (bearish reversal probability) - Price near basis = 0 points --- ## 🎯 HOW THE CONFIDENCE SCORING SYSTEM WORKS ### Signal Generation Formula QMH calculates separate Bullish and Bearish confidence scores each bar: **Bullish Confidence (0-100%):** ``` Base Score: 20 points + TFR Bullish: 25 points (if all 4 timeframes aligned bullish) + CAQE Bullish: 25 points (if intermarket pressure positive) + AMPM Bullish: 15 points (if Panic/Despair contrarian signal) + TDPZ Bullish: 15 points (if price in lower probability zones) ───────── Maximum Possible: 100 points ``` **Bearish Confidence (0-100%):** ``` Base Score: 20 points + TFR Bearish: 25 points (if all 4 timeframes aligned bearish) + CAQE Bearish: 25 points (if intermarket pressure negative) + AMPM Bearish: 15 points (if Euphoria/Greed contrarian signal) + TDPZ Bearish: 15 points (if price in upper probability zones) ───────── Maximum Possible: 100 points ``` ### Confirmed Signal Requirements A **QBUY** (Quantum Buy) signal generates when: 1. Bullish Confidence ≥ User-defined threshold (default 60%) 2. Bullish Confidence > Bearish Confidence 3. No active sell signal present A **QSELL** (Quantum Sell) signal generates when: 1. Bearish Confidence ≥ User-defined threshold (default 60%) 2. Bearish Confidence > Bullish Confidence 3. No active buy signal present ### Why This Approach Is Different **Example Comparison:** Traditional RSI Strategy: - RSI < 30 → Buy signal - Result: May buy into falling knife if trend remains bearish QMH Approach: - RSI < 30 → Psychology shows Panic (+15 points) - But requires additional confirmation: - Are all timeframes also showing bullish reversal? (+25 points) - Is intermarket pressure turning positive? (+25 points) - Is price at a statistical extreme? (+15 points) - Only when total ≥ 60 points does a QBUY signal fire This multi-layer confirmation dramatically reduces false signals while maintaining sensitivity to genuine opportunities. --- ## 🚫 NO REPAINT GUARANTEE **QMH is designed to be 100% repaint-free**, which is critical for honest backtesting and reliable live trading. ### Technical Implementation: 1. **All Multi-Timeframe Data Uses Confirmed Bars** ```pinescript tf1_close = request.security(syminfo.tickerid, "15", close , lookahead=barmerge.lookahead_off) ``` Using `close ` instead of `close ` ensures we only reference the previous confirmed bar, not the current forming bar. 2. **Lookahead Prevention** ```pinescript lookahead=barmerge.lookahead_off ``` This parameter prevents the function from accessing future data that wouldn't be available in real-time. 3. **Signal Timing** Signals appear on the bar AFTER all conditions are met, not retroactively on the bar where conditions first appeared. ### What This Means for Users: - **Backtest Accuracy**: Historical signals match exactly what you would have seen in real-time - **No Disappearing Signals**: Once a signal appears, it stays (though price may move against it) - **Honest Performance**: Results reflect true predictive power, not hindsight optimization - **Live Trading Reliability**: Alerts fire at the same time signals appear on the chart The dashboard displays "✓ NO REPAINT" to confirm this guarantee. --- ## 📖 HOW TO USE THIS INDICATOR ### Basic Trading Strategy **For Trend Followers:** 1. **Wait for Signal Confirmation** - QBUY label appears below a bar = Confirmed bullish entry opportunity - QSELL label appears above a bar = Confirmed bearish entry opportunity 2. **Check Confidence Score** - 60-70%: Moderate confidence (consider smaller position size) - 70-85%: High confidence (standard position size) - 85-100%: Very high confidence (consider larger position size) 3. **Enter Trade** - Long entry: Market or limit order near signal bar - Short entry: Market or limit order near signal bar 4. **Set Targets Using Probability Zones** - Long trades: Target the adjusted upper zone (lime line) - Short trades: Target the adjusted lower zone (red line) - Alternatively, target the basis line (yellow) for conservative exits 5. **Set Stop Loss** - Long trades: Below recent swing low minus 1 ATR - Short trades: Above recent swing high plus 1 ATR **For Mean Reversion Traders:** 1. **Wait for Extreme Zones** - Price touches extreme lower zone (dotted red line below) - Price touches extreme upper zone (dotted lime line above) 2. **Confirm with Psychology** - At lower extreme: Look for Panic or Despair state - At upper extreme: Look for Euphoria or Greed state 3. **Wait for Confidence Build** - Monitor dashboard until confidence exceeds threshold - Requires patience - extreme touches don't always reverse immediately 4. **Enter Reversal** - Target: Return to basis line (yellow SMA 20) - Stop: Beyond the extreme zone **For Position Traders (Longer Timeframes):** 1. **Use Daily Timeframe** - Set chart to daily for longer-term signals - Signals will be less frequent but higher quality 2. **Require High Confidence** - Filter setting: Min Confidence Score 80%+ - Only take the strongest multi-dimensional setups 3. **Confirm with Resonance Background** - Green tinted background = All timeframes bullish aligned - Red tinted background = All timeframes bearish aligned - Only enter when background tint matches signal direction 4. **Hold for Major Targets** - Long trades: Hold until extreme upper zone or opposite signal - Short trades: Hold until extreme lower zone or opposite signal --- ## 📊 DASHBOARD INTERPRETATION The QMH Dashboard (top-right corner) provides real-time market analysis across all four dimensions: ### Dashboard Elements: 1. **✓ NO REPAINT** - Green confirmation that signals don't repaint - Always visible to remind users of signal integrity 2. **SIGNAL: BULL/BEAR XX%** - Shows dominant direction (whichever confidence is higher) - Displays current confidence percentage - Background color intensity reflects confidence level 3. **Psychology: ** - Current market emotional state - Color coded: - Orange = Euphoria (extreme bullish emotion) - Yellow = Greed (moderate bullish emotion) - Gray = Neutral (balanced state) - Purple = Fear (uncertainty) - Red = Panic (extreme bearish emotion) - Dark red = Despair (capitulation) 4. **Resonance: ** - Multi-timeframe alignment strength - Positive = All timeframes bullish aligned - Negative = All timeframes bearish aligned - Near zero = Timeframes not synchronized - Emoji indicator: 🔥 (bullish resonance) ❄️ (bearish resonance) 5. **Intermarket: ** - Cross-asset pressure measurement - Positive = BTC/DXY/VIX correlations supporting upside - Negative = Correlations supporting downside - Warning ⚠️ if correlation breakdown detected 6. **RSI: ** - Current RSI(14) reading - Background colors: Red (>70 overbought), Green (<30 oversold) - Status: OB (overbought), OS (oversold), or • (neutral) 7. **Status: READY BUY / READY SELL / WAIT** - Quick trade readiness indicator - READY BUY: Confidence ≥ threshold, bias bullish - READY SELL: Confidence ≥ threshold, bias bearish - WAIT: Confidence below threshold ### How to Use Dashboard: **Before Entering a Trade:** - Verify Status shows READY (not WAIT) - Check that Resonance matches signal direction - Confirm Psychology isn't contradicting (e.g., buying during Euphoria) - Note Intermarket value - breakdowns (⚠️) suggest caution **During a Trade:** - Monitor Psychology shifts (e.g., from Fear to Greed in a long) - Watch for Resonance changes that could signal exit - Check for Intermarket breakdown warnings --- ## ⚙️ CUSTOMIZATION SETTINGS ### TFR Settings (Temporal Fractal Resonance) - **Enable/Disable**: Turn TFR analysis on/off - **Fractal Sensitivity** (5-50, default 14): - Lower values = More responsive to short-term changes - Higher values = More stable, slower to react - Recommendation: 14 for balanced, 7 for scalping, 21 for position trading ### CAQE Settings (Cross-Asset Quantum Entanglement) - **Enable/Disable**: Turn CAQE analysis on/off - **Asset 1** (default BTC): Reference asset for correlation analysis - **Asset 2** (default DXY): Second reference asset - **Asset 3** (default VIX): Third reference asset - **Correlation Length** (10-100, default 20): - Lower values = More sensitive to recent correlation changes - Higher values = More stable correlation measurements - Recommendation: 20 for most assets, 50 for less volatile markets ### Psychology Settings (Adaptive Market Psychology Matrix) - **Enable/Disable**: Turn AMPM analysis on/off - **Volume Spike Threshold** (1.0-5.0x, default 2.0): - Lower values = Detect smaller volume increases as spikes - Higher values = Only flag major volume surges - Recommendation: 2.0 for stocks, 1.5 for crypto ### Probability Settings (Time-Decay Probability Zones) - **Enable/Disable**: Turn TDPZ visualization on/off - **Probability Lookback** (20-200, default 50): - Lower values = Zones adapt faster to recent price action - Higher values = Zones based on longer statistical history - Recommendation: 50 for most uses, 100 for position trading ### Filter Settings - **Min Confidence Score** (40-95%, default 60%): - Lower threshold = More signals, more false positives - Higher threshold = Fewer signals, higher quality - Recommendation: 60% for active trading, 75% for selective trading ### Visual Settings - **Show Entry Signals**: Toggle QBUY/QSELL labels on chart - **Show Probability Zones**: Toggle zone visualization - **Show Psychology State**: Toggle dashboard display --- ## 🔔 ALERT CONFIGURATION QMH includes four alert conditions that can be configured via TradingView's alert system: ### Available Alerts: 1. **Quantum Buy Signal** - Fires when: Confirmed QBUY signal generates - Message includes: Confidence percentage - Use for: Entry notifications 2. **Quantum Sell Signal** - Fires when: Confirmed QSELL signal generates - Message includes: Confidence percentage - Use for: Entry notifications or exit warnings 3. **Market Panic** - Fires when: Psychology state reaches Panic - Use for: Contrarian opportunity alerts 4. **Market Euphoria** - Fires when: Psychology state reaches Euphoria - Use for: Reversal warning alerts ### How to Set Alerts: 1. Right-click on chart → "Add Alert" 2. Condition: Select "Quantum Market Harmonics" 3. Choose alert type from dropdown 4. Configure expiration, frequency, and notification method 5. Create alert **Recommendation**: Set alerts for Quantum Buy/Sell signals with "Once Per Bar Close" frequency to avoid intra-bar false triggers. --- ## 💡 BEST PRACTICES ### For All Users: 1. **Backtest First** - Test on your specific market and timeframe before live trading - Different assets may perform better with different confidence thresholds - Verify that the No Repaint guarantee works as described 2. **Paper Trade** - Practice with signals on a demo account first - Understand typical signal frequency for your timeframe - Get comfortable with the dashboard interpretation 3. **Risk Management** - Never risk more than 1-2% of capital per trade - Use proper stop losses (not just mental stops) - Position size based on confidence score (larger size at higher confidence) 4. **Consider Context** - QMH signals work best in clear trends or at extremes - During tight consolidation, false signals increase - Major news events can invalidate technical signals ### Optimal Use Cases: **QMH Works Best When:** - ✅ Markets are trending (up or down) - ✅ Volatility is normal to elevated - ✅ Price reaches probability zone extremes - ✅ Multiple timeframes align - ✅ Clear inter-market relationships exist **QMH Is Less Effective When:** - ❌ Extremely low volatility (zones contract too much) - ❌ Sideways choppy markets (conflicting timeframes) - ❌ Flash crashes or news events (correlations break down) - ❌ Very illiquid assets (irregular price action) ### Session Considerations: - **24/7 Markets (Crypto)**: Works on all sessions, but signals may be more reliable during high-volume periods (US/European trading hours) - **Forex**: Best during London/New York overlap when volume is highest - **Stocks**: Most reliable during regular trading hours (not pre-market/after-hours) --- ## ⚠️ LIMITATIONS AND RISKS ### This Indicator Cannot: - **Predict Black Swan Events**: Sudden unexpected events invalidate technical analysis - **Guarantee Profits**: No indicator is 100% accurate; losses will occur - **Replace Risk Management**: Always use stop losses and proper position sizing - **Account for Fundamental Changes**: Company news, economic data, etc. can override technical signals - **Work in All Market Conditions**: Less effective during extreme low volatility or major news events ### Known Limitations: 1. **Multi-Timeframe Lag**: Uses confirmed bars (`close `), so signals appear one bar after conditions met 2. **Correlation Dependency**: CAQE requires sufficient history; may be less reliable on newly listed assets 3. **Computational Load**: Multiple `request.security()` calls may cause slower performance on older devices 4. **Repaint of Dashboard**: Dashboard updates every bar (by design), but signals themselves don't repaint ### Risk Warnings: - Past performance doesn't guarantee future results - Backtesting results may not reflect actual trading results due to slippage, commissions, and execution delays - Different markets and timeframes may produce different results - The indicator should be used as a tool, not as a standalone trading system - Always combine with your own analysis, risk management, and trading plan --- ## 🎓 EDUCATIONAL CONCEPTS This indicator synthesizes several established financial theories and technical analysis concepts: ### Academic Foundations: 1. **Fractal Market Hypothesis** (Edgar Peters) - Markets exhibit self-similar patterns across time scales - Implemented via multi-timeframe resonance analysis 2. **Behavioral Finance** (Kahneman & Tversky) - Investor psychology drives market inefficiencies - Implemented via market psychology state classification 3. **Intermarket Analysis** (John Murphy) - Asset classes correlate and influence each other predictably - Implemented via cross-asset correlation monitoring 4. **Mean Reversion** (Statistical Arbitrage) - Prices tend to revert to statistical norms - Implemented via probability zones and standard deviation bands 5. **Multi-Timeframe Analysis** (Technical Analysis Standard) - Higher timeframe trends dominate lower timeframe noise - Implemented via fractal resonance scoring ### Learning Resources: To better understand the concepts behind QMH: - Read "Intermarket Analysis" by John Murphy (for CAQE concepts) - Study "Thinking, Fast and Slow" by Daniel Kahneman (for psychology concepts) - Review "Fractal Market Analysis" by Edgar Peters (for TFR concepts) - Learn about Bollinger Bands (for TDPZ foundation) --- ## 🔄 VERSION HISTORY AND UPDATES **Current Version: 1.0** This is the initial public release. Future updates will be published using TradingView's Update feature (not as separate publications). Planned improvements may include: - Additional reference assets for CAQE - Optional machine learning-based weight optimization - Customizable psychology state definitions - Alternative probability zone calculations - Performance metrics tracking Check the "Updates" tab on the script page for version history. --- ## 📞 SUPPORT AND FEEDBACK ### How to Get Help: 1. **Read This Description First**: Most questions are answered in the detailed sections above 2. **Check Comments**: Other users may have asked similar questions 3. **Post Comments**: For general questions visible to the community 4. **Use TradingView Messaging**: For private inquiries (if available) ### Providing Useful Feedback: When reporting issues or suggesting improvements: - Specify your asset, timeframe, and settings - Include a screenshot if relevant - Describe expected vs. actual behavior - Check if issue persists with default settings ### Continuous Improvement: This indicator will evolve based on user feedback and market testing. Constructive suggestions for improvements are always welcome. --- ## ⚖️ DISCLAIMER This indicator is provided for **educational and informational purposes only**. It does **not constitute financial advice, investment advice, trading advice, or any other type of advice**. **Important Disclaimers:** - You should **not** rely solely on this indicator to make trading decisions - Always conduct your own research and due diligence - Past performance is not indicative of future results - Trading and investing involve substantial risk of loss - Only trade with capital you can afford to lose - Consider consulting with a licensed financial advisor before trading - The author is not responsible for any trading losses incurred using this indicator **By using this indicator, you acknowledge:** - You understand the risks of trading - You take full responsibility for your trading decisions - You will use proper risk management techniques - You will not hold the author liable for any losses --- ## 🙏 ACKNOWLEDGMENTS This indicator builds upon the collective knowledge of the technical analysis and trading community. While the specific implementation and combination are original, the underlying concepts draw from: - The Pine Script community on TradingView - Academic research in behavioral finance and market microstructure - Classical technical analysis methods developed over decades - Open-source indicators that demonstrate best practices in Pine Script coding Special thanks to TradingView for providing the platform and Pine Script language that make indicators like this possible. --- ## 📚 ADDITIONAL RESOURCES **Pine Script Documentation:** - Official Pine Script Manual: www.tradingview.com **Related Concepts to Study:** - Multi-timeframe analysis techniques - Correlation analysis in financial markets - Behavioral finance principles - Mean reversion strategies - Bollinger Bands methodology **Recommended TradingView Tools:** - Strategy Tester: To backtest signal performance - Bar Replay: To see how signals develop in real-time - Alert System: To receive notifications of new signals --- **Thank you for using Quantum Market Harmonics. Trade safely and responsibly.**

Indicateur Pine Script®

par Smart-Day-Trader

WorldCup Dashboard + Institutional Sessions © 2025 NewMeta™ — Educational use only. # Full, Premium Description ## WorldCup Dashboard + Institutional Sessions **A trade-ready, intraday framework that combines market structure, real flow, and institutional timing.** This toolkit fuses **Institutional Sessions** with a **price–volume decision engine** so you can see *who is active*, *where value sits*, and *whether the drive is real*. You get: **CVD/Delta**, volume-weighted **Momentum**, **Aggression** spikes, **FVG (MTF)** with nearest side, **Daily Volume Profile (VAH/POC/VAL)**, **ATR regime**, a **24h position gauge**, classic **candle patterns**, IBH/IBL + **first-hour “true close”** lines, and a **10-vote confluence scoreboard**—all in one view. --- ## What’s inside (and how to trade it) ### 🌍 Institutional Sessions (Sydney • Tokyo • London • New York) * Session boxes + a highlighted **first hour**. * Plots the **true close** (first-hour close) as a running line with a label. **Use:** Many desks anchor risk to this print. Above = bullish bias; below = bearish. **IBH/IBL** breaks during London/NY carry the most signal. ### 📊 CVD / Delta (Flow) * Net buyer vs seller pressure with smooth trend state. **Use:** **Rising CVD + acceptance above mid/POC** confirms continuation. Bearish price + rising CVD = caution (possible absorption). ### ⚡ Volume-Weighted Momentum * Momentum adjusted by participation quality (volume). **Use:** Momentum>MA and >0 → trend drive is “real”; <0 and falling → distribution risk. ### 🔥 Aggression Detector * ROC × normalized volume × wick factor to flag **forceful** candles. **Use:** On spikes, avoid fading blindly—wait for pullbacks into **aligned FVG** or for aggression to cool. ### 🟦🟪 Fair Value Gaps (with MTF) * Detects up to 3 recent FVGs and marks the **nearest** side to price. **Use:** Trend pullbacks into **bullish FVG** for longs; bounces into **bearish FVG** for shorts. Optional threshold to filter weak gaps. ### 🧭 24h Gauge (positioning) * Shows current price across the 24h low⇢high with a mid reference. **Use:** Above mid and pushing upper third = momentum continuation setups; below mid = sell the rips bias. ### 🧱 Daily Volume Profile (manual per day) * **VAH / POC / VAL** derived from discretized rows. **Use:** **POC below** supports longs; **POC above** caps rallies. Fade VAH/VAL in ranges; treat them as break/hold levels in trends. ### 📈 ATR Regime * **ATR vs ATR-avg** with direction and regime flag (**HIGH / NORMAL / LOW**). **Use:** HIGH ⇒ give trades room & favor trend following. LOW ⇒ fade edges, scale targets. ### 🕯️ Candle Patterns (contextual, not standalone) * Engulfings, Morning/Evening Star, 3 Soldiers/Crows, Harami, Hammer/Shooting Star, Double Top/Bottom. **Use:** Only with session + flow + momentum alignment. ### 🤝 Price–Volume Classification * Labels each bar as **continuation**, **exhaustion**, **distribution**, or **healthy pullback**. **Use:** Align continuation reads with trend; treat “Price↑ + Vol↓” as a caution flag. ### 🧪 Confluence Scoreboard & B/S Meter * Ten elements vote: 🔵 bull, ⚪ neutral, 🟣 bear. **Use:** Execution filter—take setups when the board’s skew matches your trade direction. --- ## Playbooks (actionable) **Trend Pullback (Long)** 1. London/NY active, Momentum↑, CVD↑, price above 24h mid & POC. 2. Pullback into **nearest bullish FVG**. 3. Invalidate under FVG low or **true-close** line. 4. Targets: IBH → VAH → 24h high. **Range Fade (Short)** 1. Asia/quiet regime, **Price↑ + Vol↓** into **VAH**, ATR low. 2. Nearest FVG bearish or scoreboard skew bearish. 3. Invalidate above VAH/IBH. 4. Targets: POC → VAL. **News/Impulse** Aggression spike? Don’t chase. Let it pull back into the aligned FVG; require CVD/Momentum agreement before entry. --- ## Alerts (included) * **Bull/Bear Confluence ≥ 7/10** * **Intraday Target Achieved** / **Daily Target Achieved** * **Session True-Close Retests** (Sydney/Tokyo/London/NY) *(Keep alerts “Once per bar” unless you specifically want intrabar triggers.)* --- ## Setup Tips * **UTC**: Choose the reference that matches how you track sessions (default UTC+2). * **Volume threshold**: 2.0× is a strong baseline; raise for noisy alts, lower for majors. * **CVD smoothing**: 14–24 for scalps; 24–34 for slower markets. * **ATR lengths**: Keep defaults unless your asset has a persistent regime shift. --- ## Why this framework? Because **timing (sessions)**, **truth (flow)**, and **location (value/FVG)** together beat any single signal. You get *who is trading*, *how strong the push is*, and *where risk lives*—on one screen—so execution is faster and cleaner. --- **Disclaimer**: Educational use only. Not financial advice. Markets are risky—backtest and size responsibly.

Indicateur Pine Script®

par onedaywillbebillionaire

Mis à jour

多周期趋势动量面板加强版（Multi-Timeframe Trend Momentum Panel - User Guide）多周期趋势动量面板(Multi-Timeframe Trend Momentum Panel - User Guide)(english explanation follows.) 📖 指标功能详解 (精简版): 🎯 核心功能: 1. 多周期趋势分析同时监控8个时间周期(1m/5m/15m/1H/4H/D/W/M) 2. 4维度投票系统 MA趋势+RSI动量+MACD+布林带综合判断 3. 全球交易时段可视化亚洲/伦敦/纽约交易时间 4. 趋势强度评分 0100%量化市场力量 5. 智能警报强势多空信号自动推送 ________________________________________ 📚 重要名词解释: 🔵 趋势状态 (MA均线分析): 名词含义信号强度强势多头快MA远高于慢MA(差值≥0.35%) ⭐⭐⭐⭐⭐ 做多多头倾向快MA略高于慢MA(差值<0.35%) ⭐⭐⭐ 谨慎做多震荡快慢MA缠绕,无明确方向 ⚠️ 观望空头倾向快MA略低于慢MA ⭐⭐⭐ 谨慎做空强势空头快MA远低于慢MA ⭐⭐⭐⭐⭐ 做空简单理解: 快MA就像短跑运动员(反应快),慢MA是长跑运动员(稳定)。短跑远超长跑=强势多头,反之=强势空头。 ________________________________________ 🟠 动量状态 (RSI力度分析): 名词含义操作建议动量上攻↗ RSI>60且快速上升强烈买入信号动量高位 RSI>60但上升变慢警惕回调,可减仓动量中性 RSI在4060之间,平稳等待方向明确动量低位 RSI<40但下跌变慢警惕反弹,可止盈动量下压↘ RSI<40且快速下降强烈卖出信号简单理解: RSI就像汽车速度表。"动量上攻"=油门踩到底加速,"动量高位"=已经很快但不再加速了。 ________________________________________ 🟣 辅助信号: MACD: • MACD多头 = 柱状图>0 = 买方力量强 • MACD空头 = 柱状图<0 = 卖方力量强布林带(BB): • BB超买 = 价格在布林带上轨附近 = 可能回调 • BB超卖 = 价格在布林带下轨附近 = 可能反弹 • BB中轨 = 价格在中间位置 = 平衡状态 ________________________________________ 💡 快速上手 3步看懂面板: 第1步: 看"综合结论标签" (K线上方) • 绿色"多头占优" → 可以做多 • 红色"空头占优" → 可以做空 • 橙色"震荡/均衡" → 观望第2步: 看"票数多/空" (面板最下方) • 多头票数远大于空头 (差距>2) → 趋势强 • 票数接近 (差距<1) → 震荡市第3步: 看"趋势强度" (综合标签中) • 强度>70% → 强势趋势,可重仓 • 强度5070% → 中等趋势,正常仓位 • 强度<50% → 弱势,轻仓或观望 ________________________________________ 🎨 时段背景色含义: • 紫色背景 = 亚洲时段 (东京交易时间) 波动较小 • 橙色背景 = 伦敦时段 (欧洲交易时间) 波动增大 • 蓝色背景 = 纽约凌晨美盘准备阶段 • 红色背景 = 纽约关键5分钟 (09:3009:35) ⚠️ 最重要! 市场最活跃,趋势易形成 • 绿色背景 = 纽约上午后段延续早盘趋势交易建议: 重点关注红色关键时段,这5分钟往往决定全天方向! ________________________________________ ⚙️ 三大市场推荐设置 🥇 黄金: Hull MA 12/EMA 34, 阈值0.250.35% ₿ 比特币: EMA 21/EMA 55, 阈值0.801.20% 💎 以太坊: TEMA 21/EMA 55, 阈值0.600.80% 参数优化建议黄金 (XAUUSD) 快速MA: Hull MA 12 (超灵敏捕捉黄金快速波动) 慢速MA: EMA 34 (斐波那契数列) RSI周期: 9 (加快反应) 强趋势阈值: 0.25% 周期: 5, 15, 60, 240, 1440 比特币 (BTCUSD) 快速MA: EMA 21 慢速MA: EMA 55 RSI周期: 14 强趋势阈值: 0.8% (波动大,阈值需提高) 周期: 15, 60, 240, D, W 外汇 EUR/USD 快速MA: TEMA 10 (快速响应) 慢速MA: T3 30, 因子0.7 (平滑噪音) RSI周期: 14 强趋势阈值: 0.08% (外汇波动小) 周期: 5, 15, 60, 240, 1440 📖 Indicator Function Details (Concise Version): 🎯 Core Functions: 1. MultiTimeframe Trend Analysis Monitors 8 timeframes simultaneously (1m/5m/15m/1H/4H/D/W/M) 2. 4Dimensional Voting System Comprehensive judgment based on MA trend + RSI momentum + MACD + Bollinger Bands 3. Global Trading Sessions Visualizes Asia/London/New York trading hours 4. Trend Strength Score Quantifies market strength from 0100% 5. Smart Alerts Automatically pushes strong bullish/bearish signals 📚 Key Term Explanations: 🔵 Trend Status (MA Analysis): | Term | Meaning | Signal Strength | | | | | | Strong Bull | Fast MA significantly > Slow MA (Diff ≥0.35%) | ⭐⭐⭐⭐⭐ Long | | Bullish Bias | Fast MA slightly > Slow MA (Diff <0.35%) | ⭐⭐⭐ Caution Long | | Ranging | MAs intertwined, no clear direction | ⚠️ Wait & See | | Bearish Bias | Fast MA slightly < Slow MA | ⭐⭐⭐ Caution Short | | Strong Bear | Fast MA significantly < Slow MA | ⭐⭐⭐⭐⭐ Short | Simple Understanding: Fast MA = sprinter (fast reaction), Slow MA = longdistance runner (stable). Sprinter far ahead = Strong Bull, opposite = Strong Bear. 🟠 Momentum Status (RSI Analysis): | Term | Meaning | Trading Suggestion | | | | | | Momentum Up ↗ | RSI >60 & rising rapidly | Strong Buy Signal | | Momentum High | RSI >60 but rising slower | Watch for pullback, consider reducing position | | Momentum Neutral | RSI between 4060, stable | Wait for clearer direction | | Momentum Low | RSI <40 but falling slower | Watch for rebound, consider taking profit | | Momentum Down ↘ | RSI <40 & falling rapidly | Strong Sell Signal | Simple Understanding: RSI = car speedometer. "Momentum Up" = full throttle acceleration, "Momentum High" = already fast but not accelerating further. 🟣 Auxiliary Signals: MACD: MACD Bullish = Histogram >0 = Strong buyer power MACD Bearish = Histogram <0 = Strong seller power Bollinger Bands (BB): BB Overbought = Price near upper band = Possible pullback BB Oversold = Price near lower band = Possible rebound BB Middle = Price near middle band = Balanced state 💡 Quick Start 3 Steps to Understand the Panel: Step 1: Check "Composite Conclusion Label" (Above the chart) Green "Bulls Favored" → Consider Long Red "Bears Favored" → Consider Short Orange "Ranging/Balanced" → Wait & See Step 2: Check "Votes Bull/Bear" (Bottom of the panel) Bull votes significantly > Bear votes (Difference >2) → Strong Trend Votes close (Difference <1) → Ranging Market Step 3: Check "Trend Strength" (In the composite label) Strength >70% → Strong Trend, consider heavier position Strength 5070% → Moderate Trend, normal position size Strength <50% → Weak Trend, light position or wait & see 🎨 Trading Session Background Color Meanings: Purple = Asian Session (Tokyo hours) Lower volatility Orange = London Session (European hours) Increased volatility Blue = NY Early Morning US session preparation phase Red = NY Critical 5 Minutes (09:3009:35) ⚠️ Most Important! Market most active, trends easily form Green = NY Late Morning Continuation of early session trend Trading Tip: Focus on the red critical period; these 5 minutes often determine the day's direction! ⚙️ Recommended Settings for Three Major Markets 🥇 Gold (XAUUSD): Fast MA: Hull MA 12 (Highly sensitive for gold's fast moves) Slow MA: EMA 34 (Fibonacci number) RSI Period: 9 (Faster reaction) Strong Trend Threshold: 0.25% Timeframes: 5, 15, 60, 240, 1440 ₿ Bitcoin (BTCUSD): Fast MA: EMA 21 Slow MA: EMA 55 RSI Period: 14 Strong Trend Threshold: 0.8% (High volatility, requires higher threshold) Timeframes: 15, 60, 240, D, W 💎 Ethereum (ETHUSD): Fast MA: TEMA 21 Slow MA: EMA 55 RSI Period: 14 Strong Trend Threshold: 0.600.80% Timeframes: 15, 60, 240, D, W 💱 Forex EUR/USD: Fast MA: TEMA 10 (Fast response) Slow MA: T3 30, Factor 0.7 (Smooths noise) RSI Period: 14 Strong Trend Threshold: 0.08% (Forex has low volatility) Timeframes: 5, 15, 60, 240, 1440

Indicateur Pine Script®

多周期趋势动量面板(Multi-Timeframe Trend Momentum Panel - User Guide)多周期趋势动量面板(Multi-Timeframe Trend Momentum Panel - User Guide)(english explanation follows.) 📖 指标功能详解 (精简版): 🎯 核心功能: 1. 多周期趋势分析同时监控8个时间周期(1m/5m/15m/1H/4H/D/W/M) 2. 4维度投票系统 MA趋势+RSI动量+MACD+布林带综合判断 3. 全球交易时段可视化亚洲/伦敦/纽约交易时间 4. 趋势强度评分 0100%量化市场力量 5. 智能警报强势多空信号自动推送 ________________________________________ 📚 重要名词解释: 🔵 趋势状态 (MA均线分析): 名词含义信号强度强势多头快MA远高于慢MA(差值≥0.35%) ⭐⭐⭐⭐⭐ 做多多头倾向快MA略高于慢MA(差值<0.35%) ⭐⭐⭐ 谨慎做多震荡快慢MA缠绕,无明确方向 ⚠️ 观望空头倾向快MA略低于慢MA ⭐⭐⭐ 谨慎做空强势空头快MA远低于慢MA ⭐⭐⭐⭐⭐ 做空简单理解: 快MA就像短跑运动员(反应快),慢MA是长跑运动员(稳定)。短跑远超长跑=强势多头,反之=强势空头。 ________________________________________ 🟠 动量状态 (RSI力度分析): 名词含义操作建议动量上攻↗ RSI>60且快速上升强烈买入信号动量高位 RSI>60但上升变慢警惕回调,可减仓动量中性 RSI在4060之间,平稳等待方向明确动量低位 RSI<40但下跌变慢警惕反弹,可止盈动量下压↘ RSI<40且快速下降强烈卖出信号简单理解: RSI就像汽车速度表。"动量上攻"=油门踩到底加速,"动量高位"=已经很快但不再加速了。 ________________________________________ 🟣 辅助信号: MACD: • MACD多头 = 柱状图>0 = 买方力量强 • MACD空头 = 柱状图<0 = 卖方力量强布林带(BB): • BB超买 = 价格在布林带上轨附近 = 可能回调 • BB超卖 = 价格在布林带下轨附近 = 可能反弹 • BB中轨 = 价格在中间位置 = 平衡状态 ________________________________________ 💡 快速上手 3步看懂面板: 第1步: 看"综合结论标签" (K线上方) • 绿色"多头占优" → 可以做多 • 红色"空头占优" → 可以做空 • 橙色"震荡/均衡" → 观望第2步: 看"票数多/空" (面板最下方) • 多头票数远大于空头 (差距>2) → 趋势强 • 票数接近 (差距<1) → 震荡市第3步: 看"趋势强度" (综合标签中) • 强度>70% → 强势趋势,可重仓 • 强度5070% → 中等趋势,正常仓位 • 强度<50% → 弱势,轻仓或观望 ________________________________________ 🎨 时段背景色含义: • 紫色背景 = 亚洲时段 (东京交易时间) 波动较小 • 橙色背景 = 伦敦时段 (欧洲交易时间) 波动增大 • 蓝色背景 = 纽约凌晨美盘准备阶段 • 红色背景 = 纽约关键5分钟 (09:3009:35) ⚠️ 最重要! 市场最活跃,趋势易形成 • 绿色背景 = 纽约上午后段延续早盘趋势交易建议: 重点关注红色关键时段,这5分钟往往决定全天方向! ________________________________________ ⚙️ 三大市场推荐设置 🥇 黄金: Hull MA 12/EMA 34, 阈值0.250.35% ₿ 比特币: EMA 21/EMA 55, 阈值0.801.20% 💎 以太坊: TEMA 21/EMA 55, 阈值0.600.80% 参数优化建议黄金 (XAUUSD) 快速MA: Hull MA 12 (超灵敏捕捉黄金快速波动) 慢速MA: EMA 34 (斐波那契数列) RSI周期: 9 (加快反应) 强趋势阈值: 0.25% 周期: 5, 15, 60, 240, 1440 比特币 (BTCUSD) 快速MA: EMA 21 慢速MA: EMA 55 RSI周期: 14 强趋势阈值: 0.8% (波动大,阈值需提高) 周期: 15, 60, 240, D, W 外汇 EUR/USD 快速MA: TEMA 10 (快速响应) 慢速MA: T3 30, 因子0.7 (平滑噪音) RSI周期: 14 强趋势阈值: 0.08% (外汇波动小) 周期: 5, 15, 60, 240, 1440 📖 Indicator Function Details (Concise Version): 🎯 Core Functions: 1. MultiTimeframe Trend Analysis Monitors 8 timeframes simultaneously (1m/5m/15m/1H/4H/D/W/M) 2. 4Dimensional Voting System Comprehensive judgment based on MA trend + RSI momentum + MACD + Bollinger Bands 3. Global Trading Sessions Visualizes Asia/London/New York trading hours 4. Trend Strength Score Quantifies market strength from 0100% 5. Smart Alerts Automatically pushes strong bullish/bearish signals 📚 Key Term Explanations: 🔵 Trend Status (MA Analysis): | Term | Meaning | Signal Strength | | | | | | Strong Bull | Fast MA significantly > Slow MA (Diff ≥0.35%) | ⭐⭐⭐⭐⭐ Long | | Bullish Bias | Fast MA slightly > Slow MA (Diff <0.35%) | ⭐⭐⭐ Caution Long | | Ranging | MAs intertwined, no clear direction | ⚠️ Wait & See | | Bearish Bias | Fast MA slightly < Slow MA | ⭐⭐⭐ Caution Short | | Strong Bear | Fast MA significantly < Slow MA | ⭐⭐⭐⭐⭐ Short | Simple Understanding: Fast MA = sprinter (fast reaction), Slow MA = longdistance runner (stable). Sprinter far ahead = Strong Bull, opposite = Strong Bear. 🟠 Momentum Status (RSI Analysis): | Term | Meaning | Trading Suggestion | | | | | | Momentum Up ↗ | RSI >60 & rising rapidly | Strong Buy Signal | | Momentum High | RSI >60 but rising slower | Watch for pullback, consider reducing position | | Momentum Neutral | RSI between 4060, stable | Wait for clearer direction | | Momentum Low | RSI <40 but falling slower | Watch for rebound, consider taking profit | | Momentum Down ↘ | RSI <40 & falling rapidly | Strong Sell Signal | Simple Understanding: RSI = car speedometer. "Momentum Up" = full throttle acceleration, "Momentum High" = already fast but not accelerating further. 🟣 Auxiliary Signals: MACD: MACD Bullish = Histogram >0 = Strong buyer power MACD Bearish = Histogram <0 = Strong seller power Bollinger Bands (BB): BB Overbought = Price near upper band = Possible pullback BB Oversold = Price near lower band = Possible rebound BB Middle = Price near middle band = Balanced state 💡 Quick Start 3 Steps to Understand the Panel: Step 1: Check "Composite Conclusion Label" (Above the chart) Green "Bulls Favored" → Consider Long Red "Bears Favored" → Consider Short Orange "Ranging/Balanced" → Wait & See Step 2: Check "Votes Bull/Bear" (Bottom of the panel) Bull votes significantly > Bear votes (Difference >2) → Strong Trend Votes close (Difference <1) → Ranging Market Step 3: Check "Trend Strength" (In the composite label) Strength >70% → Strong Trend, consider heavier position Strength 5070% → Moderate Trend, normal position size Strength <50% → Weak Trend, light position or wait & see 🎨 Trading Session Background Color Meanings: Purple = Asian Session (Tokyo hours) Lower volatility Orange = London Session (European hours) Increased volatility Blue = NY Early Morning US session preparation phase Red = NY Critical 5 Minutes (09:3009:35) ⚠️ Most Important! Market most active, trends easily form Green = NY Late Morning Continuation of early session trend Trading Tip: Focus on the red critical period; these 5 minutes often determine the day's direction! ⚙️ Recommended Settings for Three Major Markets 🥇 Gold (XAUUSD): Fast MA: Hull MA 12 (Highly sensitive for gold's fast moves) Slow MA: EMA 34 (Fibonacci number) RSI Period: 9 (Faster reaction) Strong Trend Threshold: 0.25% Timeframes: 5, 15, 60, 240, 1440 ₿ Bitcoin (BTCUSD): Fast MA: EMA 21 Slow MA: EMA 55 RSI Period: 14 Strong Trend Threshold: 0.8% (High volatility, requires higher threshold) Timeframes: 15, 60, 240, D, W 💎 Ethereum (ETHUSD): Fast MA: TEMA 21 Slow MA: EMA 55 RSI Period: 14 Strong Trend Threshold: 0.600.80% Timeframes: 15, 60, 240, D, W 💱 Forex EUR/USD: Fast MA: TEMA 10 (Fast response) Slow MA: T3 30, Factor 0.7 (Smooths noise) RSI Period: 14 Strong Trend Threshold: 0.08% (Forex has low volatility) Timeframes: 5, 15, 60, 240, 1440

Indicateur Pine Script®

HTF Cross Breakout [CHE] HTF Cross Breakout — Detects higher timeframe close crossovers for breakout signals, anchors VWAP for trend validation, and flags continuations or traps with visual extensions for delta percent and stop levels. Summary This indicator spots moments when the current chart's close price crosses a higher timeframe close, marking potential breakouts only when the current bar shows directional strength. It anchors a volume-weighted average price line from the breakout point to track trend health, updating labels to show if the move continues or reverses into a trap. Extensions add a dotted line linking the breakout level to the current close with percent change display, plus a stop-loss marker at the VWAP end. Signals gain robustness from higher timeframe confirmation and anti-repainting options, reducing noise in live bars compared to simple crossover tools. Motivation: Why this design? Traders often face false breakouts from intrabar wiggles on lower timeframes, especially without higher timeframe alignment, leading to whipsaws in volatile sessions. This design uses higher timeframe close as a stable reference for crossover detection, combined with anchored volume weighting to gauge sustained momentum. It addresses these by enforcing bar confirmation and directional filters, providing clearer entry validation and risk points without overcomplicating the chart. What’s different vs. standard approaches? Reference baseline Standard crossover indicators like moving average crosses operate solely on the chart timeframe, ignoring higher timeframe context and lacking volume anchoring. Architecture differences - Higher timeframe data pulls via security calls with optional repainting control for stability. - Anchored VWAP resets at each signal, accumulating from the breakout bar only. - Label dynamics update in real-time for continuation checks, with extensions for visual delta and stop computation. - Event-driven line finalization prunes old elements after a set bar extension. Practical effect Charts show persistent lines and labels that extend live but finalize cleanly on new events, avoiding clutter. This matters for spotting trap reversals early via label color shifts, and extensions provide quick risk visuals without manual calculations, improving decision speed in trend trades. How it works (technical) The indicator first determines a higher timeframe based on user selection, pulling its close price securely. It checks for crossovers or crossunders of the current close against this higher close, but only triggers on confirmed bars with matching directional opens and closes. On a valid event, a horizontal line and label mark the higher close level, while a dashed VWAP line starts accumulating typical price times volume from that bar onward. During the active phase, the breakout line extends to the current bar, the label repositions and updates text based on whether the current close holds above or below the level for bulls or bears. A background tint warns if the close deviates adversely from the current VWAP. Extensions draw a vertical dotted line at the last bar between the breakout level and close, placing a midpoint label with percent difference; separately, a label at the VWAP end shows a computed stop price. Persistent variables track the active state and accumulators, resetting on new events after briefly extending old elements. Repaint risk from security calls is mitigated by confirmed bar gating or user opt-in. Parameter Guide Plateau Length (reserved for future, currently unused): Sets a length for potential plateau detection in extensions; default 3, minimum 1. Higher values would increase stability but are not active yet—leave at default to avoid tuning. Line Width: Controls thickness of breakout, VWAP, and extension lines; default 2, range 1 to 5. Thicker lines improve visibility on busy charts but may obscure price action—use 1 for clean views, 3 or more for emphasis. +Bars after next HTF event (finalize old, then delete): Extends old lines and labels by this many bars before deletion on new signals; default 20, minimum 0. Shorter extensions keep charts tidy but risk cutting visuals prematurely; longer aids review but builds clutter over time. Evaluate label only on HTF close (prevents gray traps intrabar): When true, label updates wait for higher timeframe confirmation; default true. Enabling reduces intrabar flips for stabler signals, though it may delay feedback—disable for faster live trading at repaint cost. Allow Repainting: Permits real-time security data without confirmation offset; default false. False ensures historical accuracy but lags live bars; true speeds updates but can repaint on HTF closes. Timeframe Type: Chooses HTF method—Auto Timeframe (dynamic steps up), Multiplier (chart multiple), or Manual (fixed string); default Auto Timeframe. Auto adapts to chart scale for convenience; Multiplier suits custom scaling like 5 times current; Manual for precise like 1D on any chart. Multiplier for Alternate Resolution: Scales chart timeframe when Multiplier type selected; default 5, minimum 1. Values near 1 mimic current resolution for subtle shifts; higher like 10 jumps to broader context, increasing signal rarity. Manual Resolution: Direct timeframe string like 60 for 1H when Manual type; default 60. Match to trading horizon—shorter for swing, longer for positional—to balance frequency and reliability. Show Extension 1: Toggles dotted line and delta percent label between breakout level and current close; default true. Disable to simplify for basic use, enable for precise momentum tracking. Dotted Line Width: Thickness for Extension 1 line; default 2, range 1 to 5. Align with main Line Width for consistency. Text Size: Size for delta percent label; options tiny, small, normal, large; default normal. Smaller reduces overlap on dense charts; larger aids glance reads. Decimals for Δ%: Precision in percent change display; default 2, range 0 to 6. Fewer decimals speed reading; more suit low-volatility assets. Positive Δ Color: Hue for upward percent changes; default lime. Choose contrasting for visibility. Negative Δ Color: Hue for downward percent changes; default red. Pair with positive for quick polarity scan. Dotted Line Color: Color for Extension 1 line; default gray. Neutral tones blend well; brighter for emphasis. Background Transparency (0..100): Opacity for delta label background; default 90. Higher values fade for subtlety; lower solidifies for readability. Show Extension 2: Toggles stop-loss label at VWAP end; default true. Turn off for entry focus only. Stop Method: Percent from VWAP end or fixed ticks; options Percent, Ticks; default Percent. Percent scales with price levels; Ticks suits tick-based instruments. Stop %: Distance as fraction of VWAP for Percent method; default 1.0, step 0.05, minimum 0.0. Tighter like 0.5 reduces risk but increases stops; wider like 2.0 allows breathing room. Stop Ticks: Tick count offset for Ticks method; default 20, minimum 0. Adjust per asset volatility—fewer for tight control. Price Decimals: Rounding for stop price text; default 4, range 0 to 10. Match syminfo.precision for clean display. Text Size: Size for stop label; options tiny, small, normal, large; default normal. Scale to chart zoom. Text Color: Foreground for stop text; default white. Ensure contrast with background. Inherit VWAP Color (BG tint): Bases stop label background on VWAP hue; default true. True maintains theme; false allows custom black base. BG Transparency (0..100): Opacity for stop label background; default 0. Zero for no tint; up to 100 for full fade. Reading & Interpretation Breakout lines appear green for bullish crosses or red for bearish, extending live until a new event finalizes them briefly then deletes. Labels start blank, updating to Bull Cont. or Bear Cont. in matching colors if holding the level, or gray Bull Trap/Bear Trap on reversal. VWAP dashes yellow for bulls, orange for bears, sloping with accumulated volume weight—deviations trigger faint red background warnings. Extension 1's dotted vertical shows at the last bar, with midpoint label green/red for positive/negative percent from breakout to close. Extension 2 places a left-aligned label at VWAP end with stop price and method note, tinted to VWAP for context. Practical Workflows & Combinations For trend following, enter long on green Bull Cont. labels above VWAP with higher highs confirmation, filtering via rising structure; short on red Bear Cont. below. Pair with volume surges or RSI above 50 for bulls to avoid traps. For exits, trail stops using the Extension 2 level, tightening on warnings or gray labels—aggressive on continuations, conservative post-trap. In multi-timeframe setups, use default Auto on 15m charts for 1H signals, scaling multiplier to 4 for daily context on hourly; test on forex/stocks where volume is reliable, avoiding low-liquidity assets. Behavior, Constraints & Performance Signals confirm on bar close with HTF gating when strict mode active, but live bars may update if repainting enabled—opt false for backtest fidelity, true for intraday speed. Security calls risk minor repaints on HTF closes, mitigated by confirmation offsets. Resources cap at 1000 bars back, 50 lines/labels total, with event prunes to stay under budgets—no loops, minimal arrays. Limits include VWAP lag in low-volume periods and dependency on accurate HTF data; gaps or holidays may skew anchors. Sensible Defaults & Quick Tuning Defaults suit 5m-1H charts on liquid assets: Auto HTF, no repaint, 1% stops. For choppy markets with excess signals, enable strict eval and bump multiplier to 10 for rarer triggers. If sluggish in trends, shorten extend bars to 10 and allow repainting for quicker visuals. On high-vol like crypto, widen stop % to 2.0 and use Ticks method; for stables like indices, tighten to 0.5% and keep Percent. What this indicator is—and isn’t This is a signal visualization layer for breakout confirmation and basic risk marking, best as a filter in discretionary setups. It isn’t a standalone system or predictive oracle—combine with price structure, news awareness, and sizing rules for real edges. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino

Indicateur Pine Script®

Mis à jour

FVG Scanner Pro FVG Scanner Pro — Smart Fair Value Gap Detector (with HTF context & proximity alerts) What it does FVG Scanner Pro automatically finds Fair Value Gaps (FVGs) on your current chart and (optionally) on a higher timeframe (HTF), draws them as color-coded zones, and notifies you when price comes close to a gap boundary using an ADR-based proximity trigger and (optional) volume confirmation. It’s designed for ICT-style gap trading, confluence building, and clean visual execution. How it works: FVG definition * Bullish FVG (gap up): low > high (the current candle’s low is above the high 2 bars ago). * Bearish FVG (gap down): high < low (the current candle’s high is below the low 2 bars ago). * Gaps smaller than your Min FVG Size (%) are ignored. (Gap size = (top-bottom)/bottom * 100.) Higher-timeframe logic (auto-selected) The script auto picks a sensible HTF: 1–5m → 15m, 15m → 1H, 1H → 4H, 4H → 1D, 1D → 1W, 1W → 1M, small 1M → 3M, big ≥3M → 12M. You can display HTF FVGs and even filter so current-TF FVGs only show when they overlap an HTF gap. Proximity alerts (ADR-based) The script computes ADR on the current chart timeframe over a user-set lookback (default 20 bars). An alert fires when price moves toward the closest actionable boundary and comes within ADR × Multiplier: Bullish: price moving down, within distance of the bottom of a bullish FVG. Bearish: price moving up, within distance of the top of a bearish FVG. Yellow ▲/▼ markers show where a proximity alert triggered. Volume filter (optional) Require volume to be greater than SMA(20) × multiplier to accept a newly formed FVG. Lifecycle Each gap remains active for Extend FVG Box (Bars) bars. You can delete the box after fill, or keep filled gaps visible as gray zones, or hide them. Color legend Current-TF Bullish: Pink/Magenta box Current-TF Bearish: Cyan/Turquoise box HTF Bullish: Gold box HTF Bearish: Orange box Filled (if shown): Gray box Alert markers: Yellow ▲ (bullish), Yellow ▼ (bearish) Inputs (what to tweak) Show FVGs: Bullish / Bearish / Both Max Bars Back to Find FVG: collection window & cleanup guard Extend FVG Box (Bars): how long a zone stays tradable/active Min FVG Size (%): ignore micro gaps Delete Box After Fill & Show Filled FVGs: choose how you want completed gaps handled Show Alert Markers: show/hide the yellow proximity arrows Show Higher Timeframe FVG: overlay HTF gaps (auto TF) HTF Filter: only display current-TF gaps that overlap an HTF gap ADR Lookback & Proximity Multiplier: tune alert sensitivity to your market & timeframe Volume Filter & Volume > MA Multiple: require above-average volume for new gaps Built-in alerts (ready to use) Create alerts in TradingView (⚠️ “Once per bar” or “Once per bar close”, your choice) and select from: 🟢 Bullish FVG Proximity — price approaching a bullish gap bottom 🔴 Bearish FVG Proximity — price approaching a bearish gap top ✅ New Bullish FVG Formed ⚠️ New Bearish FVG Formed The alert messages include the symbol and price; proximity markers are also plotted on chart. Tips & best practices Use FVGs with market structure (break of structure, swing points), order blocks, or liquidity pools for confluence. On very low timeframes, raise Min FVG Size and/or lower Max Bars Back to reduce noise and keep things fast. Extend FVG Box controls how long a zone is considered valid; align it with your holding horizon (scalp vs swing). Information panel (top-right) Shows your mode, current HTF, number of gaps in memory, active bull/bear counts, and current-TF ADR.

Indicateur Pine Script®

Liquidity Triggers Key Points Liquidity Triggers indicate: Where liquidity-derived support levels are. Where liquidity-derived resistance levels are. When a large price increase is approaching via the Rip Currents . - When a large price decrease is approaching via the Dip Currents . Summary Liquidity Triggers are produced by measuring liquidity and determining where supportive liquidity and resistance-liquidity are. These trigger-levels designate price-points where breakouts, breakthroughs, and bounces are anticipated. Liquidity Triggers are dynamic, and they constantly re-evaluate liquidity conditions to determine where the next group of sellers or buyers are that can fuel rapid changes in price movement, such as initiating a trend change or stalling price-action completely. To use, simply apply to your chart and monitor for Supportive Liquidity Triggers (LTs that are below price) for bounces, and Resistance Liquidity Triggers (LTs that are above price) for rejections. You can also set Alerts designed specifically around the Liquidity Triggers. Examples Example 1: A quick look at LT Resistances and Supports. When a LT is above spot, then it is considered a resistance. When LT is below spot, it is considered a support. Example 2: LTs can indicate to us when an upcoming Rip Current (large price appreciation) or a Dip Current (large price depreciation) is starting. Here is an example of a Rip Current: And here is a Dip Current: Details Liquidity Triggers come with a default load-out that utilizes several pre-configured settings for quick and easy start-up. Triggers The default triggers are labeled LT-1 through LT-7, these correspond ` orders ` that describe which type of liquidity is monitored. The two groups of traders that are monitored are the ` Eager ` and the ` Organic `. The default triggers use the Fibonacci sequence to adjust their orders in a standardized way. Triggers 1, 2, 3, and 4 monitor the ` Eager ` traders (with default settings) while triggers 5, 6, and 7 monitor the ` Organic `traders. Eager Triggers represent profit-takers and dip-buyers . When the Eager Triggers are above the price, they are ` selling the rip `, and when the Eager Triggers are below price, they are ` buying the dip `. These moments indicate growing pressure for a reversal. Eager triggers are any trigger with an order of 89 or less . Organic Triggers represent value-seekers with long-term goals. When they are below price, they are areas of support and tend to fuel bounces, while when organic triggers that are above price are areas of resistance and often provoke rejections. Organic triggers are any trigger with an order of 90 or more . Here's an example showing the faint eager liquidity triggers above spot, indicating profit-taking and below spot after a price-dip indicating dip-buying . Customization There are additional settings and configurations available to the Liquidity Triggers indicator that help customize your view of liquidity. Smoothing Smoothing can be applied to the triggers for a more peaceful showing. The smoothing options are: None - Default. Exponential-Moving Average (EMA) : Ideal for when you want the most recent activity to take higher priority. Simple-Moving Average (SMA) : Ideal for when you want a smoother appearance but do not want to change the data too much. Weighted-Moving Average (WMA): Ideal for when you want the smoothing to increase as the trigger order increases. Modified-Moving Average (RMA): Produces the most smooth data. Here is an example of how smoothing can change the appearance of LTs for easier analysis for when things get complicated: Modifying the Default Load-out The default loadout attempts to balance having a wide view of the data without bringing too many lines or values into the picture that might be too noisy, but these values can be added to customize and expand your view if desired. The Fib load-out has the options with t he default load-out being . Feel free to mix and match and explore which views you prefer when analyzing liquidity. For example, for the extreme data-heads, you can add LDPM twice on the chart to get all of the orders displayed at once: Liquidity Triggers - Granular Triggers The granular trigger can be toggled on (default: off) for when candle-specific liquidity measurements desired. They can help identify which specific candles have eager and aggressive traders attempting to move spot: the further away the granular trigger is from the candle, the more force is being applied! Manual LTs If you’re not satisfied with the default options for triggers, you can set your own with the Manual Liquidity Triggers option. Time-Based LTs Time-based liquidity triggers give you a view of support and resistance triggers based off of the time chosen, rather than by an order. This allows you to construct “weekly Liquidity-Triggers” or “hourly Liquidity Triggers” to analyze and compare against. Note: If the timeframes are too far apart, you might get an error. For instance, putting a 1-week reference LT onto a 30-second chart may not work. Liquidity-Triggers Data-Table With the `Display Liquidity Trigger Statuses and Values` option, you can place a data-table on the chart that will display the time-based triggers, their values, and if they are above (bearish) or below (bullish) spot. Alerts When you set alerts, you can determine which order is used for determining `Is bullish`, `Is Bearish`, `Has Become Bullish`, `Has Become Bearish` alerts in the LT Alert Order setting. Several LT alerts are available to set: Is Bullish / Bearish: these are designed to analyze conditions at the end of the candle and if spot is above the alert-trigger, then an alert is sent out that conditions are bullish, and if spot is below the alert-trigger, then an alert is sent out if conditions are bearish. Has Become Bullish / Bearish: designed to analyze conditions at the start of a candle and determine if a change has occurred (a LT cross-over). Suspected Rip Current: these are designed to alert you when a suspected upwards rip in price is underway, as characterized by all LT triggers moving rapidly down away from spot. Suspected Dip Current: these are designed to alert you when a suspected downwards rip in price is underway, as characterized by all LT triggers moving rapidly up and above, away from spot. These alerts can then be put into a webhook for external processing if desired. Frequently Asked Questions How can I gain access to LT? Check out the Author's Instructions section below. Where can I get more information? Check out the Author's Instructions section below for how to obtain more information. I tried to add LT to my chart but it produced an error. Sometimes this happens but no worries. Just change the chart's interval to a different time and then back, the indicator should re-load. If that fails, try removing it completely and re-applying it. Is it normal for LTs to have different values on different timeframes? Yup! Think of each time-interval as a different "zoom" of the market. Imagine you are taking a picture of the ocean to figure out the direction of water movement. If you take the picture from space, you will see big general trends but if you take the photo from your boat in the harbor, you're going to get specific data about that area. That's how LT works! The view of the liquidity depends on the "zoom-age" (the chart's interval) used when taking the photo. I think there is an issue with the alerts - what should I do? This is not ideal! If this happens, please reach out via the contact information in the Author's Instructions section below with the following details: What symbol? What timeframe? Which alert? When did the alert occur? Can I attach the alerts to webhooks? Yup! Be sure to check out TV's guide on webhooks ( T.V. Guide to Alerts ) for how to get started. Does LT receive updates? Yup! If a bug or issue is found, an update is pushed out. You will be notified when this occurs and it is highly recommended that you replace all charts with LT on them with the new version as the updates go out.

Indicateur Pine Script®

par DeepDiveStocks

Gabriel's Triple Impulsive Candle Detector Triple Impulsive Candle Detector Overview, critical for catching impulse moves in either direction. SPX Income System is a rule-based framework designed to identify frequent, high-probability income opportunities on the S&P 500 cash index (SPX/SPY) using 0-DTE credit spreads. The core engine operates on 30-minute Impulse bars during the morning trade window and can be extended with optional modules for afternoon, overnight, and weekly swing opportunities. The methodology centers on a single, mechanical price event called a Impulse Bar (small wick to body ratio) to minimize discretion and keep execution consistent. 🔶What’s Inside Core Strategy: SPX Daily Income Timeframe: 3 kinds of 30-min bars. Window: 09:30–11:30 ET (new setups only) Instrument: SPX (cash index, XSP/SPY), executed with $5-wide credit spreads on 0-DTE SPX options Bullish Setup Entry on the break of setup bar high Use an at the money put credit spread Bearish Setup Entry on the break of setup bar low Use an at the money call credit spread Intent: Enter shortly after setup; manage to >80% max profit or EOD expiration if SPX. If it's another stock, then a 1.5~2x D ATR is suggested. Signal: An Impulse Bar that closes at/near the high (bullish) or low (bearish) of its 30-min range, verified with Volume above average. Risk—limited to the risk of the option spread. The spread is 5 dollars wide The premium collected is $2.50 $5 - 2.50 = $2.50, or the breakeven point. Which means what's left is the risk involved. The risk is $2.50 per spread 🔶Why the 30-Minute Chart? The 30-minute bar is the “chart of choice” because it filters noise and aligns with morning institutional flows. On alternate timeframes, price often retraces half the candle body before following through. On the 30m: the follow-through is more consistent, especially with 2x volume confirmation. Adding support/resistance levels at the impulse bar hl2 strengthens execution. This strategy has roots in MTF Crypto, and SPX/SPY TPO-Order Block logic. 🔶Bonus Examples: 🔹Afternoon SPX Income Second chance window (typically 14:00–15:00 ET) if the morning trade has exited, 60-min bars instead. 🔹ORB 30 – Opening Range Break (first 30 min) Classic ORB with an income twist for early action when time is limited. This can be entered on the 15 minute candle break. 🔹ORB 60 – Opening Range Break (second 30 min) A follow-up ORB variant for traders who miss the first window, verified on a 60-min chart. Enter on the final 3 minutes of the hourly candle or wait for a pullback. 🔹B&B – Bed & Breakfast (Overnight) Identifies income setups via the 10-minute chart in the last 30–60 minutes of the session with next-day open as the exit. 🔹JB – Just Breakfast Uses the prior day’s end-of-day setup to enter at the opening bell, then manages into the daily income flow. I trade 0-date, and selling an ITM spread either partially or fully then gives me a head start on the daily income potential. This may work better if you either roll or the ORB 30 also meets the criteria. 🔹All-Day-Scalper Converts income logic into 30-minute scalps using deep 75/80 delta ITM options as synthetic stock (requires >PDT). Meaning that the option will behave as if it is stock. This strategy comes with a warning: it's better if you can day trade. 🔹Tag ’n Turn—Weekly SPX Income Swing Weekly swing overlay using 30-min Pulse Bars + Bollinger Bands (50) for 3–7 day swings and as a filter for daily income alignment. I use the TTM Squeeze and obtain similar results. Target heuristics (directional days) with a fired squeeze. Part of my Gamma Scalping System. 🔶The Impulse Bar (10~40% Wick to Body Bar) An Impulse Bar is a candle that: Bullish: Closes higher than it opens and within the top ~10% of its high-low range. Bearish: Closes lower than it opens and within the bottom ~10% of its high-low range. Practical tip: Many traders mark 0-10-80-100% levels on the candle range (custom Fib or ruler) to quickly validate Pulse Bars. If it's accompanied by a volume spike, then it's better quality. 🔶SPX Daily Income—Rules & Execution 🔹Rules Chart: 30 min, no indicators required. Pure PA, TPO-based strategy. New Setups: 09:30–11:30 ET Instrument: SPX signals, executed via SPX 0-DTE credit spreads ($5 wide, $2 for SPY) 🔹Entries Bullish: Enter on a break of the setup bar high, use ATM put credit spread Bearish: Enter on a break of the setup bar low, use ATM call credit spread 🔹Exits Primary: Close at >80% of max profit (credit received) Alternate: Hold to EOD expiration Stop: Risk of the spread (defined by width – credit) Target Heuristics (directional days) Optional: 1.5–2× ATR as a reference (mirrors directional follow-through that often accelerates the >80% outcome) Credit Guidance (typical) OTM short strike ≈ $2.40 ITM short strike ≈ $2.50–$2.80 2× ITM short strike ≈ $2.80–$3.00 Trade Management (PDT-Aware) If under PDT, many prefer set-and-forget with GTC buy-back (e.g., $0.20) or EOD expiration. 1:00 PM ET time check Trending day ±$15–$20 SPX: usually no action, run to expiration Non-trending day ±$5 SPX: consider taking 40–60% if available (optional) to avoid 50/50 end-of-day decay dynamics Rationale: Without a favorable trend by ~1 PM, the odds of a late push decline; choosing a controlled partial outcome can improve long-run expectancy and reduce variance. 🔶Examples (Conceptual) 🔹Bullish: A green dot marks a bullish impulse bar; minor follow-through pushes the spread to >80% quickly. 🔹Bearish: A red triangle marks a bearish Impulse Bar; a modest down move is often sufficient for >80–95%. 🔹Tag ’n Turn—Weekly Swing (Filter & Stand-Alone) Chart: 30-minute Overlay: Bollinger Bands 50 (mean-reversion lens), or KC or TTM. Setup: Tag of upper/lower band + Pulse Bar, enter on break of Pulse Bar in that direction Target: Opposite Bollinger Band Use Case: 3–7 day swings and a directional filter for Daily Income signals (trade with weekly bias) 🔹Afternoon SPX Income: Same Pulse logic, 14:00–15:00 ET window. 🔹ORB 30 / ORB 60: Uses 30/60-min opening range; can relax Pulse threshold (up to 40% bars) for early positioning when time-constrained. 🔹B&B (Overnight): Lasts 30–60 minutes; closes the next day at open or after the first 30-minute bar. 🔹JB (Just Breakfast): Enter at open using prior day’s signal; optionally roll into Daily Income if eligible. 🔹All-Day-Scalper: Deep ITM options (~0.75–0.80 delta) as synthetic stock. Entry: Long ITM option Stop: ~40% of option price Target: 70–150% or 30-minute timed exit Note: Time-intensive; for accounts above PDT. 🔹Brokerage: Must efficiently support SPX options; a <10% spread between OI and Volume is ideal. Preferences vary; Tastytrade, Thinkorswim, and Interactive Brokers are common choices. Use what’s reliable, available in your region, and cost-effective. 🔶Alerts (Check-in) Bullish Impulse Detected (within 09:30–11:30 ET) Bearish Impulse Detected (within 09:30–11:30 ET) Afternoon Pulse (14:00–15:00 ET) ORB 30/60 Trigger B&B Window Open (last 60 mins) JB at Open Tag ’n Turn: Band Tag + Impulse (Bull/Bear) 🔶Inputs (Typical) Session windows (morning, afternoon, last hour) ~5~15 Average Bar Impulse threshold (strict 10% vs relaxed up to 40% for ORB variants) Marker/label styles (bull/bear colors, dots vs arrows) Filters (optional ATR TP, band touch BB(50-SMA, 2 Stdv.) for Tag ’n Turn) Alert toggles (on-close for webhooks) 🔶Best Practices One playbook, many Doors: Start with daily income; add afternoon or B&B/JB only after you’re consistent. Credit discipline: Don’t chase poor pricing; stick to the credit guidance. Time awareness: If no trend by ~1 PM ET, consider variance control. Weekly bias: When using Tag ’n Turn, align daily trades with the weekly swing direction for added confluence. Risk is defined as width – credit = max risk per spread. Size, accordingly, 1~2%. 🔶Disclosures & Risk This is not financial advice. Options involve risk and are not suitable for all investors. Past performance (including backtests or theoretical studies) does not guarantee future results. Slippage, fills, assignment risk, and latency can materially impact outcomes. Trade a plan you fully understand and always size for durability. On the Daily, the Impulse bars, are often a signal that you should plan for it to return back to half of the Candle's body, and plan accordingly. Plot a horizontal support/resistance level and see how price reacts to it. Keep house-money, and use 1~2% Risk, reduce exposure when VIX is low and increase it when VIX is high. TL;DR (Summary) Signal: 30-min Pulse Bar (strict 10% close in range) Window: 09:30–11:30 ET (new setups) Execution: 0-DTE $5-wide SPX credit spreads Exit: >80% max profit or EOD Add-ons: Afternoon, ORB 30/60, B&B/JB overnights, All-Day-Scalper, Tag ’n Turn weekly swing/filter Philosophy: Fully rule-based, minimal discretion, production-line consistency 0-date.

Indicateur Pine Script®

par GabrielAmadeusLau

RSI Divergence + Hidden RSI Divergence + Hidden (TV-like pairing, final) What it does This indicator plots RSI and automatically detects both regular and hidden divergences by pairing RSI pivots with price pivots. It supports a TradingView-like loose pairing (within a user-defined bar tolerance) and a strict same-bar pairing. Detected signals are drawn with lines and optional labels on the RSI pane for quick visual verification. Divergence logic Regular Bullish (label: Bull) Price makes a lower low while RSI makes a higher low → potential upward reversal. Regular Bearish (label: Bear) Price makes a higher high while RSI makes a lower high → potential downward reversal. Hidden Bullish (label: H_Bull) Price makes a higher low while RSI makes a lower low → trend-continuation bias upward. Hidden Bearish (label: H_Bear) Price makes a lower high while RSI makes a higher high → trend-continuation bias downward. All conditions use pivot-to-pivot comparisons with optional equality tolerance for price and RSI to reduce false “equal” mismatches. Pairing modes TV-like Pairs the latest price and RSI pivots if their pivot bars occur within ±tolBars. A lightweight “pending” buffer allows pairing a newly detected pivot with a recent opposite pivot that arrived a few bars earlier/later (within tolerance). Same Bar Price and RSI pivots must occur on the exact same bar to form a pair. Key inputs RSI Source & Length: srcRsi, rsiLen (default 14). RSI line and reference levels (70/50/30) can be shown/hidden. Pivot Window: leftBars, rightBars for both price and RSI pivots. Pairing: pairMode = TV-like or Same Bar; tolBars for bar tolerance (TV-like only). Price Pivot Basis: priceMode = High/Low (default) or Close. Equality Tolerance: allowEqual (use >=/<=), priceEpsTks (ticks) for price equality slack, rsiEps (points) for RSI equality slack. Visibility: showRSI, showRegular, showHidden, showLabels. Visuals Lines (on RSI): Regular Bearish: red Regular Bullish: lime Hidden Bearish: orange Hidden Bullish: teal Labels (optional): "Bear", "Bull", "H_Bear", "H_Bull" placed on the RSI series at the second pivot. Alerts Four alert conditions are provided and fire when the corresponding divergence is confirmed: Bear (Regular) Bull (Regular) H_Bear (Hidden) H_Bull (Hidden) Notes & tips Divergences are evaluated only when both price and RSI pivots exist and can be paired under the selected mode. Pivot sensitivity: smaller leftBars/rightBars → earlier but noisier signals; larger values → fewer, more stable pivots. Tolerance: If you miss valid setups because pivots land a few bars apart, use TV-like with a small tolBars (e.g., 1–2). If you prefer stricter confirmation, use Same Bar. Equality slack: Use priceEpsTks and rsiEps to avoid rejecting near-equal highs/lows due to tiny differences. Works on any symbol/timeframe; as with all divergence tools, treat signals as context—combine with trend, structure, and risk management.

Indicateur Pine Script®

par h.kitano19810517

RSI Bands With RSI - ATR Trend Line RSI Bands With RSI - ATR Trend Line (Smoothed Baseline) Overview A trend-following tool that fuses RSI-based regime detection with a smoothed baseline and ATR bands. Trend line aims to stay with the RSI move, cut random noise, and flip cleanly. The line draws green in bulls and red in bears; signals fire only on candle close confirmed flips. Key Features ✅ Dynamic Trend Detection RSI (>50 / <50) sets bullish/bearish regime Smoothed baseline adapts to price while damping whipsaw ATR-based bands expand/contract with volatility ✅ Precise Signal Generation Buy when trend flips to bullish (close confirms above the upper band) Sell when trend flips to bearish (close confirms below the lower band) Flips require a real band break → fewer false transitions ✅ Visual Clarity Green line = bullish trend, Red line = bearish trend ✅ Customizable Settings RSI Length (default 14) Baseline Smoothing (default 26) ATR Length (default 14) ATR Multiplier (default 1.4) Toggles for Signals and Labels ✅ TradingView Alerts Built-in Buy & Sell alerts (recommend Once per bar close) How It Works Algorithm Logic RSI Regime: RSI above/below 50 sets bull/bear. At exactly 50, the prior target is carried forward. Target & Smoothing: A per-bar target is built from the bar’s range and RSI, then smoothed with an EMA-style filter (Baseline Smoothing) to form the baseline. ATR Bands: Upper/Lower = baseline ± (ATR × Multiplier). Flip Rule (Supertrend-like): Close above upper band → bullish flip; trend line tracks the lower band (green). Close below lower band → bearish flip; trend line tracks the upper band (red). Between bands → prior trend line persists. Signals/Alerts: A flip event generates a Buy/Sell signal and alert. Best Use Cases Trending Markets – Built to ride sustained moves in either direction. Multiple Timeframes – Works from intraday to higher TFs; higher TFs usually produce cleaner flips. Various Asset Classes – Forex, Indices, Stocks, Crypto, Commodities; ATR adapts to volatility. Recommended Settings Conservative (Lower Frequency) RSI 14–20 • Baseline 34 • ATR 14–21 • Multiplier 1.8–2.2 Use for swing/position trading; calmer signal stream. Balanced (Default) RSI 14 • Baseline 26 • ATR 14 • Multiplier 1.4 Good general-purpose setup for swing or active intraday. Aggressive (Higher Frequency) RSI 10–14 • Baseline 13–21 • ATR 10–14 • Multiplier 1.1–1.3 For scalping/day trading; earlier but noisier flips. 🎨 Visual Elements RSI Smooth baseline (soft blue) Upper/Lower ATR Bands (faint blue) Trend Line (Bull/Bear) drawn only in the active regime (green/red) Optional Buy/Sell arrows and labels ⚠️ Important Notes Signals on Close Flips confirm on bar close. Intrabar crosses can revert; wait for confirmation. Risk Management Size positions appropriately; many traders trail beyond the opposite band/line. Factor in spread, slippage, sessions, and news. Confirmation & Testing Combine with structure/volume/HTF bias if desired. Backtest and forward-test per instrument and timeframe. For research/education only; not financial advice.

Indicateur Pine Script®

Dashboard Trends 📊 Dashboard Trends + Anchored Daily VWAP This indicator provides a real-time multi-timeframe trend dashboard alongside a daily anchored VWAP system, helping you assess both macro and intraday market sentiment at a glance. 🔍 Key Features ✅ Multi-Timeframe Trend Analysis Tracks whether EMA(22) is above EMA(200) across: 1m, 10m, 30m, 4h, 1D timeframes Color-coded "Bullish"/"Bearish" status for each Aggregated trend summary using 6 signals (including VWAP) ✅ Anchored Daily VWAP Uses ta.vwap to provide a session-resetting daily VWAP VWAP resets at the beginning of each trading day Live update throughout the day Supports pre-market and after-hours if chart includes ETH ✅ VWAP Bands (±1σ to ±3σ) Optional bands show price deviation from VWAP Fully customizable: Enable/disable each band Set deviation multiplier Adjust color and visibility ✅ Visual Dashboard Table display in the bottom-right corner Shows trend status per timeframe + VWAP + Summary Easy-to-read green/yellow/red color codes ⚙️ Customization Toggle VWAP line on/off Enable or disable any band level Adjust standard deviation multiplier Choose your VWAP and band colors 🧠 Summary Logic Strong Bull: 6 bullish signals Bull: 5 signals Mixed: 3–4 signals Bear: 2 signals Strong Bear: 0–1 signals This tool is perfect for traders looking to combine trend-following and intraday mean-reversion awareness, with all the critical data visualized in one compact dashboard.

Indicateur Pine Script®

Trend Gauge [BullByte]Trend Gauge Summary A multi-factor trend detection indicator that aggregates EMA alignment, VWMA momentum scaling, volume spikes, ATR breakout strength, higher-timeframe confirmation, ADX-based regime filtering, and RSI pivot-divergence penalty into one normalized trend score. It also provides a confidence meter, a Δ Score momentum histogram, divergence highlights, and a compact, scalable dashboard for at-a-glance status. ________________________________________ ## 1. Purpose of the Indicator Why this was built Traders often monitor several indicators in parallel - EMAs, volume signals, volatility breakouts, higher-timeframe trends, ADX readings, divergence alerts, etc., which can be cumbersome and sometimes contradictory. The “Trend Gauge” indicator was created to consolidate these complementary checks into a single, normalized score that reflects the prevailing market bias (bullish, bearish, or neutral) and its strength. By combining multiple inputs with an adaptive regime filter, scaling contributions by magnitude, and penalizing weakening signals (divergence), this tool aims to reduce noise, highlight genuine trend opportunities, and warn when momentum fades. Key Design Goals Signal Aggregation Merged trend-following signals (EMA crossover, ATR breakout, higher-timeframe confirmation) and momentum signals (VWMA thrust, volume spikes) into a unified score that reflects directional bias more holistically. Market Regime Awareness Implemented an ADX-style filter to distinguish between trending and ranging markets, reducing the influence of trend signals during sideways phases to avoid false breakouts. Magnitude-Based Scaling Replaced binary contributions with scaled inputs: VWMA thrust and ATR breakout are weighted relative to recent averages, allowing for more nuanced score adjustments based on signal strength. Momentum Divergence Penalty Integrated pivot-based RSI divergence detection to slightly reduce the overall score when early signs of momentum weakening are detected, improving risk-awareness in entries. Confidence Transparency Added a live confidence metric that shows what percentage of enabled sub-indicators currently agree with the overall bias, making the scoring system more interpretable. Momentum Acceleration Visualization Plotted the change in score (Δ Score) as a histogram bar-to-bar, highlighting whether momentum is increasing, flattening, or reversing, aiding in more timely decision-making. Compact Informational Dashboard Presented a clean, scalable dashboard that displays each component’s status, the final score, confidence %, detected regime (Trending/Ranging), and a labeled strength gauge for quick visual assessment. ________________________________________ ## 2. Why a Trader Should Use It Main benefits and use cases 1. Unified View: Rather than juggling multiple windows or panels, this indicator delivers a single score synthesizing diverse signals. 2. Regime Filtering: In ranging markets, trend signals often generate false entries. The ADX-based regime filter automatically down-weights trend-following components, helping you avoid chasing false breakouts. 3. Nuanced Momentum & Volatility: VWMA and ATR breakout contributions are normalized by recent averages, so strong moves register strongly while smaller fluctuations are de-emphasized. 4. Early Warning of Weakening: Pivot-based RSI divergence is detected and used to slightly reduce the score when price/momentum diverges, giving a cautionary signal before a full reversal. 5. Confidence Meter: See at a glance how many sub-indicators align with the aggregated bias (e.g., “80% confidence” means 4 out of 5 components agree ). This transparency avoids black-box decisions. 6. Trend Acceleration/Deceleration View: The Δ Score histogram visualizes whether the aggregated score is rising (accelerating trend) or falling (momentum fading), supplementing the main oscillator. 7. Compact Dashboard: A corner table lists each check’s status (“Bull”, “Bear”, “Flat” or “Disabled”), plus overall Score, Confidence %, Regime, Trend Strength label, and a gauge bar. Users can scale text size (Normal, Small, Tiny) without removing elements, so the full picture remains visible even in compact layouts. 8. Customizable & Transparent: All components can be enabled/disabled and parameterized (lengths, thresholds, weights). The full Pine code is open and well-commented, letting users inspect or adapt the logic. 9. Alert-ready: Built-in alert conditions fire when the score crosses weak thresholds to bullish/bearish or returns to neutral, enabling timely notifications. ________________________________________ ## 3. Component Rationale (“Why These Specific Indicators?”) Each sub-component was chosen because it adds complementary information about trend or momentum: 1. EMA Cross o Basic trend measure: compares a faster EMA vs. a slower EMA. Quickly reflects trend shifts but by itself can whipsaw in sideways markets. 2. VWMA Momentum o Volume-weighted moving average change indicates momentum with volume context. By normalizing (dividing by a recent average absolute change), we capture the strength of momentum relative to recent history. This scaling prevents tiny moves from dominating and highlights genuinely strong momentum. 3. Volume Spikes o Sudden jumps in volume combined with price movement often accompany stronger moves or reversals. A binary detection (+1 for bullish spike, -1 for bearish spike) flags high-conviction bars. 4. ATR Breakout o Detects price breaking beyond recent highs/lows by a multiple of ATR. Measures breakout strength by how far beyond the threshold price moves relative to ATR, capped to avoid extreme outliers. This gives a volatility-contextual trend signal. 5. Higher-Timeframe EMA Alignment o Confirms whether the shorter-term trend aligns with a higher timeframe trend. Uses request.security with lookahead_off to avoid future data. When multiple timeframes agree, confidence in direction increases. 6. ADX Regime Filter (Manual Calculation) o Computes directional movement (+DM/–DM), smoothes via RMA, computes DI+ and DI–, then a DX and ADX-like value. If ADX ≥ threshold, market is “Trending” and trend components carry full weight; if ADX < threshold, “Ranging” mode applies a configurable weight multiplier (e.g., 0.5) to trend-based contributions, reducing false signals in sideways conditions. Volume spikes remain binary (optional behavior; can be adjusted if desired). 7. RSI Pivot-Divergence Penalty o Uses ta.pivothigh / ta.pivotlow with a lookback to detect pivot highs/lows on price and corresponding RSI values. When price makes a higher high but RSI makes a lower high (bearish divergence), or price makes a lower low but RSI makes a higher low (bullish divergence), a divergence signal is set. Rather than flipping the trend outright, the indicator subtracts (or adds) a small penalty (configurable) from the aggregated score if it would weaken the current bias. This subtle adjustment warns of weakening momentum without overreacting to noise. 8. Confidence Meter o Counts how many enabled components currently agree in direction with the aggregated score (i.e., component sign × score sign > 0). Displays this as a percentage. A high percentage indicates strong corroboration; a low percentage warns of mixed signals. 9. Δ Score Momentum View o Plots the bar-to-bar change in the aggregated score (delta_score = score - score ) as a histogram. When positive, bars are drawn in green above zero; when negative, bars are drawn in red below zero. This reveals acceleration (rising Δ) or deceleration (falling Δ), supplementing the main oscillator. 10. Dashboard • A table in the indicator pane’s top-right with 11 rows: 1. EMA Cross status 2. VWMA Momentum status 3. Volume Spike status 4. ATR Breakout status 5. Higher-Timeframe Trend status 6. Score (numeric) 7. Confidence % 8. Regime (“Trending” or “Ranging”) 9. Trend Strength label (e.g., “Weak Bullish Trend”, “Strong Bearish Trend”) 10. Gauge bar visually representing score magnitude • All rows always present; size_opt (Normal, Small, Tiny) only changes text size via text_size, not which elements appear. This ensures full transparency. ________________________________________ ## 4. What Makes This Indicator Stand Out • Regime-Weighted Multi-Factor Score: Trend and momentum signals are adaptively weighted by market regime (trending vs. ranging) , reducing false signals. • Magnitude Scaling: VWMA and ATR breakout contributions are normalized by recent average momentum or ATR, giving finer gradation compared to simple ±1. • Integrated Divergence Penalty: Divergence directly adjusts the aggregated score rather than appearing as a separate subplot; this influences alerts and trend labeling in real time. • Confidence Meter: Shows the percentage of sub-signals in agreement, providing transparency and preventing blind trust in a single metric. • Δ Score Histogram Momentum View: A histogram highlights acceleration or deceleration of the aggregated trend score, helping detect shifts early. • Flexible Dashboard: Always-visible component statuses and summary metrics in one place; text size scaling keeps the full picture available in cramped layouts. • Lookahead-Safe HTF Confirmation: Uses lookahead_off so no future data is accessed from higher timeframes, avoiding repaint bias. • Repaint Transparency: Divergence detection uses pivot functions that inherently confirm only after lookback bars; description documents this lag so users understand how and when divergence labels appear. • Open-Source & Educational: Full, well-commented Pine v6 code is provided; users can learn from its structure: manual ADX computation, conditional plotting with series = show ? value : na, efficient use of table.new in barstate.islast, and grouped inputs with tooltips. • Compliance-Conscious: All plots have descriptive titles; inputs use clear names; no unnamed generic “Plot” entries; manual ADX uses RMA; all request.security calls use lookahead_off. Code comments mention repaint behavior and limitations. ________________________________________ ## 5. Recommended Timeframes & Tuning • Any Timeframe: The indicator works on small (e.g., 1m) to large (daily, weekly) timeframes. However: o On very low timeframes (<1m or tick charts), noise may produce frequent whipsaws. Consider increasing smoothing lengths, disabling certain components (e.g., volume spike if volume data noisy), or using a larger pivot lookback for divergence. o On higher timeframes (daily, weekly), consider longer lookbacks for ATR breakout or divergence, and set Higher-Timeframe trend appropriately (e.g., 4H HTF when on 5 Min chart). • Defaults & Experimentation: Default input values are chosen to be balanced for many liquid markets. Users should test with replay or historical analysis on their symbol/timeframe and adjust: o ADX threshold (e.g., 20–30) based on instrument volatility. o VWMA and ATR scaling lengths to match average volatility cycles. o Pivot lookback for divergence: shorter for faster markets, longer for slower ones. • Combining with Other Analysis: Use in conjunction with price action, support/resistance, candlestick patterns, order flow, or other tools as desired. The aggregated score and alerts can guide attention but should not be the sole decision-factor. ________________________________________ ## 6. How Scoring and Logic Works (Step-by-Step) 1. Compute Sub-Scores o EMA Cross: Evaluate fast EMA > slow EMA ? +1 : fast EMA < slow EMA ? -1 : 0. o VWMA Momentum: Calculate vwma = ta.vwma(close, length), then vwma_mom = vwma - vwma . Normalize: divide by recent average absolute momentum (e.g., ta.sma(abs(vwma_mom), lookback)), clip to . o Volume Spike: Compute vol_SMA = ta.sma(volume, len). If volume > vol_SMA * multiplier AND price moved up ≥ threshold%, assign +1; if moved down ≥ threshold%, assign -1; else 0. o ATR Breakout: Determine recent high/low over lookback. If close > high + ATR*mult, compute distance = close - (high + ATR*mult), normalize by ATR, cap at a configured maximum. Assign positive contribution. Similarly for bearish breakout below low. o Higher-Timeframe Trend: Use request.security(..., lookahead=barmerge.lookahead_off) to fetch HTF EMAs; assign +1 or -1 based on alignment. 2. ADX Regime Weighting o Compute manual ADX: directional movements (+DM, –DM), smoothed via RMA, DI+ and DI–, then DX and ADX via RMA. If ADX ≥ threshold, market is considered “Trending”; otherwise “Ranging.” o If trending, trend-based contributions (EMA, VWMA, ATR, HTF) use full weight = 1.0. If ranging, use weight = ranging_weight (e.g., 0.5) to down-weight them. Volume spike stays binary ±1 (optional to change if desired). 3. Aggregate Raw Score o Sum weighted contributions of all enabled components. Count the number of enabled components; if zero, default count = 1 to avoid division by zero. 4. Divergence Penalty o Detect pivot highs/lows on price and corresponding RSI values, using a lookback. When price and RSI diverge (bearish or bullish divergence), check if current raw score is in the opposing direction:  If bearish divergence (price higher high, RSI lower high) and raw score currently positive, subtract a penalty (e.g., 0.5).  If bullish divergence (price lower low, RSI higher low) and raw score currently negative, add a penalty. o This reduces score magnitude to reflect weakening momentum, without flipping the trend outright. 5. Normalize and Smooth o Normalized score = (raw_score / number_of_enabled_components) * 100. This yields a roughly range. o Optional EMA smoothing of this normalized score to reduce noise. 6. Interpretation o Sign: >0 = net bullish bias; <0 = net bearish bias; near zero = neutral. o Magnitude Zones: Compare |score| to thresholds (Weak, Medium, Strong) to label trend strength (e.g., “Weak Bullish Trend”, “Medium Bearish Trend”, “Strong Bullish Trend”). o Δ Score Histogram: The histogram bars from zero show change from previous bar’s score; positive bars indicate acceleration, negative bars indicate deceleration. o Confidence: Percentage of sub-indicators aligned with the score’s sign. o Regime: Indicates whether trend-based signals are fully weighted or down-weighted. ________________________________________ ## 7. Oscillator Plot & Visualization: How to Read It Main Score Line & Area The oscillator plots the aggregated score as a line, with colored fill: green above zero for bullish area, red below zero for bearish area. Horizontal reference lines at ±Weak, ±Medium, and ±Strong thresholds mark zones: crossing above +Weak suggests beginning of bullish bias, above +Medium for moderate strength, above +Strong for strong trend; similarly for bearish below negative thresholds. Δ Score Histogram If enabled, a histogram shows score - score . When positive, bars appear in green above zero, indicating accelerating bullish momentum; when negative, bars appear in red below zero, indicating decelerating or reversing momentum. The height of each bar reflects the magnitude of change in the aggregated score from the prior bar. Divergence Highlight Fill If enabled, when a pivot-based divergence is confirmed: • Bullish Divergence : fill the area below zero down to –Weak threshold in green, signaling potential reversal from bearish to bullish. • Bearish Divergence : fill the area above zero up to +Weak threshold in red, signaling potential reversal from bullish to bearish. These fills appear with a lag equal to pivot lookback (the number of bars needed to confirm the pivot). They do not repaint after confirmation, but users must understand this lag. Trend Direction Label When score crosses above or below the Weak threshold, a small label appears near the score line reading “Bullish” or “Bearish.” If the score returns within ±Weak, the label “Neutral” appears. This helps quickly identify shifts at the moment they occur. Dashboard Panel In the indicator pane’s top-right, a table shows: 1. EMA Cross status: “Bull”, “Bear”, “Flat”, or “Disabled” 2. VWMA Momentum status: similarly 3. Volume Spike status: “Bull”, “Bear”, “No”, or “Disabled” 4. ATR Breakout status: “Bull”, “Bear”, “No”, or “Disabled” 5. Higher-Timeframe Trend status: “Bull”, “Bear”, “Flat”, or “Disabled” 6. Score: numeric value (rounded) 7. Confidence: e.g., “80%” (colored: green for high, amber for medium, red for low) 8. Regime: “Trending” or “Ranging” (colored accordingly) 9. Trend Strength: textual label based on magnitude (e.g., “Medium Bullish Trend”) 10. Gauge: a bar of blocks representing |score|/100 All rows remain visible at all times; changing Dashboard Size only scales text size (Normal, Small, Tiny). ________________________________________ ## 8. Example Usage (Illustrative Scenario) Example: BTCUSD 5 Min 1. Setup: Add “Trend Gauge ” to your BTCUSD 5 Min chart. Defaults: EMAs (8/21), VWMA 14 with lookback 3, volume spike settings, ATR breakout 14/5, HTF = 5m (or adjust to 4H if preferred), ADX threshold 25, ranging weight 0.5, divergence RSI length 14 pivot lookback 5, penalty 0.5, smoothing length 3, thresholds Weak=20, Medium=50, Strong=80. Dashboard Size = Small. 2. Trend Onset: At some point, price breaks above recent high by ATR multiple, volume spikes upward, faster EMA crosses above slower EMA, HTF EMA also bullish, and ADX (manual) ≥ threshold → aggregated score rises above +20 (Weak threshold) into +Medium zone. Dashboard shows “Bull” for EMA, VWMA, Vol Spike, ATR, HTF; Score ~+60–+70; Confidence ~100%; Regime “Trending”; Trend Strength “Medium Bullish Trend”; Gauge ~6–7 blocks. Δ Score histogram bars are green and rising, indicating accelerating bullish momentum. Trader notes the alignment. 3. Divergence Warning: Later, price makes a slightly higher high but RSI fails to confirm (lower RSI high). Pivot lookback completes; the indicator highlights a bearish divergence fill above zero and subtracts a small penalty from the score, causing score to stall or retrace slightly. Dashboard still bullish but score dips toward +Weak. This warns the trader to tighten stops or take partial profits. 4. Trend Weakens: Score eventually crosses below +Weak back into neutral; a “Neutral” label appears, and a “Neutral Trend” alert fires if enabled. Trader exits or avoids new long entries. If score subsequently crosses below –Weak, a “Bearish” label and alert occur. 5. Customization: If the trader finds VWMA noise too frequent on this instrument, they may disable VWMA or increase lookback. If ATR breakouts are too rare, adjust ATR length or multiplier. If ADX threshold seems off, tune threshold. All these adjustments are explained in Inputs section. 6. Visualization: The screenshot shows the main score oscillator with colored areas, reference lines at ±20/50/80, Δ Score histogram bars below/above zero, divergence fill highlighting potential reversal, and the dashboard table in the top-right. ________________________________________ ## 9. Inputs Explanation A concise yet clear summary of inputs helps users understand and adjust: 1. General Settings • Theme (Dark/Light): Choose background-appropriate colors for the indicator pane. • Dashboard Size (Normal/Small/Tiny): Scales text size only; all dashboard elements remain visible. 2. Indicator Settings • Enable EMA Cross: Toggle on/off basic EMA alignment check. o Fast EMA Length and Slow EMA Length: Periods for EMAs. • Enable VWMA Momentum: Toggle VWMA momentum check. o VWMA Length: Period for VWMA. o VWMA Momentum Lookback: Bars to compare VWMA to measure momentum. • Enable Volume Spike: Toggle volume spike detection. o Volume SMA Length: Period to compute average volume. o Volume Spike Multiplier: How many times above average volume qualifies as spike. o Min Price Move (%): Minimum percent change in price during spike to qualify as bullish or bearish. • Enable ATR Breakout: Toggle ATR breakout detection. o ATR Length: Period for ATR. o Breakout Lookback: Bars to look back for recent highs/lows. o ATR Multiplier: Multiplier for breakout threshold. • Enable Higher Timeframe Trend: Toggle HTF EMA alignment. o Higher Timeframe: E.g., “5” for 5-minute when on 1-minute chart, or “60” for 5 Min when on 15m, etc. Uses lookahead_off. • Enable ADX Regime Filter: Toggles regime-based weighting. o ADX Length: Period for manual ADX calculation. o ADX Threshold: Value above which market considered trending. o Ranging Weight Multiplier: Weight applied to trend components when ADX < threshold (e.g., 0.5). • Scale VWMA Momentum: Toggle normalization of VWMA momentum magnitude. o VWMA Mom Scale Lookback: Period for average absolute VWMA momentum. • Scale ATR Breakout Strength: Toggle normalization of breakout distance by ATR. o ATR Scale Cap: Maximum multiple of ATR used for breakout strength. • Enable Price-RSI Divergence: Toggle divergence detection. o RSI Length for Divergence: Period for RSI. o Pivot Lookback for Divergence: Bars on each side to identify pivot high/low. o Divergence Penalty: Amount to subtract/add to score when divergence detected (e.g., 0.5). 3. Score Settings • Smooth Score: Toggle EMA smoothing of normalized score. • Score Smoothing Length: Period for smoothing EMA. • Weak Threshold: Absolute score value under which trend is considered weak or neutral. • Medium Threshold: Score above Weak but below Medium is moderate. • Strong Threshold: Score above this indicates strong trend. 4. Visualization Settings • Show Δ Score Histogram: Toggle display of the bar-to-bar change in score as a histogram. Default true. • Show Divergence Fill: Toggle background fill highlighting confirmed divergences. Default true. Each input has a tooltip in the code. ________________________________________ ## 10. Limitations, Repaint Notes, and Disclaimers 10.1. Repaint & Lag Considerations • Pivot-Based Divergence Lag: The divergence detection uses ta.pivothigh / ta.pivotlow with a specified lookback. By design, a pivot is only confirmed after the lookback number of bars. As a result: o Divergence labels or fills appear with a delay equal to the pivot lookback. o Once the pivot is confirmed and the divergence is detected, the fill/label does not repaint thereafter, but you must understand and accept this lag. o Users should not treat divergence highlights as predictive signals without additional confirmation, because they appear after the pivot has fully formed. • Higher-Timeframe EMA Alignment: Uses request.security(..., lookahead=barmerge.lookahead_off), so no future data from the higher timeframe is used. This avoids lookahead bias and ensures signals are based only on completed higher-timeframe bars. • No Future Data: All calculations are designed to avoid using future information. For example, manual ADX uses RMA on past data; security calls use lookahead_off. 10.2. Market & Noise Considerations • In very choppy or low-liquidity markets, some components (e.g., volume spikes or VWMA momentum) may be noisy. Users can disable or adjust those components’ parameters. • On extremely low timeframes, noise may dominate; consider smoothing lengths or disabling certain features. • On very high timeframes, pivots and breakouts occur less frequently; adjust lookbacks accordingly to avoid sparse signals. 10.3. Not a Standalone Trading System • This is an indicator, not a complete trading strategy. It provides signals and context but does not manage entries, exits, position sizing, or risk management. • Users must combine it with their own analysis, money management, and confirmations (e.g., price patterns, support/resistance, fundamental context). • No guarantees: past behavior does not guarantee future performance. 10.4. Disclaimers • Educational Purposes Only: The script is provided as-is for educational and informational purposes. It does not constitute financial, investment, or trading advice. • Use at Your Own Risk: Trading involves risk of loss. Users should thoroughly test and use proper risk management. • No Guarantees: The author is not responsible for trading outcomes based on this indicator. • License: Published under Mozilla Public License 2.0; code is open for viewing and modification under MPL terms. ________________________________________ ## 11. Alerts • The indicator defines three alert conditions: 1. Bullish Trend: when the aggregated score crosses above the Weak threshold. 2. Bearish Trend: when the score crosses below the negative Weak threshold. 3. Neutral Trend: when the score returns within ±Weak after being outside. Good luck – BullByte

Indicateur Pine Script®

Hilbert micro trends Sub The HILBERT MICRO TRENDS indicator uses advanced Digital Signal Processing techniques to uncover hidden characteristics in price series, providing a statistical edge across all types of assets. This indicator specializes in detecting short- and medium-term micro trends, which can appear isolated, embedded within larger trends, or even during broad-ranging price phases. It operates with a single parameter, simplifying configuration and greatly reducing the risk of overfitting. HILBERT MICRO TRENDS applies modern low-pass and high-pass filtering techniques to smooth price data and remove noise efficiently across multiple levels. The mathematical formulas generate four recursively smoothed series, each more refined than the last in a subtle and precise way, avoiding abrupt changes. These smoothed series outperform traditional moving averages in every aspect: they have less lag (detecting trend shifts faster), generate fewer false signals, and stay closer to price action. This gives them an edge over standard indicators and algorithms based on conventional moving averages such as the simple, exponential, Kalman, or Hull MA. Visual Structure The indicator displays in two parts: one on the main chart and one on a sub-chart. On the main chart, the four smoothed series create a shaded area, with the upper and lower bounds representing the maximum and minimum of the series. If a series is rising (positive derivative), it signals bullish momentum; if falling, bearish. Since each series has a different smoothing level, they represent different time perspectives, and the indicator considers all four simultaneously. If all series are bullish, the area turns solid green. If three are bullish and one bearish, it's pale green. Two bullish, two bearish: gray. One bullish and three bearish: pale red. All bearish: solid red. A confirmed micro trend is present only when all four are aligned, i.e., when the area is pure green or red. The sub-chart displays a histogram version of the same shaded area as an oscillator. An additional smoothed line tracks when the width of this shaded area expands or contracts. How to Use and Interpret As stated, the goal is to detect micro trends in price. The first rule is to open long positions only when the area is solid green, and shorts only when it’s solid red. Transitions from pale green to solid green can signal the start of a bullish micro trend, and similarly, from pale red to solid red for bearish trends. The width of the shaded area indicates the strength of the movement (best seen in the histogram). A wider area suggests stronger momentum, which is related to volatility only when a micro trend is active. Use the orange line in the histogram to determine whether the micro trend is gaining or losing strength. A decreasing width suggests the trend might be ending, signaling an exit opportunity. However, since the orange line lags behind, it’s better used as confirmation rather than a trigger. For quicker signals, changes to pure red or green are more effective. Price Relationship Pay attention to the price's relative position to the shaded area. If the price stays within or fluctuates inside the area, it's usually a sign of a ranging market with no clear trend—avoid trading in such conditions. However, if the price breaks out and moves away from the area, it's a strong sign a micro trend has begun. When the price returns to the shaded area, the trend might be ending. The indicator also marks pivot points from the last pure green or red zone. While not directly used to enter trades, these serve as useful price action reference points for combining with other strategies or tools. Parameter Settings The indicator includes a single but crucial parameter that controls smoothing intensity. A low value makes the indicator faster; a higher value slows it down. Success depends on choosing the right setting for the market environment. For long, clear trends, use higher values (80–100), as late entries are acceptable and premature exits are avoided. For shorter, mean-reverting trends, lower values (~40) are better to avoid lag. The default setting is 60, which suits most markets, but users are encouraged to adjust it to current conditions. Always identify the current market phase and backtest how past micro trends have behaved on the instrument being traded. This ensures the indicator is tuned to the asset’s behavior and can deliver optimal results.

Indicateur Pine Script®

Hilbert micro trends Main The HILBERT MICRO TRENDS indicator uses advanced Digital Signal Processing techniques to uncover hidden characteristics in price series, providing a statistical edge across all types of assets. This indicator specializes in detecting short- and medium-term micro trends, which can appear isolated, embedded within larger trends, or even during broad-ranging price phases. It operates with a single parameter, simplifying configuration and greatly reducing the risk of overfitting. HILBERT MICRO TRENDS applies modern low-pass and high-pass filtering techniques to smooth price data and remove noise efficiently across multiple levels. The mathematical formulas generate four recursively smoothed series, each more refined than the last in a subtle and precise way, avoiding abrupt changes. These smoothed series outperform traditional moving averages in every aspect: they have less lag (detecting trend shifts faster), generate fewer false signals, and stay closer to price action. This gives them an edge over standard indicators and algorithms based on conventional moving averages such as the simple, exponential, Kalman, or Hull MA. Visual Structure The indicator displays in two parts: one on the main chart and one on a sub-chart. On the main chart, the four smoothed series create a shaded area, with the upper and lower bounds representing the maximum and minimum of the series. If a series is rising (positive derivative), it signals bullish momentum; if falling, bearish. Since each series has a different smoothing level, they represent different time perspectives, and the indicator considers all four simultaneously. If all series are bullish, the area turns solid green. If three are bullish and one bearish, it's pale green. Two bullish, two bearish: gray. One bullish and three bearish: pale red. All bearish: solid red. A confirmed micro trend is present only when all four are aligned, i.e., when the area is pure green or red. The sub-chart displays a histogram version of the same shaded area as an oscillator. An additional smoothed line tracks when the width of this shaded area expands or contracts. How to Use and Interpret As stated, the goal is to detect micro trends in price. The first rule is to open long positions only when the area is solid green, and shorts only when it’s solid red. Transitions from pale green to solid green can signal the start of a bullish micro trend, and similarly, from pale red to solid red for bearish trends. The width of the shaded area indicates the strength of the movement (best seen in the histogram). A wider area suggests stronger momentum, which is related to volatility only when a micro trend is active. Use the orange line in the histogram to determine whether the micro trend is gaining or losing strength. A decreasing width suggests the trend might be ending, signaling an exit opportunity. However, since the orange line lags behind, it’s better used as confirmation rather than a trigger. For quicker signals, changes to pure red or green are more effective. Price Relationship Pay attention to the price's relative position to the shaded area. If the price stays within or fluctuates inside the area, it's usually a sign of a ranging market with no clear trend—avoid trading in such conditions. However, if the price breaks out and moves away from the area, it's a strong sign a micro trend has begun. When the price returns to the shaded area, the trend might be ending. The indicator also marks pivot points from the last pure green or red zone. While not directly used to enter trades, these serve as useful price action reference points for combining with other strategies or tools. Parameter Settings The indicator includes a single but crucial parameter that controls smoothing intensity. A low value makes the indicator faster; a higher value slows it down. Success depends on choosing the right setting for the market environment. For long, clear trends, use higher values (80–100), as late entries are acceptable and premature exits are avoided. For shorter, mean-reverting trends, lower values (~40) are better to avoid lag. The default setting is 60, which suits most markets, but users are encouraged to adjust it to current conditions. Always identify the current market phase and backtest how past micro trends have behaved on the instrument being traded. This ensures the indicator is tuned to the asset’s behavior and can deliver optimal results.

Indicateur Pine Script®

Frozen Bias Zones – Sentiment Lock-ins Overview The Frozen Bias Zones indicator visualizes market sentiment lock-ins using a combination of RSI, MACD, and OBV. It creates "bias zones" that indicate whether the market is in a sustained bullish or bearish phase. These zones are then highlighted on the chart, helping traders spot when the market is locked in a bias. The script also detects breakout events from these zones and marks them with clear labels for easier decision-making. Features Multi-Indicator Sentiment Analysis: Combines RSI, MACD, and OBV to detect synchronized bullish or bearish sentiment. Frozen Bias Zones: Identifies and visually represents zones where the market has remained in a particular sentiment (bullish or bearish) for a defined period. Breakout Alerts: Displays labels to indicate when the price breaks out of the established bias zone. Customizable Inputs: Adjust the zone duration, RSI, MACD, and breakout label visibility. Input Parameters Bias Duration (biasLength) The minimum number of candles the market must stay in a specific sentiment to consider it a "Frozen Bias Zone". Default: 5 candles. RSI Period (rsiPeriod) Period for the Relative Strength Index (RSI) calculation. Default: 14 periods. MACD Settings MACD Fast (macdFast): The fast-moving average period for the MACD calculation. Default: 12. MACD Slow (macdSlow): The slow-moving average period for the MACD calculation. Default: 26. MACD Signal (macdSig): The signal line period for MACD. Default: 9. Show Break Label (showBreakLabel) Toggle to show labels when the price breaks out of the bias zone. Default: True (shows label). Bias Zone Colors Bullish Bias Color (bullColor): The color for bullish zones (light green). Bearish Bias Color (bearColor): The color for bearish zones (light red). How It Works This indicator analyzes three key market metrics to determine whether the market is in a bullish or bearish phase: RSI (Relative Strength Index) Measures the speed and change of price movements. RSI > 50 indicates a bullish phase, while RSI < 50 indicates a bearish phase. MACD (Moving Average Convergence Divergence) Measures the relationship between two moving averages of the price. A positive MACD histogram indicates bullish momentum, while a negative histogram indicates bearish momentum. OBV (On-Balance Volume) Uses volume flow to determine if a trend is likely to continue. A rising OBV indicates bullish accumulation, while a falling OBV indicates bearish distribution. Bias Zone Detection The market sentiment is considered bullish if all three indicators (RSI, MACD, and OBV) are bullish, and bearish if all three indicators are bearish. Bullish Zone: A zone is created when the market sentiment remains bullish for the duration of the specified biasLength. Bearish Zone: A zone is created when the market sentiment remains bearish for the duration of the specified biasLength. These bias zones are visually represented on the chart as colored boxes (green for bullish, red for bearish). Breakout Detection The script automatically detects when the market exits a bias zone. If the price moves outside the bounds of the established zone (either up or down), the script will display one of the following labels: Bias Break (Up): Indicates that the price has broken upwards out of the zone (with a green label). Bias Break (Down): Indicates that the price has broken downwards out of the zone (with a red label). These labels help traders easily identify potential breakout points. Example Use Case Bullish Market Conditions: If the RSI is above 50, the MACD histogram is positive, and OBV is increasing, the script will highlight a green bias zone. Traders can watch for potential bullish breakouts or trend continuation after the zone ends. Bearish Market Conditions: If the RSI is below 50, the MACD histogram is negative, and OBV is decreasing, the script will highlight a red bias zone. Traders can look for potential bearish breakouts when the zone ends. Conclusion The Frozen Bias Zones indicator is a powerful tool for traders looking to visualize prolonged market sentiment, whether bullish or bearish. By combining RSI, MACD, and OBV, it helps traders spot when the market is "locked in" to a bias. The breakout labels make it easier to take action when the price moves outside of the established zone, potentially signaling the start of a new trend. Instructions To use this script: Add the Frozen Bias Zones indicator to your TradingView chart. Adjust the input parameters to suit your trading strategy. Observe the colored bias zones on your chart, along with breakout labels, to make informed decisions on trend continuation or reversal.

Indicateur Pine Script®

par CryptoSnagger

TrendPredator PRO The TrendPredator PRO Stacey Burke, a seasoned trader and mentor, developed his trading system over the years, drawing insights from influential figures such as George Douglas Taylor, Tony Crabel, Steve Mauro, and Robert Schabacker. His popular system integrates select concepts from these experts into a consistent framework. While powerful, it remains highly discretionary, requiring significant real-time analysis, which can be challenging for novice traders. The TrendPredator indicators support this approach by automating the essential analysis required to trade the system effectively and incorporating mechanical bias and a multi-timeframe concept. They provide value to traders by significantly reducing the time needed for session preparation, offering all relevant chart analysis and signals for live trading in real-time. The PRO version offers an advanced pattern identification logic that highlights developing context as well as setups related to the constellation of the signals provided. It provides real-time interpretation of the multi-timeframe analysis table, following an extensive underlying logic with more than 150 different setup variations specifically developed for the system and indicator. These setups are constantly back- and forward-tested and updated according to the results. This version is tailored to traders primarily trading this system and following the related setups in detail. The former TrendPredator ES version does not provide that option. It is significantly leaner and is designed for traders who want to use the multi-timeframe logic as additional confluence for their trading style. It is very well suited to support many other trading styles, including SMC and ICT. The Multi-timeframe Master Pattern Inspired by Taylor’s 3-day cycle and Steve Mauro’s work with “Beat the Market Maker,” Burke’s system views markets as cyclical, driven by the manipulative patterns of market makers. These patterns often trap traders at the extremes of moves above or below significant levels with peak formations, then reverse to utilize their liquidity, initiating the next phase. Breakouts away from these traps often lead to range expansions, as described by Tony Crabel and Robert Schabacker. After multiple consecutive breakouts, especially after the psychological number three, overextension might develop. A break in structure may then lead to reversals or pullbacks. The TrendPredator Indicator and the related multi-timeframe trading system are designed to track these cycles on the daily timeframe and provide signals and trade setups to navigate them. Bias Logic and Multi-Timeframe Concept The indicator covers the basic signals of Stacey Burke's system: - First Red Day (FRD): Bearish break in structure, signalling weak longs in the market. - First Green Day (FGD): Bullish break in structure signalling weak shorts in the markt. - Three Days of Longs (3DL): Overextension signalling potential weak longs in the market. - Three Days of Shorts (3DS): Overextension signalling potential weak shorts in the market. - Inside Day (ID): Contraction, signalling potential impulsive reversal or range expansion move. It enhances the original system by introducing: Structured Bias Logic: Tracks bias by following how price trades concerning the last previous candle high or low that was hit. For example if the high was hit, we are bullish above and bearish below. - Bullish state: Breakout (BO), Fakeout Low (FOL) - Bearish state: Breakdown (BD), Fakeout High (FOH) Multi-Timeframe Perspective: - Tracks all signals across H4, H8, D, W, and M timeframes, to look for alignment and follow trends and momentum in a mechanical way. Developing Context: - Identifies specific predefined context states based on the monthly, weekly and daily bias. Developing Setups: - Identifies specific predefined setups based on context and H8 bias as well as SB signals. The indicator monitors the bias and signals of the system across all relevant timeframes and automates the related graphical chart analysis as well as context and setup zone identification. In addition to the master pattern, the system helps to identify the higher timeframe situation and follow the moves driven by other timeframe traders to then identify favourable context and setup situations for the trader. Example: Full Bullish Cycle on the Daily Timeframe with Multi-Timeframe Signals - The Trap/Peak Formation The market breaks down from a previous day’s and maybe week’s low—potentially after multiple breakdowns—but fails to move lower and pulls back up to form a peak formation low and closes as a first green day. MTF Signals: Bullish daily and weekly fakeout low; three consecutive breakdown days (1W Curr FOL, 1D Curr FOL, BO 3S). Context: Reversal (REV) Setup: Fakeout low continuation low of day (FOL Cont LOD) - Pullback and Consolidation The next day pulls further up after first green day signal, potentially consolidates inside the previous day’s range. MTF Signals: Fakeout low and first green day closing as an inside day (1D Curr IS, Prev FOL, First G). Context: Reversal continuation (REV Cont) Setup: Previous fakeout low continuation low handing fruit (Prev FOL Cont LHF) - Range Expansion/Trend The following day breaks up through the previous day’s high, launching a range expansion away from the trap. MTF Signals: Bullish daily breakout of an inside day (1D Curr BO, Prev IS). Context: Uptrend healthy (UT) Setup: Breakout continuation low hanging fruit (BO Cont LHF) - Overextension After multiple consecutive breakouts, the market reaches a state of overextension, signalling a possible reversal or pullback. MTF Signals: Three days of breakout longs (1D Curr BO, Prev BO, BO 3L). Context: Uptrend extended (UT) - Reversal After a breakout of previous days high that fails, price pulls away from the high showing a rollover of momentum across all timeframes and a potential short setup. MTF Signals: Three days of breakout longs, daily fakeout high (1D 3L, FOH) Context: Reversal countertrend (REV) Setup: Fakeout high continuation high of day (FOH Cont HOD) Note: This is only one possible illustrative scenario; there are many variations and combinations. Example Chart: Full Bullish Cycle with Correlated Signals Multi-Timeframe Signals examples: Context and Setups examples: Note: The signals shown along the move are manually added illustrations. The indicator shows these in realtime in the table at top and bottom right. This is only one possible scenario; there are many variations and combinations. Due to the fractal nature of markets, this cycle can be observed across all timeframes. The strongest setups occur when there is multi-timeframe alignment. For example, a peak formation and potential reversal on the daily timeframe have higher probability and follow-through when they align with bearish signals on higher timeframes (e.g., weekly/monthly BD/FOH) and confirmation on lower timeframes (H4/H8 FOH/BD). With this perspective, the system enables the trader to follow the trend and momentum while identifying rollover points in a highly differentiated and precise way. Using the Indicator for Trading The automated analysis provided by the indicator can be used for thesis generation in preparation for a session as well as for live trading, leveraging the real-time updates as well as the context and setup indicated or alerted. It is recommended to customize the settings deeply, such as hiding the lower timeframes for thesis generation or the specific alert time window and settings to the specific trading schedule and playbook of the trader. 1. Context Assessment: Evaluate alignment of higher timeframes (e.g., Month/Week, Week/Day). More alignment → Stronger setups. - The context table offers an interpretation of the higher timeframe automatically. See below for further details. 2. Setup Identification: Follow the bias of daily and H8 timeframes. A setup mostly requires alignment of these. Setup Types: - Trend Trade: Trade in alignment with the previous day’s trend. Example: Price above the previous day’s high → Focus on long setups (dBO, H8 FOL) until overextension or reversal signs appear (H8 BO 3L, First R). - Reversal Trade: Identify reversal setups when lower timeframes show rollovers after higher timeframe weakness. Example: Price below the previous day’s high → Look for reversal signals at the current high of day (H8 FOH, BO 3L, First R). - The setup table shows potential setups for the specific price zone in the table automatically. See below for further details. 3. Entry Confirmation: Confirm entries based on H8 and H4 alignment, candle closes and lower timeframe fakeouts. - H8 and H4 should always align for a final confirmation, meaning the breach lines should be both in the back of a potential trade setup. - M15/ 5 candle close can be seen as acceptance beyond a level or within the setup zone. - M15/5 FOH/ FOL signals lower timeframe traps potentially indicating further confirmation. Example Chart Reversal Trade: Context: REV (yellow), Reversal counter trend, Month in FOL with bearish First R, Week in BO but bearishly overextended with BO 3L, Day in Fakeout high reversing bearishly. Setup: FOH Cont HOD (red), Day in Fakeout high after BO 3L overextension, confirmed by H8 FOH high of day, First R as further confluence. Two star quality and countertrend. Entry: H4 BD, M15 close below followed by M15 FOH. Detailed Features and Options 1. Context and Setup table The Context and Setup Table is the core feature of the TrendPredator PRO indicator. It delivers real-time interpretation of the multi-timeframe analysis based on an extensive underlying logic table with over 150 variations, specifically developed for this system and indicator. This logic is continuously updated and optimized to ensure accuracy and performance. 1.1. Developing Context States for developing higher timeframe context are determined based on signals from the monthly, weekly, and daily timeframes. - Green and Red indicate alignment and potentially interesting developing setups. - Yellow signals a mixed or conflicting bias, suggesting caution when taking trades. The specific states are: - UT (yellow): Uptrend extended - UT (green): Uptrend healthy - REV (yellow): Reversal day counter trend - REV (green): Reversal day mixed trend - REV Cont (green): Reversal continuation mixed trend - REV Cont (yellow): Reversal continuation counter trend - REV into UT (green): Reversal day into uptrend - REV Cont into UT (green): Reversal continuation into uptrend - UT Pullback (yellow): Counter uptrend breakdown day - Conflicting (yellow): Conflicting signals - Consolidating (yellow): Consolidating sideways - Inside (yellow): Trading inside after an inside week - DT Pullback (yellow): Counter downtrend breakout day - REV Cont into DT (red): Reversal continuation into downtrend - REV into DT (red): Reversal day into downtrend - REV Cont (yellow): Reversal continuation counter trend - REV Cont (red): Reversal continuation mixed trend - REV (red): Reversal day mixed trend - REV (yellow): Reversal day countertrend - DT (red): Downtrend healthy - DT (yellow): Downtrend extended Example: Uptrend The Uptrend Context (UT, green) indicates a healthy uptrend with all timeframes aligning bullishly. In this case, the monthly is in a Fakeout Low (FOL) and currently inside the range, while the weekly and daily are both in Breakout (BO) states. This context is favorable for developing long setups in the direction of the trend. Example: Uptrend pullback The Uptrend Pullback Context (UT Pullback, yellow) indicates a Breakdown (BD) on the daily timeframe against a higher timeframe uptrend. In this case, the monthly is in a Fakeout Low (FOL) and currently inside its range, the weekly is in Breakout (BO) and also currently inside, while the daily is in Breakdown (BD). This context reflects a conflicting situation—potentially signaling either an early reversal back into the uptrend or, if the breakdown extends, the beginning of a possible trend change. Example: Reversal into Uptrend The Reversal into Uptrend Context (REV into UT, green) indicates a lower timeframe reversal aligning with a higher timeframe uptrend. In this case, the monthly is in Breakout (BO), the weekly is in Breakout (BO) and currently inside its range, while the daily is showing a bullish Fakeout Low (FOL) reversal. This context is potentially very favorable for long setups, as it signals a strong continuation of the uptrend supported across multiple timeframes. Example: Reversal The Bearish Reversal Context indicates a lower timeframe rollover within an ongoing higher timeframe uptrend. In this case, the monthly remains in Breakout (BO), the weekly has shifted into a Fakeout High (FOH) after three weeks of breakout longs, and the daily is already in Breakdown (BD). This context suggests a potentially favorable developing short setup, as early signs of weakness appear across timeframes. 1.2. Developing Setup The states for specific setups are based on the context and the signals from the daily timeframe and H8, indicating that price is in the zone of alignment. The setup description refers to the state of the daily timeframe, while the suffix relates to the H8 timeframe. For example, "prev FOH Cont LHF" means that the previous day is in FOH (Fakeout High) relative to yesterday's breakout level, currently trading inside, and we are in an H8 breakdown, indicating a potential LHF (Lower High Formation) short trade if the entry confirms. The suffix HOD means that H8 is in FOH or BO (Breakout). The specific states are: - REV HOD (red): Reversal high of day - REV Cont LHF (red): Reversal continuation low hanging fruit - BO Cont LHF (green): Breakout continuation low hanging fruit - BO Cont LOD (green): Breakout continuation low of day - FOH Cont HOD (red): Fakeout high continuation high of day - FOH Cont LHF ((red): Fakeout high continuation low hanging fruit - prev BD Cont HOD (red): Previous breakdown continuation high of day - prev BD Cont LHF (red): Previous breakdown continuation low hanging fruit - prev FOH Cont HOD (red): Previous fakeout high continuation high of day - prev FOH Cont LHF (red): Previous fakeout high continuation low hanging fruit - prev FOL Cont LOD (green): Previous fakeout low continuation low of day - prev FOL Cont LHF (green): Previous fakeout low continuation low hanging fruit - prev BO Cont LOD (green): Previous breakout continuation low of day - prev BO Cont LHF (green): Previous breakout continuation low hanging fruit - FOL Cont LHF (green): Fakeout low continuation low hanging fruit - FOL Cont LOD (green): Fakeout low continuation low of day - BD Cont LHF (red): BD continuation low hanging fruit - BD Cont LOD (red): Breakdown continuation low of day - REV Cont LHF (green): Reversal continuation low hanging fruit - REV LOD (green): Reversal low of day - Inside: Trading inside after an inside day Type: Indicates the situation of the indicated setup concerning: - Trend: Following higher timeframe trend - Mixed: Mixed higher timeframe signals - Counter: Against higher timeframe bias Quality: Indicates the quality of the indicated setup according to the specified logic table No star: Very low quality * One star: Low quality ** Two star: Medium quality *** Three star: High quality Example: Breakout Continuation Trend Setup This setup highlights a healthy uptrend where the month is in a breakout, the week is in a fakeout low, and the day is in a breakout after a first green day. As the H8 breaks out to the upside, a long setup zone is triggered, presenting a breakout continuation low-hanging fruit trade. This is a trend trade in an overextended situation on the H8, with an H8 3L, resulting in an overall quality rating of one star. Example: Fakeout Low Continuation Trend Setup This setup shows a reversal into uptrend, with the month in a breakout, the week in a breakout, and the day in a fakeout low after breaking down the previous day and now reversing back up. As H8 breaks out to the upside, a long setup zone is triggered, presenting a previous fakeout low continuation, low-hanging fruit trade. This is a medium-quality trend trade. Example: Reversal Setup - Mixed Trend This setup shows a reversal setup in line with the weekly trend, with the month in a fakeout low, the week in a fakeout high, and the day in a fakeout high after breaking out earlier in the day and now reversing back down. As H8 loses the previous breakout level after 3 breakouts (with H8 3L), a short setup zone is triggered, presenting a fakeout high continuation at the high of the day. This is a high-quality trade in a mixed trend situation. Setup Alerts: Alerts can be activated for setups freshly triggered on the chart within your trading window. Detailed filter logic for setup alerts: - Setup quality: 1-3 star - Setup type: Counter, Mixed and Trend - Setup category: e.g. Reversal Bearish, Breakout, Previous Fakeout High - 1D BO and First signals: 3DS, 3DL, FRD, FGD, ID Options: - Alerts on/ off - Alert time window (from/ to) - Alert filter customization Note: To activate alerts from a script in TradingView, some settings need to be adjusted. Open the "Create Alert" dialog and select the option "Any alert() function call" in the "Condition" section. Choose "TrendPredator PRO" to ensure that alerts trigger properly from the code. Alerts can be activated for entire watchlists or individual pairs. Once activated, the alerts run in the background and notify the user whenever a setup is freshly triggered according to the filter settings. 2. Multi-Timeframe Table Provides a real-time view of system signals, including: Current Timeframe (Curr): Bias states. - Breakout (green BO): Bullish after breaking above the previous high. - Fakeout High (red FOH): Bearish after breaking above the previous high but pulling back down. - Breakdown (red BD): Bearish after breaking below the previous low. - Fakeout Low (green FOL): Bullish after breaking below the previous low but pulling back up. - Inside (IS): Price trading neutral inside the previous range, taking the previous bias (color indicates the previous bias). Previous Timeframe (Prev): Tracks last candle bias state and transitions dynamically. - Bias for last candle: BO, FOH, BD, FOL in respective colors. - Inside bar (yellow IS): Indicated as standalone signal. Note: Also previous timeframes get constantly updated in real time to track the bias state in relation to the level that was hit. This means a BO can still lose the level and become a FOH, and vice versa, and a BD can still become a FOL, and vice versa. This is critical to see for example if traders that are trapped in that timeframe with a FOH or FOL are released. An inside bar stays fixed, though, since no level was hit in that timeframe. Breakouts (BO): Breakout count 3 longs and 3 shorts. - 3 Longs (red 3L): Bearish after three breakouts without hitting a previous low. - 3 Shorts (green 3S): Bullish after three breakdowns without hitting a previous high. First Countertrend Close (First): Tracks First Red or Green Day. - First Green (G): After two consecutive red closes. - First Red (R): After two consecutive green closes. Options: Customizable font size and label colors. 3. Historic Highs and Lows Displays historic highs and lows per timeframe for added context, enabling users to track sequences over time. Timeframes: H4, H8, D, W, M Options: Customize for timeframes shown, number of historic candles per timeframe, colors, formats, and labels. 4. Previous High and Low Extensions Displays extended previous levels (high, low, and close) for each timeframe to assess how price trades relative to these levels. H4: P4H, P4L, P4C H8: P8H, P8L, P8C Daily: PDH, PDL, PDC Weekly: PWH, PWL, PWC Monthly: PMH, PML, PMC Options: Fully customizable for timeframes shown, colors, formats, and labels. 5. Breach Lines Tracks live market reactions (e.g., breakouts or fakeouts) per timeframe for the last previous high or low that was hit, highlighting these levels originating at the breached candle to indicate bias (color-coded). Red: Bearish below Green: Bullish above H4: 4FOL, 4FOH, 4BO, 4BD H8: 8FOL, 8FOH, 8BO, 8BD D: dFOL, dFOH, dBO, dBD W: wFOL, wFOH, wBO, wBD M: mFOL, mFOH, mBO, mBD Options: Fully customizable for timeframes shown, colors, formats, and labels. Overall Options: Toggle single feature groups on/off. Customize H8 open/close time as an offset to UTC to be provider independent. Colour settings con be adjusted for dark or bright backgrounds. Higher Timeframe Use Case Examples Example Use Case: Weekly Template Analysis The Weekly Template is a core concept in Stacey Burke’s trading style. The analysis is conducted on the daily timeframe, focusing on the higher timeframe bias and identifying overextended conditions within the week—such as multiple breakouts and peak formations signaling potential reversals. In this example, the candles are colored by the TrendPredator FO indicator, which highlights the state of individual candles. This allows for precise evaluation of both the trend state and the developing weekly template. It is a valuable tool for thesis generation before a trading session and for backtesting purposes. Example Use Case: High Timeframe 5-Star Setup Analysis (Stacey Burke "ain't coming back" ACB Template) This analysis identifies high-probability trade opportunities when daily breakout or breakdown closes occur near key monthly levels mid-week, signaling overextensions and potentially large parabolic moves. The key signal to look for is a breakout or breakdown close on a Wednesday. This is useful for thesis generation before a session and also for backtesting. In this example, the TrendPredator FO indicator colors the candles to highlight individual candle states, particularly those that close in breakout or breakdown. Additionally, an indicator is shown on the chart shading every Wednesday, making it easier to visually identify the signals. 5 Star Alerts: Alerts can be activated for this potential 5-Star setup constellation. The alert is triggered when there is a breakout or breakdown close on a Wednesday. Further recommendations: - Higher timeframe context: TPO or volume profile indicators can be used to gain an even better overview. - Late session trading: Entries later in the session, such as during the 3rd hour of the NY session, offer better analysis and follow-through on setups. - Entry confirmation: Momentum indicators like VWAP, Supertrend, or EMA are helpful for increasing precision. Additionally, tracking lower timeframe fakeouts can provide powerful confluence. To track those the TrendPredator Fakeout Highlighter (FO), that has been specifically developed for this can be of great help: Limitations: Data availability using TradingView has its limitations. The indicator leverages only the real-time data available for the specific timeframe being used. This means it cannot access data from timeframes lower than the one displayed on the chart. For example, if you are on a daily chart, it cannot use H8 data. Additionally, on very low timeframes, the historical availability of data might be limited, making higher timeframe signals unreliable. To address this, the indicator automatically hides the affected columns in these specific situations, preventing false signals. Disclaimer This indicator is for educational purposes only and does not guarantee profits. None of the information provided shall be considered financial advice. The indicator does not provide final buy or sell signals but highlights zones for potential setups. Users are fully responsible for their trading decisions and outcomes.

Indicateur Pine Script®

Mis à jour

Volume Standard Deviation Alert Gus Purpose The script detects and alerts traders when the volume of a trading asset significantly exceeds a calculated threshold based on the standard deviation of volume over a specified lookback period. It optionally filters these alerts based on whether the price action is bullish or bearish. Key Components Inputs lookback (default: 20) The number of bars to consider when calculating the moving average and standard deviation of volume. stdDevFactor (default: 2.0) The multiplier for the standard deviation to determine the threshold for a volume spike. alertOnClose (default: true) Determines whether alerts should only be triggered after the bar has closed. checkBullBear (default: false) Enables filtering of alerts based on the bullishness or bearishness of the bar. Calculations volSMA The simple moving average (SMA) of the volume over the lookback period. volStd The standard deviation of the volume over the lookback period. threshold The alert threshold is calculated as: Threshold = volSMA + ( stdDevFactor × volStd ) Threshold=volSMA+(stdDevFactor×volStd) isBullish & isBearish Determines whether the current bar is bullish (close > open) or bearish (close < open). volumeSpikeCondition A condition that triggers when the current volume exceeds the calculated threshold. bullishCondition & bearishCondition Refines the spike condition by requiring the bar to be bullish or bearish when checkBullBear is enabled. finalCondition The ultimate alert condition based on the user’s preference for bullish/bearish filtering. finalTrigger Ensures the alert only triggers at bar close if alertOnClose is set to true. Visualization Plots the SMA of the volume (volSMA) and the threshold line (threshold), helping traders visually understand the conditions. Histograms the current volume and colors the bars: Red: Volume exceeds the threshold. Blue: Volume is below the threshold. Alerts The script generates an alert message when the finalTrigger condition is met: "Bullish Volume Spike!" if the bar is bullish. "Bearish Volume Spike!" if the bar is bearish. "High Volume Spike!" if no bull/bear filter is applied. Alerts are sent using alert() with the message and set to trigger once per bar close. Usage Traders can use this script to identify unusual volume activity, which often precedes significant price movements. Customizability allows traders to tune the lookback period, standard deviation multiplier, and whether to filter for bullish/bearish spikes. Visual and audible cues help in identifying important market events in real time. This indicator is particularly useful for spotting market breakouts or breakdowns driven by high trading activity.

Indicateur Pine Script®

par BTCPortugal

Directional Volume Index Directional Volume Index (DVI) (buying/selling pressure) This index is adapted from the Directional Movement Index (DMI), but based on volume instead of price movements. The idea is to detect building directional volume indicating a growing amount of orders that will eventually cause the price to follow. (DVI is not displayed by default) The rough algorithm for the Positive Directional Volume Index (green bar): calculate the delta to the previous green bar's volume if the delta is positive (growing buying pressure) add it to an SMA, else add 0 (also for red bars) divide these average deltas by the average volume the result is the Positive Directional Volume Index (DVI+) (vice versa for DVI-) Differential Directional Volume Index (DDVI) (relative pressure) Creating the difference of both Directional Volume Indexes (DVI+ - DVI-) creates the Differential Directional Volume Index (DDVI) with rising values indicating a growing buying pressure, falling values a growing selling pressure. (DDVI is displayed by default, smoothed by a custom moving average) Average Directional Volume Index (ADVX) (pressure strength) Putting the relative pressure (DDVI) in relation to the total pressure (DVI+ + DVI-) we can determine the strength and duration of the currently building volume change / trend. For the DMI/ADX usually 20 is an indicator for a strong trend, values above 50 suggesting exhaustion and approaching reversals. (ADVX is not displayed by default, smoothed by a custom moving average) Divergences of the Differential Directional Volume Index (DDVI) (imbalances) By detecting divergences we can detect situations where e.g. bullish volume starts to build while price is in a downtrend, suggesting that there is growing buying pressure indicating an imminent bullish pullback/order block or reversal. (strong and hidden divergences are displayed by default) Divergences Overview: strong bull: higher lows on volume, lower lows on price medium bull: higher lows on volume, equal lows on price weak bull: equal lows on volume, lower lows on price hidden bull: lower lows on volume, higher lows on price strong bear: lower highs on volume, higher highs on price medium bear: lower highs on volume, equal highs on price weak bear: equal highs on volume, higher highs on price hidden bear: higher highs on volume, lower highs on price DDVI Bands (dynamic overbought/oversold levels) Using Bollinger Bands with DDVI as source we receive an averaged relative pressure with stdev band offsets. This can be used as dynamic overbought/oversold levels indicating reversals on sharp crossovers. Alerts As of now there are no alerts built in, but all internal data is exposed via plot and plotshape functions, so it can be used for custom crossover conditions in the alert dialog. This is still a personal research project, so if you find good setups, please let me know.

Indicateur Pine Script®

Mis à jour

Custom RSI & MACD Momentum Entry Signals Indicator Explanation: Custom RSI & MACD Momentum Entry Signals Introduction The "Custom RSI & MACD Momentum Entry Signals" indicator combines the Relative Strength Index (RSI) and the Moving Average Convergence Divergence (MACD) to generate precise long and short entry signals. This indicator offers a powerful combination of overbought/oversold zones, momentum analysis, and RSI-EMA crossovers to assist traders in making better decisions. How the Indicator Works 1. RSI Calculation and EMA The RSI is calculated based on the closing price with an adjustable period (default: 14). An Exponential Moving Average (EMA) of the RSI (default: 9) is plotted to identify RSI trend changes. When the RSI crosses its EMA upwards, it signals a bullish impulse. Conversely, a downward cross indicates a bearish impulse. 2. MACD Calculation and Momentum Shifts The MACD line is derived from the difference between a fast EMA (default: 12) and a slow EMA (default: 26). The Signal line is the EMA of the MACD line (default: 9). The MACD histogram represents the difference between the MACD line and the Signal line. Momentum shifts are detected as follows: Weakening Bearish: Histogram is negative but increasing (less bearish pressure). Strengthening Bullish: Histogram is positive and rising. Weakening Bullish: Histogram is positive but decreasing. Strengthening Bearish: Histogram is negative and falling. Signal Generation Long Signals A Long signal is triggered when all of the following conditions are met: The RSI was previously below 30 (oversold condition). MACD momentum shifts from "strengthening bearish" to "weakening bearish" or turns bullish. The RSI crosses its EMA upwards. A green upward arrow is displayed below the bar, and the background is lightly shaded green for additional visualization. Short Signals A Short signal is triggered when all of the following conditions are met: The RSI was previously above 70 (overbought condition). MACD momentum shifts from "strengthening bullish" to "weakening bullish" or turns bearish. The RSI crosses its EMA downwards. A red downward arrow is displayed above the bar, and the background is lightly shaded red for additional visualization. Visual Elements RSI and EMA: The RSI is shown in purple. The RSI EMA is shown in blue. Horizontal lines at 30 (oversold) and 70 (overbought) provide additional context. MACD: The MACD line is displayed in blue. The Signal line is displayed in orange. The zero line is added for easier interpretation. Signals: Green arrows: Long signals. Red arrows: Short signals. Background color: Light green for long conditions, light red for short conditions. Use Cases This indicator is ideal for: Trend Followers: Combining RSI and MACD allows traders to identify entry points during impulsive trend shifts. Swing Traders: Long and short signals can be used at reversal points to capture short-term price movements. Momentum Traders: By considering MACD momentum, the indicator provides additional confidence in signal generation. Customizable Settings The indicator provides flexible input options: RSI Period (default: 14) RSI EMA Period (default: 9) MACD Parameters: Fast, slow, and signal EMAs can be adjusted. Conclusion The Custom RSI & MACD Momentum Entry Signals indicator is a powerful tool for traders looking to combine RSI and MACD to identify high-probability entry signals. With clear visualization and precise signal generation, traders can make decisions more efficiently and capitalize on market movements.

Indicateur Pine Script®

Black RSI (Multi Symbol RSI)📌 GENERAL OVERVIEW Black RSI (Multi Symbol RSI) is an indicator with multiple-RSI (multi-symbol support), It is a powerful indicator designed for analyzing the relative strength of multiple financial instruments within a single chart. This indicator essentially combines multiple instances of the Relative Strength Index (RSI) for different symbols, allowing traders to compare and contrast market conditions for a broader, simultaneous analysis of various assets. By tracking RSI across multiple assets, traders can identify broader market trends, and sector rotations, or pinpoint relative strengths and weaknesses among different instruments. Please check the below sections for details. Black RSI (Multi Symbol RSI) Indicator Features Summary: + Multiple RSI with multi-symbol ◢ This indicator plots Primary+3 multiple RSI for multiple symbols at once. For instance, it could simultaneously show the RSI of indices (e.g., SPX, NASDAQ) or stocks within a sector, providing insights into how these assets are moving relative to one another. + Custom Divergence Module ◢ It allows the user to select the divergence source among the multiple RSI (Primary, 1st, 2nd or 3rd RSI) and displays regular/hidden bullish/bearish divergence for selected RSI only. + Custom RSI Moving Average/BBs ◢ It allows the user to select the RSI moving average/BBs source among the multiple RSI (Primary, 1st, 2nd or 3rd RSI) and displays moving average/BBs for selected RSI only. + Alert Triggers ◢ The indicator can incorporate alert functions that notify the user when an RSI threshold (e.g., overbought or oversold levels) is crossed for any of the selected symbols. 📌HOW TO USE IT Confirm Trends Across Symbols: Use the indicator to confirm trends across multiple assets. For example, if most symbols within a sector or index are showing RSI levels above 50, it may indicate a bullish trend in that sector. Conversely, if most RSIs are below 50, it may signal bearish sentiment. Spot Divergences: Look for RSI divergences across symbols, which can hint at potential reversals. For instance, if most symbols show declining RSI levels while a few have increasing RSI, it could indicate relative strength in those few, making them candidates for closer watch. Identify Overbought/Oversold Conditions: By observing the RSI levels of multiple symbols, you can identify when certain assets are overbought (typically RSI > 70) or oversold (typically RSI < 30). When multiple assets show similar RSI levels, this can indicate broader market sentiment or sector momentum. Sector Rotation Analysis: In longer-term trading or portfolio rebalancing, a Multi-RSI Multi-Symbol indicator can help detect sector rotation patterns by showing which sectors are gaining strength (higher RSI) and which are weakening, facilitating informed sectoral shifts. Use in Conjunction with Other Indicators: The Multi-RSI can serve as a supporting indicator alongside trend indicators like Moving Averages or Bollinger Bands, helping to confirm entry and exit points. For example, if a symbol’s RSI shows an overbought condition and it aligns with a resistance level from a Moving Average, this could strengthen a sell signal. Customization: Customize the settings to match your trading style. For instance, day traders might prefer a shorter RSI period and timeframes, while swing traders may benefit from longer timeframes and smoother RSI. ⚙️Black RSI (Multi Symbol RSI) SETTINGS Black RSI (Multi) Dashboard ◢ + 1st RSI: Enable/Disable 1st RSI + 2nd RSI: Enable/Disable 2nd RSI + 3rd RSI: Enable/Disable 3rd RSI RSI Primary Tools ◢ + RSI Moving Average/Bollinger Bands: Enable/Disable RSI Moving Average/Bollinger Bands + Smooth RSI: Enable/Disable Smooth RSI (for Primary RSI) + RSI Divergence: Enable/Disable Divergence for user-selected RSI RSI Secondary Tools ◢ + RSI OB/OS Color Bars: Enable/Disable RSI OB/OS Color Bars for user-selected RSI + RSI OB/OS Highlights: Enable/Disable OB/OS Highlights for user-selected RSI + Background: Enable/Disable RSI Background + Primary RSI Settings ▾ - Override Primary RSI Symbol: Allows the user to select the symbol for Primary RSI - Primary RSI Length: User input primary RSI length value - Primary RSI Source: User primary RSI source selection - RSI Line Thickness: User input line thickness value for primary RSI - Primary RSI Colors: - OB/OS Highlights: Enable/Disable OB/OS Primary RSI Highlights - RSI Overbought Threshold: The user can set the RSI overbought threshold value. This Overbought Threshold value will also be applied to All RSI (Primary, 1st, 2nd, 3rd) and "RSI Divergence overbought condition" and "RSI OB/OS Highlights" - RSI Oversold Threshold: The user can set the RSI oversold threshold value. The lower band (oversold line) of RSI. This Oversold Threshold value will also be applied to All RSI (Primary, 1st, 2nd, 3rd) and "RSI Divergence oversold condition" and "RSI OB/OS Highlights" + 1st RSI Settings ▾ - Override 1st RSI Symbol: Allows the user to select the symbol for 1st RSI - 1st RSI Length: User input 1st RSI length value - 1st RSI Source: User 1st RSI source selection - RSI Line Thickness: User input line thickness value for 1st RSI - 1st RSI Colors: - OB/OS Highlights: Enable/Disable OB/OS 1st RSI Highlights + 2nd RSI Settings ▾ - Override 2nd RSI Symbol: Allows the user to select the symbol for 2nd RSI - 2nd RSI Length: User input 2nd RSI length value - 2nd RSI Source: User 2nd RSI source selection - RSI Line Thickness: User input line thickness value for 2nd RSI - 2nd RSI Colors: - OB/OS Highlights: Enable/Disable OB/OS 2nd RSI Highlights + 3rd RSI Settings ▾ - Override 3rd RSI Symbol: Allows the user to select the symbol for 3rd RSI - 3rd RSI Length: User input 3rd RSI length value - 3rd RSI Source: User 3rd RSI source selection - RSI Line Thickness: User input line thickness value for 3rd RSI - 3rd RSI Colors: - OB/OS Highlights: Enable/Disable OB/OS 3rd RSI Highlights + RSI Bands & Threshold Settings ▾ - RSI Middle Band: Allows the user to plot optional RSI band on the RSI Oscillator - RSI Bullish Band: Allows the user to plot optional RSI band on the RSI Oscillator - RSI Bearish Band: Allows the user to plot optional RSI band on the RSI Oscillator + Primary RSI Smooth Settings ▾ - Type: The user selected Smooth MA type for Primary RSI. With RSI Smooth enabled, it will also affect Primary RSI Divergences detection (all divergences will be plotted according to the "Smoothed RSI line") - Length: User input Smooth MA length value for Primary RSI + RSI Moving Average Settings ▾ - MA/BB RSI Source: Allows the user to MA/BB source selection - MA/BB Enable/Disable: Allows the user to select Moving average only, BBs only or Both to display on the RSI Oscillator - RSI Moving Average Colors: Allows the user to select Bullish/Bearish colours of RSI Moving Average - RSI Moving Average Type: Allows the user to select RSI MA Type - RSI Moving Average Length: User input RSI MA length value - RSI Moving Average Thickness: User input RSI MA thickness - Bollinger Bands Colors: Allows the user to select BBs colours - BB StdDev: user input Bollinger Bands standard deviation value + RSI Divergence Settings ▾ - Divergence RSI source: User selection of divergence source . - Divergence source: User selection of divergence source . "oscillator" (divergence detection with high/low or close of RSI), "price" (divergence detection with high/low or close of price) - Bull price source: User selection of Bull price source. Bull price source: "Low" (low of price divergence detection), "Close" (close of price divergence detection) (linked to "price" in "Divergence source") - Bear price source: User selection of Bear price source. Bear price source: "High" (high of price divergence detection), "Close" (close of price divergence detection) (linked to "price" in "Divergence source") - Low/High left bars: How many candles to compare on the left side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signalled, but the quality of those detections could be lower. - Low/High right bars: How many candles to compare on the right side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signalled, but the quality of those detections could be lower. - Maximum lookback bars: The maximum length of a divergence (number of bars). If a detected divergence is longer than this, it will be discarded. - Price threshold: User selection of Price threshold, higher values more lines - RSI threshold: User selection of RSI threshold, higher values more lines - Show Lows: Displays lows of RSI - Show Highs: Displays highs of RSI - Show Divergence as: - Line Style: - Line thickness: User input divergence line thickness value - Label Transparency: it could reduce label mess on the oscillator line, input "100" for label text only without label background - Labels Text Color: User label text colour selection Auto Text Color > Auto colour change of label text according to Dark/Light chart theme - Bull Divergences: Enable/Disable of Bull divergences > Color: User selection of Bull divergence color > Potential Bull: It will plot potential regular bull divergence with a dotted line. - Bear Divergences: Enable/Disable of Bear divergences > Color: User selection of Bear divergence color > Potential Bear: It will plot potential regular bear divergence with a dotted line. - Hidden Bull Div: Enable/Disable of Hidden Bull divergences > Color: User selection of Hidden Bull divergence colour > Potential H.Bull: It will plot potential hidden bull divergence with a dotted line. - Hidden Bear Div: Enable/Disable of Hidden Bear divergences > Color: User selection of Hidden Bear divergence colour > Hidden Bear divergence: It will plot potential hidden bear divergence with a dotted line. > Regular Bull oversold only: It will show Regular Bullish RSI divergences in the oversold zone only, RSI oversold threshold can be configured in the "Primary RSI Settings" section. > Regular Bear overbought only: It will show Regular Bearish RSI divergences in the overbought zone only, RSI overbought threshold can be configured in the "Primary RSI Settings" section. + RSI OB/OS Colored Bars Settings▾ - OB/OS Bar RSI Source: User selection of OB/OS Bars RSI source . - Overbought Bar Color: User RSI OB Bars colour selection - Oversold Bar Color: User RSI OS Bars colour selection + Overbought/Oversold Highlights ▾ - OB/OS Highlights RSI Source: User selection of OB/OS Highlights RSI source . - Overbought Highlights : Enable/Disable Overbought Highlights - Oversold Highlights : Enable/Disable Oversold Highlights - Transparency: Gradient transparency of highlighted area + RSI Line & Label Settings ▾ - Show Symbol label: Enable/Disable each RSI symbol label. - RSI line offset: Shifts the RSI to the left or the right on the given number of bars, Default is 0 + Background Setting ▾ - Custom Background Color: User selection of Background color Feedback & Bug Report If you find any bugs in this indicator or have any suggestions, please let me know. Please give feedback & appreciate it if you like to see more future updates and indicators. Thank you

Indicateur Pine Script®

par NabeelBlack

Mis à jour

Breakouts with Tests & Retests [LuxAlgo]The Breakouts Tests & Retests indicator highlights tests and retests of levels constructed from detected swing points. A swing area of interest switches colors when a breakout occurs. Users can control the sensitivity of the swing point detection and the width of the swing areas. 🔶 USAGE When a Swing point is detected, an area of interest is drawn, colored green for a bullish swing and red when bearish. A test is confirmed when the opening price is situated in the area of interest, and the closing price is above or below the area, depending on whether it is a bullish or bearish swing. Tests are highlighted with a solid-colored triangle. A breakout is confirmed when the price closes in the opposite position, below or above the area, in which case the area will switch colors. If the opening price is located within the area and the closing price closes outside the area, in the same direction as the breakout, this is considered a retest . Retests are highlighted with a hollow-colored triangle. Note that tests/retests do not act on wicks. The main factor is that the opening price is in the area of interest, while the closing price is outside. 🔹 Area Of Interest Width The user can adjust the width of the swing areas. Changing the " Width " is a fast and easy way to find different areas of interest. A higher "Multiple" setting would return a wider area, allowing price to develop within it for a longer period of time and potentially provide later test signals. When a swing area is broken, a higher "Width" setting can make it more complicated for the price to break it again, allowing a swing area to remain valid for a longer period of time thus potentially providing more retest signals. 🔶 DETAILS Generally, only one bullish/bearish pattern can be active at a time. This means that no more than 1 bullish or bearish area will be active. The " Display " settings, however, can help control how areas of different types are displayed. Bullish AND Bearish: Both, bullish and bearish patterns can be drawn at the same time Bullish OR Bearish: Only 1 bullish or 1 bearish pattern is drawn at a time Bullish: Only bullish patterns Bearish: Only bearish patterns 🔹 Test/Retest Labels The user can adjust the settings so only the latest test/retest label is shown or set a minimum number of bars until the next test/retest can be drawn. 🔹 Maximum Bars Users can set a limit of bars for when there is no test/retest in that period; the area of interest won't be updated anymore and will be available and ready for the next Swing. An option for pulling the area back to the last retest is included. 🔶 SETTINGS Display: Determines which swing areas are displayed by the indicator. See the "DETAILS" section for more information Multiple: Adjusts the width of the areas of interest Maximum Bars: Limit of bars for when there is no test/retest Display Test/Retest Labels: Show all labels or just the last test/retest label associated with a swing area Minimum Bars: Minimum bars required for a subsequent test/retest label are allowed to be displayed Set Back To Last Retest: When after "Maximum Bars" no test/retest is found, place the right side of the area at the last test/retest 🔹 Swings Left: x amount of wicks on the left of a potential Swing need to be higher/lower for a Swing to be confirmed. Right: The number of wicks on the right of a potential swing needs to be higher/lower for a Swing to be confirmed. 🔹 Style Bullish: color for test period (before a breakout) / retest period (after a breakout) Bearish: color for test period (before a breakout) / retest period (after a breakout) Label Size

Indicateur Pine Script®

11 22 33 44 55 66 77 88 99 1010 1111 1212 1313 1414 1515 1616 1717 1818 1919 2020 2121 2222 2323 2424 2525 2626 2727 2828 2929 3030 3131 3232 3333 3434 3535 3636 3737 3838 3939 4040 4141 4242

Données de marché sélectionnées fournies par ICE Data Services. Données de référence sélectionnées fournies par FactSet. Copyright © 2025 FactSet Research Systems Inc.Copyright © 2025, American Bankers Association. Base de données CUSIP fournie par FactSet Research Systems Inc. Tous droits réservés. Documents déposés auprès de la SEC et autres documents fournis par Quartr.© 2025 TradingView, Inc.

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