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MLActivationFunctionsLibrary "MLActivationFunctions" Activation functions for Neural networks. binary_step(value) Basic threshold output classifier to activate/deactivate neuron.   Parameters:      value : float, value to process.   Returns: float linear(value) Input is the same as output.   Parameters:      value : float, value to process.   Returns: float sigmoid(value) Sigmoid or logistic function.   Parameters:      value : float, value to process.   Returns: float sigmoid_derivative(value) Derivative of sigmoid function.   Parameters:      value : float, value to process.   Returns: float tanh(value) Hyperbolic tangent function.   Parameters:      value : float, value to process.   Returns: float tanh_derivative(value) Hyperbolic tangent function derivative.   Parameters:      value : float, value to process.   Returns: float relu(value) Rectified linear unit (RELU) function.   Parameters:      value : float, value to process.   Returns: float relu_derivative(value) RELU function derivative.   Parameters:      value : float, value to process.   Returns: float leaky_relu(value) Leaky RELU function.   Parameters:      value : float, value to process.   Returns: float leaky_relu_derivative(value) Leaky RELU function derivative.   Parameters:      value : float, value to process.   Returns: float relu6(value) RELU-6 function.   Parameters:      value : float, value to process.   Returns: float softmax(value) Softmax function.   Parameters:      value : float array, values to process.   Returns: float softplus(value) Softplus function.   Parameters:      value : float, value to process.   Returns: float softsign(value) Softsign function.   Parameters:      value : float, value to process.   Returns: float elu(value, alpha) Exponential Linear Unit (ELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.0, predefined constant, controls the value to which an ELU saturates for negative net inputs. .   Returns: float selu(value, alpha, scale) Scaled Exponential Linear Unit (SELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.67326324, predefined constant, controls the value to which an SELU saturates for negative net inputs. .      scale : float, default=1.05070098, predefined constant.   Returns: float exponential(value) Pointer to math.exp() function.   Parameters:      value : float, value to process.   Returns: float function(name, value, alpha, scale) Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float derivative(name, value, alpha, scale) Derivative Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float
Bibliothèque Pine Script®
par RicardoSantos
2
Stochastic with Outlier Labels/MTFTL;DR This indicator is an update to a simple stochastic ('Stoch_MTF' by binarytrader666) that provides a novel outlier highlighting feature Improvements on stochastic: 1. Novel outlier highlighting that points out crosses that are the Nth consecutive cross or greater. 2. Allowing for multiple timeframes to be shown on the same chart 3. Highlighting/Labelling crosses and providing labels for alerts A cross of the stochastics in the high or low zones establishes a trend. Successive crosses in the same region seem to indicate a continuation of that trend. The outlier functionality here provides a signal for when X number of crosses have been in the same trend, signaling further strength of that signal. I also provided the necessary code for converting this to a strategy if you so wish at the bottom.
Indicateur Pine Script®
par on2valhalla
1
Linear Regression Trend Channel with Entries & AlertsPlease Use this Indicator If you understand the risk posed by linear regression trend channel Features Provides trend channel (best value for period is 40 on 5 minute timeframe Provides BUY/SELL entries based on current channel Provides custom color for channel Best used with MattyPips strategy indicators Risks : Please note, this script is the likes of Bollinger bands and poses a risk of falling in a trend range. Entries may keep running on the same direction while the market is moving.
Indicateur Pine Script®
par MrTuanDoan
23
Moving Average ExponentialThe EMA 50 Trend Filter At the heart of the Sniper system lies the 50-period Exponential Moving Average. Unlike simple moving averages, the EMA applies a weighting factor to recent price data, significantly reducing lag. Role in Strategy: Trend Identification: Serves as the binary divider between Long and Short bias. Dynamic Structure: Acts as dynamic support in uptrends and resistance in downtrends. Signal Filtering: The algorithm automatically suppresses any 'Buy' signals below the line and 'Sell' signals above it, ensuring you never trade against the institutional momentum.
Indicateur Pine Script®
par GiladKatz
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator Introduction and Theoretical Background Design Rationale Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime. Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility. The Solution Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring. How It Works This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals: Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals. Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking. Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion. Why Use It? Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time. ◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow). ◦ Magenta/Pink Flow: Strong Bearish Trend. ◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop. Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend. ⚖️ Chapter 1: System Architecture Introduction: Composite Analytical Framework System Overview Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior. Operational Objective The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence. Market Microstructure Analysis: Limitations of Conventional Models Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies: • Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance. • Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events. • Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution. Core Design Principles To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles: Principle A: Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility. Principle B: Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon. • Concept: This visualization represents the aggregate strength and consistency of the trend. • Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness. Principle C: Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors: 1. Volatility: Confirmed expansion via the Impulse Core. 2. Momentum: Directional alignment via the Hybrid Oscillator. 3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts. 🔍 Chapter 2: Core Modules & Algorithmic Logic Module A: Impulse Core (Normalized Volatility Deviation) Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states. Volatility Z-Score Normalization The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread. ◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion. ◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance. ◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration. f_impulse() => atr_f = ta.atr(fastLen) // Fast Volatility Baseline atr_s = ta.atr(slowLen) // Slow Volatility Baseline std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation (atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation Algorithmic Framework • Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30). • Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback. • Signal Generation: ◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase. ◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move. Module B: Gradient Oscillator (RSI-SMA Hybrid) Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence. Technical Architecture • Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally. • State Analysis: Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals. • Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions. // Laminar Flow Validation f_validate_trend() => // Calculate spread between Ribbon layers ribbon_spread = ta.stdev(ribbon_array, 15) // Only allow signals if Ribbon is expanded (Laminar Flow) is_flowing = ribbon_spread > min_expansion_threshold // If compressed (Knotted), force signal to false is_flowing ? signal : na Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation) This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends. Dynamic Threshold Adjustment • Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles. • Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic. • Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion. Anti-Greed Logic: Dynamic Threshold Calculation f_adjust_threshold(base_slope, win_streak) => // Adds a 10% penalty to the difficulty for every consecutive win penalty_factor = 0.10 risk_scaler = 1 + (win_streak * penalty_factor) // Returns the new, harder-to-reach threshold base_slope * risk_scaler Module D: Trend Baseline (Triple-Smoothed Structure) The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration. Smoothing Stages 1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action. 2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data. 3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve. Functionality This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline 🚦 Chapter 3: Risk Management & Exit Protocols Quantitative Risk Management (TP/SL & Trailing) Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime. • ATR-Based Dynamic Bracketing: The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR). ◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise. ◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry. • Close-Validation Protocol ("Soft Stop"): Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory. ◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold. ◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility. • Step-Function Trailing Mechanism: To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed: ◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold. ◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL. • Algorithmic Exit Protocols (Dynamic Liquidity Analysis) ◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates. ◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust. Multi-Factor Exit Logic (The Tri-Vector System) The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met: • 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown. • 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation. • 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals. 🎨 Chapter 4: Visualization Guide Gradient Oscillator Ribbon The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market. • Visuals: ◦ Cyan/Blue Ribbon: Indicates Bullish Momentum. ◦ Pink/Magenta Ribbon: Indicates Bearish Momentum. • Interpretation: ◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following. ◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity. ◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating. Trend Baseline The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market. • Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish). • Interpretation: Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it. Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends. Entry Signals & Labels Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence. • Visuals: Labeled signals appear above/below specific candles. • Interpretation: These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized. Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital. Dynamic TP/SL Boxes The semi-transparent colored zones drawn via fill() represent the risk management geometry. • Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels. • Function: Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios). SAR + MACD Glow Small glowing shapes appearing above or below candles. • Visuals: Triangle or circle glows near the price bars. • Interpretation: This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup. Support/Resistance Table A small table located at the bottom-right of the chart. • Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support). • Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments. 🖥️ Chapter 5: Dashboard & Operational Guide Integrated Analytics Panel (Dashboard Overview) To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors. A. Intermediate Structure (12H Trend) • Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window. • Interpretation: ◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow. ◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored. ◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor. B. Composite Confluence Score (Signal Confidence) • Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline). • Grading Scale: Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing. Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation. Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone"). C. Statistical Deviation Status (Mean Reversion) • Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA). • Alert States: Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone. Normal: Price is within standard distribution limits, suitable for trend-following entries. D. Volatility Regime Classification • Metric: Compares current ATR against a 100-period historical baseline to categorize the market state. • Regimes: Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events. Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment. High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance. E. Performance Telemetry • Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe. • Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended. Operational Protocols & Signal Decoding Visual Interpretation Standards • Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes. • Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector. • Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure. System Calibration (Settings) • Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias. • Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise. ⚙️ Chapter 6: System Configuration & Alert Guide This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs. 🌐 LANGUAGE SETTINGS (Localization) ◦ Select Language (Default: English): Function: Instantly translates all chart labels, dashboard texts into your preferred language. Supported: English, Korean, Chinese, Spanish ⚡ IMPULSE CORE SETTINGS (Volatility Engine) ◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility. Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react. ◦ Fast Pulse Length (Default: 10): The short-term ATR period. Role: Detects rapid volatility expansion. ◦ Slow Pulse Length (Default: 30): The long-term ATR baseline. Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses. 🎯 TP/SL SETTINGS (Risk Management) ◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation. ◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands. Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs. ◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry. ◦ Use Soft Stop (Close Basis): Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations. 🔊 RIBBON SETTINGS (Momentum Visualization) ◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon. ◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array. ◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon. Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes. 📎 DISPLAY OPTIONS ◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter. ◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles. 📈 TREND BASELINE (Structural Filter) ◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation. ◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline. ◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid. 🧠 SMART EXIT (Dynamic Liquidity) ◦ Use Smart Exit: Enables the momentum exhaustion logic. ◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits. ◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates. 🛡️ TRAILING STOP (Step) ◦ Use Trailing Stop: Activates the step-function trailing mechanism. ◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price. ◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position. 🌀 SAR & MACD SETTINGS (Secondary Confirmation) ◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters. ◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score. ◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals. 🔄 ANTI-GREED LOGIC (Behavioral Bias) ◦ Strict Entry after Win: Enables the negative feedback loop. ◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win. Role: Prevents overtrading and entering at the top of an extended trend. 🌍 HTF FILTER (Multi-Timeframe) ◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals. ◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals). 📉 RSI PEAK & CHOPPINESS ◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected. ◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market. 📐 SLOPE TRIGGER LOGIC ◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity). ◦ Slope Sensitivity (1.5): The angle required to trigger this override. ⛔ FLAT MARKET FILTER (ADX & ATR) ◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend. ◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market). 🔔 Alert Configuration Guide Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events. How to Set Up: Click the "Alert" (Clock) icon in the TradingView toolbar. Select "Impulse Reactor " from the Condition dropdown. Choose one of the specific trigger conditions below: 🚀 Entry Signals (Trend Initiation) Long Entry: Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align). Usage: Use this to enter new Long positions. Short Entry: Trigger: Fires when a confirmed Bearish Setup is detected. Usage: Use this to enter new Short positions. 🎯 Profit Taking (Target Levels) Long TP: Trigger: Fires when price hits the calculated Take Profit level for a Long trade. Usage: Automate partial or full profit taking. Short TP: Trigger: Fires when price hits the calculated Take Profit level for a Short trade. Usage: Automate partial or full profit taking. 🛡️ Defensive Exits (Risk Management) Smart Exit: Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed). Usage: Recommended for tightening stops or closing positions early to preserve gains. Overbought / Oversold: Trigger: Fires when the ribbon extends into extreme zones. Usage: Warning signal to prepare for a potential reversal or pullback. 💡 Secondary Confirmation (Confluence) SAR+MACD Bullish: Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend. Usage: Ideal for Pyramiding (adding to an existing winning position). SAR+MACD Bearish: Trigger: Fires when Parabolic SAR and MACD align bearishly. Usage: Ideal for adding to short positions. ⚠️ Chapter 7: Conclusion & Risk Disclosure Methodological Synthesis Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align. Disclaimer & Risk Warnings ◦ Educational Purpose Only This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. ◦ No Guarantee of Performance Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions. ◦ High-Risk Warning Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades. ◦ Software Limitations The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Indicateur Pine Script®
par ApexLegion
6
Dark VectorThe Dark Vector is a professional-grade trend-following system designed to solve the two most common causes of trading losses: over-trading during chop and exiting trends too early. Unlike standard indicators that continuously recalculate based on every price tick, this system operates on a strict "State Machine" logic. This means it tracks the current market phase and refuses to issue conflicting signals. If the system is Long, it mathematically cannot issue another Long signal until the previous trend has concluded. The system relies on three core engines: 1. The Trend Architecture (Modified SuperTrend) The backbone of the system is an ATR-based trailing stop mechanism. It creates a dynamic trend line that adjusts to volatility. When volatility expands, the line widens to prevent premature stop-outs during market noise. When volatility contracts, the line tightens to protect profits. 2. The Noise Gate (Choppiness Index) This is the system's safety filter. It measures the fractal efficiency of the market—essentially determining if price is moving in a clear direction or moving sideways. When the market enters a consolidation phase (sideways chop), the Noise Gate activates, turning the candles gray and physically blocking all new entry signals. This prevents the user from entering trades in low-probability environments. 3. The Singularity State Machine This internal logic enforces trading discipline. It treats the trend as a binary state (Bullish or Bearish). It forces an alternating signal pattern, ensuring that you are only alerted to the specific moment a major trend reversal occurs, rather than being bombarded with repetitive signals during a long run. Best Way to Use This System To maximize profitability and minimize false positives, it is recommended to use the "Regime & Alignment" methodology outlined below. 1. The Traffic Light Rule Before placing any trade, observe the color of the candlesticks on the chart: Green Candles: The market is in a confirmed Bullish Impulse. You should only look for Long entries or hold existing positions. Shorting is statistically dangerous here. Red Candles: The market is in a confirmed Bearish Impulse. You should only look for Short entries or hold cash. Buying the dip here is high-risk. Gray Candles: The market is in a Chop/Squeeze regime. The Noise Gate is active. Do not open new positions. This indicates indecision, and the market is likely to destroy option premiums or stop out tight leverage. Wait for the candles to return to Green or Red before acting. 2. The Entry Trigger Enter a trade only when a text label (LONG or SHORT) appears. Long Signal: Occurs when price closes above the Trend Line AND the market is not in a Chop zone. Short Signal: Occurs when price closes below the Trend Line AND the market is not in a Chop zone. 3. The Exit Strategy There are two ways to manage the trade once active: The Trend Follower (Conservative): Hold the position until the Trend Line flips color. This captures the maximum duration of the move but may give back some profit at the very end. The Stop Loss (Active): The Trend Line (the white value in your dashboard) acts as your Trailing Stop. If a candle closes beyond this line, the trend is technically invalidated. You should exit immediately. 4. Multi-Timeframe Alignment (The Golden Rule) The highest win rates are achieved when your trading timeframe aligns with the higher-order trend. Step 1: Check the 4-Hour chart. Is the Trend Line Green? Step 2: Switch to the 15-Minute chart. Step 3: Only take the LONG signals on the 15-Minute chart. Ignore all Short signals. Reasoning: Counter-trend trades often fail. By trading only in the direction of the higher timeframe, you are swimming with the current, not against it. Recommended Settings by Style Swing Trading (Daily/4H): Keep the Trend Factor at 4.0. This ignores daily noise and keeps you in the trade for weeks or months. Day Trading (1H/15m): Lower the Trend Factor to 3.0. This makes the system more reactive to intraday reversals. Scalping (5m): Lower the Trend Factor to 2.0 and the ATR Length to 7. This is aggressive and requires strict adherence to the Stop Loss. Disclaimer This indicator is for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any asset. Trading cryptocurrencies, stocks, and futures involves a high degree of risk and the potential for significant financial loss. The user assumes all responsibility for their trading decisions. Past performance of any system or indicator is not indicative of future results. Always practice risk management and never trade with money you cannot afford to lose.
Indicateur Pine Script®
par DarkPoolCrypto
5
RSI adaptive zones [AdaptiveRSI]This script introduces a unified mathematical framework that auto-scales oversold/overbought and support/resistance zones for any period length. It also adds true RSI candles for spotting intrabar signals. Built on the Logit RSI foundation, this indicator converts RSI into a statistically normalized space, allowing all RSI lengths to share the same mathematical footing. What was once based on experience and observation is now grounded in math. ✦ ✦ ✦ ✦ ✦ 💡 Example Use Cases RSI(14): Classic overbought/oversold signals + divergence Support in an uptrend using RSI(14) Range breakouts using RSI(21) Short-term pullbacks using RSI(5) ✦ ✦ ✦ ✦ ✦ THE PAST: RSI Interpretation Required Multiple Rulebooks Over decades, RSI practitioners discovered that RSI behaves differently depending on trend and lookback length: • In uptrends, RSI tends to hold higher support zones (40–50) • In downtrends, RSI tends to resist below 50–60 • Short RSIs (e.g., RSI(2)) require far more extreme threshold values • Longer RSIs cluster near the center and rarely reach 70/30 These observations were correct — but lacked a unifying mathematical explanation. ✦ ✦ ✦ ✦ ✦ THE PRESENT: One Framework Handles RSI(2) to RSI(200) Instead of using fixed thresholds (70/30, 90/10, etc.), this indicator maps RSI into a normalized statistical space using: • The Logit transformation to remove 0–100 scale distortion • A universal scaling based on 2/√(n−1) scaling factor to equalize distribution shapes As a result, RSI values become directly comparable across all lookback periods. ✦ ✦ ✦ ✦ ✦ 💡 How the Adaptive Zones Are Calculated The adaptive framework defines RSI zones as statistical regimes derived from the Logit-transformed RSI . Each boundary corresponds to a standard deviation (σ) threshold, scaled by 2/√(n−1), making RSI distributions comparable across periods. This structure was inspired by Nassim Nicholas Taleb’s body–shoulders–tails regime model: Body (±0.66σ) — consolidation / equilibrium Shoulders (±1σ to ±2.14σ) — trending region Tails (outside of ±2.14σ) — rare, high-volatility behavior Transitions between these regimes are defined by the derivatives of the position (CDF) function : • ±1σ → shift from consolidation to trend • ±√3σ → shift from trend to exhaustion Adaptive Zone Summary Consolidation: −0.66σ to +0.66σ Support/Resistance: ±0.66σ to ±1σ Uptrend/Downtrend: ±1σ to ±√3σ Overbought/Oversold: ±√3σ to ±2.14σ Tails: outside of ±2.14σ ✦ ✦ ✦ ✦ ✦ 📌 Inverse Transformation: From σ-Space Back to RSI A final step is required to return these statistically normalized boundaries back into the familiar 0–100 RSI scale. Because the Logit transform maps RSI into an unbounded real-number domain, the inverse operation uses the hyperbolic tangent function to compress σ-space back into the bounded RSI range. RSI(n) = 50 + 50 · tanh(z / √(n − 1)) The result is a smooth, mathematically consistent conversion where the same statistical thresholds maintain identical meaning across all RSI lengths, while still expressing themselves as intuitive RSI values traders already understand. ✦ ✦ ✦ ✦ ✦ Key Features Mathematically derived adaptive zones for any RSI period Support/resistance zone identification for trend-aligned reversals Optional OHLC RSI bars/candles for intrabar zone interactions Fully customizable zone visibility and colors Statistically consistent interpretation across all markets and timeframes Inputs RSI Length — core parameter controlling zone scaling RSI Display : Line / Bar / Candle visualization modes ✦ ✦ ✦ ✦ ✦ 💡 How to Use This indicator is a framework , not a binary signal generator. Start by defining the question you want answered, e.g.: • Where is the breakout? • Is price overextended or still trending? • Is the correction ending, or is trend reversing? Then: Choose the RSI length that matches your timeframe Observe which adaptive zone price is interacting with Interpret market behavior accordingly Example: Long-Term Trend Assesment using RSI(200) A trader may ask: "Is this a long term top?" Unlikely, because RSI(200) holds above Resistance zone , therefore the trend remains strong. ✦ ✦ ✦ ✦ ✦ 👉 Practical tip: If you used to overlay weekly RSI(14) on a daily chart (getting a line that waits 5 sessions to recalculate), you can now read the same long-horizon state continuously : set RSI(70) on the daily chart (~14 weeks × 5 days/week = 70 days) and let the adaptive zones update every bar . Note: It won’t be numerically identical to the weekly RSI due to lookback period used, but it tracks the same regime on a standardized scale with bar-by-bar updates. ✦ ✦ ✦ ✦ ✦ Note: This framework describes statistical structure, not prediction. Use as part of a complete trading approach. Past behavior does not guarantee future outcomes. framework ≠ guaranteed signal --- Attribution & License This indicator incorporates: • Logit transformation of RSI • Variance scaling using 2/√(n−1) • Zone placement derived from Taleb’s body–shoulders–tails regime model and CDF derivatives • Inverse TANH(z) transform for mapping z-scores back into bounded RSI space Released under CC BY-NC-SA 4.0 — free for non-commercial use with credit. © AdaptiveRSI
Indicateur Pine Script®
par AdaptiveRSI
16
Hybrid Flow Master📊 Hybrid Flow Master - Professional Trading Indicator Overview Hybrid Flow Master is an advanced all-in-one trading indicator that combines Smart Money Concepts, institutional order flow analysis, and multi-timeframe confluence scoring to identify high-probability trade setups. Designed for both scalpers and swing traders across all markets (Forex, Crypto, Stocks, Indices). 🎯 Key Features 1. Intelligent Confluence System (0-100% Scoring) Proprietary scoring algorithm that weighs multiple factors Only signals when minimum confidence threshold is met Real-time probability calculations for each setup Signal quality grading: A+, A, B, C ratings 2. Smart Money Concepts (SMC) Automatic Order Block detection (bullish/bearish) Fair Value Gap (FVG) identification Market structure analysis (Higher Highs, Lower Lows) Swing high/low tracking with visual markers 3. Multi-Timeframe Analysis Higher timeframe trend filter for confluence Customizable HTF periods (1H, 4H, Daily, etc.) Prevents counter-trend trades Aligns entries with major trends 4. Volume Flow Analysis Volume spike detection with customizable thresholds Volume delta calculations (buying vs selling pressure) Institutional footprint identification Background highlighting for high-volume bars 5. Advanced Risk Management ATR-based stop loss calculation Automatic take profit levels Customizable risk/reward ratios (1:1, 1:2, 1:3+) Visual SL/TP lines on chart Position sizing guidance 6. Professional Dashboard Real-time HUD displaying: Market bias (Bullish/Bearish/Neutral) Higher timeframe trend status Current confluence percentage Volume status (Normal/High) RSI reading with color coding ATR volatility measure Signal quality grade 7. Smart Alert System Bullish confluence signals Bearish confluence signals Volume spike notifications Customizable alert messages Works with mobile app notifications 📈 What Makes It Unique? ✅ No Repainting - All signals are confirmed and final ✅ Probability-Based - Shows confidence level, not just binary signals ✅ Multi-Factor Confluence - Combines structure, volume, momentum, and HTF analysis ✅ Clean Interface - Toggle individual components on/off ✅ Works on All Timeframes - From 1-minute scalping to daily swing trading ✅ Universal Markets - Forex, Crypto, Stocks, Indices, Commodities 🎨 Customization Options Adjustable swing detection length Volume threshold settings Minimum confluence score filter Custom color schemes Dashboard position (4 corners) Show/hide individual components Risk/reward ratio adjustment ATR multiplier for stops 📊 Best Used For: ✔️ Scalping (1m - 15m charts) ✔️ Day Trading (15m - 1H charts) ✔️ Swing Trading (4H - Daily charts) ✔️ Trend Following ✔️ Reversal Trading ✔️ Breakout Trading 💡 How to Use: Add indicator to chart - Works immediately with default settings Set your timeframe - Choose your trading style Wait for signals - Green BUY or Red SELL labels with confidence % Check confluence score - Higher % = better quality setup Review dashboard - Confirm market bias and HTF trend Manage risk - Use provided SL/TP levels or adjust to your preference Set alerts - Get notified of high-probability setups ⚙️ Recommended Settings: For Scalping (1m-5m): Swing Length: 5-7 Min Confluence: 70% HTF: 15m or 1H For Day Trading (15m-1H): Swing Length: 10-15 Min Confluence: 60% HTF: 4H or Daily For Swing Trading (4H-Daily): Swing Length: 15-20 Min Confluence: 50-60% HTF: Weekly 📚 Indicator Components: ✦ Market Structure Detection ✦ Order Block Identification ✦ Fair Value Gaps (FVG) ✦ Volume Analysis ✦ RSI (14) ✦ MACD (12, 26, 9) ✦ ATR (14) ✦ Multi-Timeframe Trend ✦ Confluence Scoring Algorithm 🚀 Performance Notes: Optimized for speed and efficiency Minimal CPU usage Clean chart presentation Limited drawing objects (no chart clutter) Works on all TradingView plans ⚠️ Important Notes: This indicator is a tool to assist trading decisions, not financial advice Always use proper risk management (1-2% per trade recommended) Backtest on your preferred market and timeframe Combine with your own analysis and strategy Past performance does not guarantee future results 🔔 Alert Setup: Right-click indicator name → "Add Alert" → Choose: "Bullish Confluence Signal" for buy setups "Bearish Confluence Signal" for sell setups "Volume Spike Alert" for unusual activity 💬 Support: For questions, suggestions, or custom modifications, feel free to message me directly through TradingView.
Indicateur Pine Script®
par kariyappavinay
Regime [CHE] Regime — Minimal HTF MACD histogram regime marker with a simple rising versus falling state. Summary Regime is a lightweight overlay that turns a higher-timeframe-style MACD histogram condition into a simple regime marker on your chart. It queries an imported core module to determine whether the histogram is rising and then paints a consistent marker color based on that boolean state. The output is intentionally minimal: no lines, no panels, no extra smoothing visuals, just a repeated marker that reflects the current regime. This makes it useful as a quick context filter for other signals rather than a standalone system. Motivation: Why this design? A common problem in discretionary and systematic workflows is clutter and over-interpretation. Many regime tools draw multiple plots, which can distract from price structure. This script reduces the regime idea to one stable question: is the MACD histogram rising under a given preset and smoothing length. The core logic is delegated to a shared module to keep the indicator thin and consistent across scripts that rely on the same definition. What’s different vs. standard approaches? Reference baseline: A standard MACD histogram plotted in a separate pane with manual interpretation. Architecture differences: Uses a shared library call for the regime decision, rather than re-implementing MACD logic locally. Uses a single boolean output to drive marker color, rather than plotting histogram bars. Uses fixed marker placement at the bottom of the chart for consistent visibility. Practical effect: You get a persistent “context layer” on price without dedicating a separate pane or reading histogram amplitude. The chart shows state, not magnitude. How it works (technical) 1. The script imports `chervolino/CoreMACDHTF/2` and calls `core.is_hist_rising()` on each bar. 2. Inputs provide the source series, a preset string for MACD-style parameters, and a smoothing length used by the library function. 3. The library returns a boolean `rising` that represents whether the histogram is rising according to the library’s internal definition. 4. The script maps that boolean to a color: yellow when rising, blue otherwise. 5. A circle marker is plotted on every bar at the bottom of the chart, colored by the current regime state. Only the most recent five hundred bars are displayed to limit visual load. Notes: The exact internal calculation details of `core.is_hist_rising()` are not shown in this code. Any higher timeframe mechanics, security usage, or confirmation behavior are determined by the imported library. (Unknown) Parameter Guide Source — Selects the price series used by the library call — Default: close — Tips: Use close for consistency; alternate sources may shift regime changes. Preset — Chooses parameter preset for the library’s MACD-style configuration — Default: 3,10,16 — Trade-offs: Faster presets tend to flip more often; slower presets tend to react later. Smoothing Length — Controls smoothing used inside the library regime decision — Default: 21 — Bounds: minimum one — Trade-offs: Higher values typically reduce noise but can delay transitions. (Library behavior: Unknown) Reading & Interpretation Yellow markers indicate the library considers the histogram to be rising at that bar. Blue markers indicate the library considers it not rising, which may include falling or flat conditions depending on the library definition. (Unknown) Because markers repeat on every bar, focus on transitions from one color to the other as regime changes. This tool is best read as context: it does not express strength, only direction of change as defined by the library. Practical Workflows & Combinations Trend following: Use yellow as a condition to allow long-side entries and blue as a condition to allow short-side entries, then trigger entries with your primary setup such as structure breaks or pullback patterns. (Optional) Exits and stops: Consider tightening management after a color transition against your position direction, but do not treat a single flip as an exit signal without price-based confirmation. (Optional) Multi-asset and multi-timeframe: Keep `Source` consistent across assets. Use the slower preset when instruments are noisy, and the faster preset when you need earlier context shifts. The best transferability depends on the imported library’s behavior. (Unknown) Behavior, Constraints & Performance Repaint and confirmation: This script itself uses no forward-looking indexing and no explicit closed-bar gating. It evaluates on every bar update. Any repaint or confirmation behavior may come from the imported library. If the library uses higher timeframe data, intrabar updates can change the state until the higher timeframe bar closes. (Unknown) security and HTF: Not visible here. The library name suggests HTF behavior, but the implementation is not shown. Treat this as potentially higher-timeframe-driven unless you confirm the library source. (Unknown) Resources: No loops, no arrays, no heavy objects. The plotting is one marker series with a five hundred bar display window. Known limits: This indicator does not convey histogram magnitude, divergence, or volatility context. A binary regime can flip in choppy phases depending on preset and smoothing. Sensible Defaults & Quick Tuning Starting point: Source: close Preset: 3,10,16 Smoothing Length: 21 Tuning recipes: Too many flips: choose the slower preset and increase smoothing length. Too sluggish: choose the faster preset and reduce smoothing length. Regime changes feel misaligned with your entries: keep the preset, switch the source back to close, and tune smoothing length in small steps. What this indicator is—and isn’t This is a minimal regime visualization and a context filter. It is not a complete trading system, not a risk model, and not a prediction engine. Use it together with price structure, execution rules, and position management. The regime definition depends on the imported library, so validate it against your market and timeframe before relying on it. 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 MACD HTF Hardcoded
Indicateur Pine Script®
par chervolino
Market Breadth - [JTCAPITAL]Market Breadth - is a comprehensive crypto market strength and sentiment indicator designed to visualize the overall bullish or bearish alignment across 40 major cryptocurrencies. By combining multi-asset Exponential Moving Average (EMA) comparisons and smoothing techniques, it offers a clean, aggregated view of the broader market trend—helping traders quickly assess whether the market is dominated by bullish momentum or bearish pressure. The indicator works by calculating in the following steps: Symbol Selection and Data Retrieval The script monitors 40 leading cryptocurrencies based on Market Cap. Each asset’s daily close price is requested using a 1D timeframe. This ensures that every data point reflects the same temporal resolution, allowing the indicator to evaluate global crypto strength rather than individual token volatility. EMA Comparison per Asset For each asset, two Exponential Moving Averages (EMAs) are calculated: A short-term EMA with period emalength (default 10). A long-term EMA with period emalength2 (default 20). Each coin receives a score of +1 when the short-term EMA is greater than the long-term EMA (indicating bullish structure), or -1 when it is below (indicating bearish structure). This binary scoring system effectively converts individual price action into a directional sentiment measure. Market Breadth Aggregation All 40 individual scores are summed into a single composite value called scores . If many assets have bullish EMA alignment, the total score becomes strongly positive. If the majority show bearish alignment, the total score turns negative. This step transforms scattered price data into one unified market breadth metric—quantifying how many assets participate in the same directional trend. Smoothing the Breadth Line To reduce short-term noise and isolate trend direction, the aggregated score is smoothed using an EMA of length = smoothlen (default 15). The resulting smoothed line helps identify sustained shifts in collective sentiment rather than temporary fluctuations. Visualization and Color Coding When scores > 0 , the market breadth is bullish and the histogram is colored blue. When scores < 0 , the breadth turns bearish and the histogram is purple. The same logic applies to the smoothed line and background color, offering an instant visual cue of market mood transitions. Buy and Sell Conditions: The indicator itself does not trigger direct buy/sell signals but rather acts as a market regime filter . Traders can use it as follows: Buy Filter: When the smoothed value is above zero and rising, the majority of assets confirm an uptrend — this favors long setups or trend continuation entries. Sell Filter: When the smoothed value is below zero and falling, bearish alignment dominates — ideal for short setups or defensive risk management. Optional filters could include combining this with RSI or volume-weighted momentum indicators to confirm breadth-based reversals. Features and Parameters: emalength – Defines the short-term EMA length used for individual asset trend detection (default 10). emalength2 – Defines the long-term EMA length (default 20). smoothlen – Defines the smoothing EMA length for the total market breadth line (default 15). 40 asset inputs – User-editable symbols allow full customization of which cryptos are tracked. Dynamic color backgrounds – Visual distinction between bullish and bearish phases. Specifications: Exponential Moving Average (EMA) EMA is a type of moving average that places more weight on recent price data, responding faster to market changes compared to SMA. By comparing a short-term and long-term EMA, the indicator captures momentum shifts across each asset individually. The crossover logic (EMA10 > EMA20) signals bullish conditions, while the opposite indicates bearish momentum. Market Breadth Market Breadth quantifies how many assets are participating in a directional move. Instead of tracking a single coin’s trend, breadth analysis measures collective sentiment. When most coins’ short-term EMAs are above long-term EMAs, the market shows healthy bullish breadth. Conversely, when most are below, weakness dominates. Smoothing (EMA on Scores) After summing the breadth score, the result is smoothed with an additional EMA to mitigate the inherent volatility caused by individual coin reversals. This second-level smoothing transforms raw fluctuations into a readable, trend-consistent curve. Color Visualization Visual cues are integral for intuitive interpretation. Blue Shades: Indicate bullish alignment and collective upward momentum. Purple Shades: Indicate bearish conditions and potential risk-off phases. The background tint reinforces visual clarity even when the indicator is overlaid on price charts. Background Logic By applying the same color logic to the chart’s background, users can instantly recognize the prevailing market phase. Use Cases As a trend confirmation filter for other indicators (e.g., trade only in the direction of positive breadth). As a divergence tool : when price rises but breadth weakens, it may signal a topping market. As a macro sentiment monitor : perfect for assessing when the crypto market as a whole transitions from bearish to bullish structure. Summary “ Market Breadth - ” transforms the chaotic price movements of 40 cryptocurrencies into a single, powerful visual representation of overall market health. By merging EMA cross analysis with market-wide aggregation and smoothing , it provides traders with a deep understanding of when bullish or bearish forces dominate the ecosystem. It’s a clean, data-driven approach to identifying shifts in crypto market sentiment — a perfect companion for trend-following, macro analysis, and timing portfolio exposure. Enjoy!
Indicateur Pine Script®
par JTCapitalNL
MA SMART Angle ### 📊 WHAT IS MA SMART ANGLE? **MA SMART Angle** is an advanced momentum and trend detection indicator that analyzes the angles (slopes) of multiple moving averages to generate clear, non-repainting BUY and SELL signals. **Original Concept Credit:** This indicator builds upon the "MA Angles" concept originally created by **JD** (also known as Duyck). The core angle calculation methodology and Jurik Moving Average (JMA) implementation by **Everget** are preserved from the original open-source work. The angle calculation formula was contributed by **KyJ**. This enhanced version is published with respect to the open-source nature of the original indicator. Original indicator reference: "ma angles - JD" by Duyck --- ## 🎯 ORIGINALITY & VALUE PROPOSITION ### **What Makes This Different from the Original:** While the original "MA Angles" by **JD** provided excellent angle visualization, it lacked actionable entry signals. **MA SMART Angle** addresses this by adding: **1. Clear Entry/Exit Signals** - Explicit BUY/SELL arrows based on angle crossovers, momentum confirmation, and MA alignment - No guessing when to enter trades - the indicator tells you exactly when conditions align **2. Non-Repainting Logic** - All signals use confirmed historical data (shifted by 2 bars minimum) - Critical for backtesting reliability and live trading confidence - Original indicator could repaint signals on current bar **3. Dual Signal System** - **Simple Mode:** More frequent signals based on angle crossovers + momentum (for active traders) - **Strict Mode:** Requires full multi-MA alignment + momentum confirmation (for conservative traders) - Adaptable to different trading styles and risk tolerances **4. Smart Signal Filtering** - **Anti-spam cooldown:** Prevents duplicate signals within configurable bar count - **No-trade zone detection:** Filters out low-conviction sideways markets automatically - **Multi-timeframe MA alignment:** Ensures all moving averages agree on direction before signaling **5. Enhanced Visualization** - Large, clear BUY/SELL arrows with descriptive labels - Color-coded backgrounds for market states (trending vs. ranging) - Momentum histogram showing acceleration/deceleration in real-time - Live status table displaying trend strength, angle value, momentum, and MA alignment **6. Professional Alert System** - Four distinct alert conditions: BUY Signal, SELL Signal, Strong BUY, Strong SELL - Enables automated trade notifications and strategy integration **7. Modified MA Periods** - Original used EMA(27), EMA(83), EMA(278) - Enhanced version uses faster EMA(3), EMA(8), EMA(13) for more responsive signals - Better suited for modern volatile markets and shorter timeframes --- ## 📐 HOW IT WORKS - TECHNICAL EXPLANATION ### **Core Methodology:** The indicator calculates angles (slopes) for five key moving averages: - **JMA (Jurik Moving Average)** - Smooth, lag-reduced trend line (original implementation by **Everget**) - **JMA Fast** - Responsive momentum indicator with higher power parameter - **MA27 (EMA 3)** - Primary fast-moving average for signal generation - **MA83 (EMA 8)** - Medium-term trend confirmation - **MA278 (EMA 13)** - Slower trend filter ### **Angle Calculation Formula (by KyJ):** ``` angle = arctan((MA - MA ) / ATR(14)) × (180 / π) ``` **Why ATR normalization?** - Makes angles comparable across different instruments (forex, stocks, crypto) - Makes angles comparable across different timeframes - Accounts for volatility - a 10-point move in different assets has different significance **Angle Interpretation:** - **> 15°** = Strong trend (momentum accelerating) - **0° to 15°** = Weak trend (momentum present but moderate) - **-2° to +2°** = No-trade zone (sideways/choppy market) - **< -15°** = Strong downtrend ### **Signal Generation Logic:** #### **BUY Signal Conditions:** 1. MA27 angle crosses above 0° (upward momentum initiates) 2. All three EMAs (3, 8, 13) pointing upward (trend alignment confirmed) 3. Momentum is positive for 2+ bars (acceleration, not deceleration) 4. Angle exceeds minimum threshold (not in no-trade zone) 5. Cooldown period passed (prevents signal spam) #### **SELL Signal Conditions:** 1. MA27 angle crosses below 0° (downward momentum initiates) 2. All three EMAs pointing downward (downtrend alignment) 3. Momentum is negative for 2+ bars 4. Angle below negative threshold (not in no-trade zone) 5. Cooldown period passed #### **Strong BUY+ / SELL+ Signals:** Additional entry opportunities when JMA Fast crosses JMA Slow while maintaining strong directional angle - indicates momentum acceleration within established trend. --- ## 🔧 HOW TO USE ### **Recommended Settings by Trading Style:** **Scalpers / Day Traders:** - Signal Type: **Simple** - Minimum Angle: **3-5°** - Cooldown Bars: **3-5 bars** - Timeframes: 1m, 5m, 15m **Swing Traders:** - Signal Type: **Strict** - Minimum Angle: **7-10°** - Cooldown Bars: **8-12 bars** - Timeframes: 1H, 4H, Daily **Position Traders:** - Signal Type: **Strict** - Minimum Angle: **10-15°** - Cooldown Bars: **15-20 bars** - Timeframes: Daily, Weekly ### **Parameter Descriptions:** **1. Source** (default: OHLC4) - Price data used for MA calculations - OHLC4 provides smoothest angles - Close is more responsive but noisier **2. Threshold for No-Trade Zones** (default: 2°) - Angles below this are considered sideways/ranging - Increase for stricter filtering of choppy markets - Decrease to allow signals in quieter trending periods **3. Signal Type** (Simple vs. Strict) - **Simple:** Angle crossover OR (trend + momentum) - **Strict:** Angle crossover AND all MAs aligned AND momentum confirmed - Start with Simple, switch to Strict if too many false signals **4. Minimum Angle for Signal** (default: 5°) - Only generate signals when angle exceeds this threshold - Higher values = stronger trends required - Lower values = more sensitive to momentum changes **5. Cooldown Bars** (default: 5) - Minimum bars between consecutive signals - Prevents spam during volatile chop - Scale with your timeframe (higher TF = more bars) **6. Color Bars** (default: true) - Colors chart bars based on signal state - Green = bullish conditions, Red = bearish conditions - Can disable if you prefer clean price bars **7. Background Colors** - **Yellow background** = No-trade zone (low angle, ranging market) - **Green flash** = BUY signal generated - **Red flash** = SELL signal generated - All customizable or can be disabled --- ## 📊 INTERPRETING THE INDICATOR ### **Visual Elements:** **Main Chart Window:** - **Thick Lime/Fuchsia Line** = MA27 angle (primary signal line) - **Medium Green/Red Line** = MA83 angle (trend confirmation) - **Thin Green/Red Line** = MA278 angle (slow trend filter) - **Aqua/Orange Line** = JMA Fast (momentum detector) - **Green/Red Area** = JMA slope (overall trend context) - **Blue/Purple Histogram** = Momentum (angle acceleration/deceleration) **Signal Arrows:** - **Large Green ▲ "BUY"** = Primary buy signal (all conditions met) - **Small Green ▲ "BUY+"** = Strong momentum buy (JMA fast cross) - **Large Red ▼ "SELL"** = Primary sell signal (all conditions met) - **Small Red ▼ "SELL+"** = Strong momentum sell (JMA fast cross) **Status Table (Top Right):** - **Angle:** Current MA27 angle in degrees - **Trend:** Classification (STRONG UP/DOWN, UP/DOWN, FLAT) - **Momentum:** Acceleration state (ACCEL UP/DN, Up/Down) - **MAs:** Alignment status (ALL UP/DOWN, Mixed) - **Zone:** Trading zone status (ACTIVE vs. NO TRADE) - **Last:** Bars since last signal ### **Trading Strategies:** **Strategy 1: Pure Signal Following** - Enter LONG on BUY signal - Exit on SELL signal - Use stop-loss at recent swing low/high - Works best on trending instruments **Strategy 2: Confirmation with Price Action** - Wait for BUY signal + bullish candlestick pattern - Wait for SELL signal + bearish candlestick pattern - Increases win rate by filtering premature signals - Recommended for beginners **Strategy 3: Momentum Acceleration** - Use BUY+/SELL+ signals for adding to positions - Only take these in direction of primary signal - Scalp quick moves during momentum spikes - For experienced traders **Strategy 4: Mean Reversion in No-Trade Zones** - When status shows "NO TRADE", fade extremes - Wait for angle to exit no-trade zone for reversal - Contrarian approach for range-bound markets - Requires tight stops --- ## ⚠️ LIMITATIONS & DISCLAIMERS **What This Indicator DOES:** ✅ Measures momentum direction and strength via angle analysis ✅ Generates signals when multiple conditions align ✅ Filters out low-conviction sideways markets ✅ Provides visual clarity on trend state **What This Indicator DOES NOT:** ❌ Predict future price movements with certainty ❌ Guarantee profitable trades (no indicator can) ❌ Work equally well on all instruments/timeframes ❌ Replace proper risk management and position sizing **Known Limitations:** - **Lagging Nature:** Like all moving averages, signals occur after momentum begins - **Whipsaw Risk:** Can generate false signals in volatile, directionless markets - **Optimization Required:** Parameters need adjustment for different assets - **Not a Complete System:** Should be combined with risk management, position sizing, and other analysis **Best Performance Conditions:** - Strong trending markets (crypto bull runs, stock breakouts) - Liquid instruments (major forex pairs, large-cap stocks) - Appropriate timeframe selection (match to trading style) - Used alongside support/resistance and volume analysis --- ## 🔔 ALERT SETUP The indicator includes four alert conditions: **1. BUY SIGNAL** - Message: "MA SMART Angle: BUY SIGNAL! Angle crossed up with momentum" - Use for: Primary long entries **2. SELL SIGNAL** - Message: "MA SMART Angle: SELL SIGNAL! Angle crossed down with momentum" - Use for: Primary short entries or long exits **3. Strong BUY** - Message: "MA SMART Angle: Strong BUY momentum - JMA fast crossed up" - Use for: Adding to longs or aggressive entries **4. Strong SELL** - Message: "MA SMART Angle: Strong SELL momentum - JMA fast crossed down" - Use for: Adding to shorts or aggressive exits **Setting Up Alerts:** 1. Right-click indicator → "Add Alert on MA SMART Angle" 2. Select desired condition from dropdown 3. Choose notification method (popup, email, webhook) 4. Set alert expiration (typically "Once Per Bar Close") --- ## 📚 EDUCATIONAL VALUE This indicator serves as an excellent learning tool for understanding: **1. Angle-Based Momentum Analysis** - Traditional indicators show MA crossovers - This shows the *rate of change* (velocity) of MAs - Teaches traders to think in terms of momentum acceleration **2. Multi-Timeframe Confirmation** - Shows how fast, medium, and slow MAs interact - Demonstrates importance of trend alignment - Helps develop patience for high-probability setups **3. Signal Quality vs. Quantity Tradeoff** - Simple mode = more signals, more noise - Strict mode = fewer signals, higher quality - Teaches discretionary filtering skills **4. Market State Recognition** - Visual distinction between trending and ranging markets - Helps traders avoid trading choppy conditions - Develops "market context" awareness --- ## 🔄 DIFFERENCES FROM OTHER MA INDICATORS **vs. Traditional MA Crossovers:** - Measures momentum (angle) rather than just price crossing MA - Provides earlier signals as angles change before price crosses - Filters better for sideways markets using no-trade zones **vs. MACD:** - Uses multiple MAs instead of just two - ATR normalization makes it universal across instruments - Visual angle representation more intuitive than histogram **vs. Supertrend:** - Not based on ATR bands but on MA slope analysis - Provides graduated strength indication (not just binary trend) - Less prone to whipsaw in low volatility **vs. Original "MA Angles" by JD:** - Adds explicit entry/exit signals (original had none) - Implements no-repaint logic for reliability - Includes signal filtering and quality controls - Provides dual signal systems (Simple/Strict) - Enhanced visualization and status monitoring - Uses faster MA periods (3/8/13 vs 27/83/278) for modern markets --- ## 📖 CODE STRUCTURE (for Pine Script learners) This indicator demonstrates: **Advanced Pine Script Techniques:** - Custom function implementation (JMA, angle calculation) - Var declarations for stateful tracking - Table creation for HUD display - Multi-condition signal logic - Alert system integration - Proper use of historical references for no-repaint **Code Organization:** - Modular function definitions (JMA, angle) - Clear separation of concerns (inputs, calculations, plotting, alerts) - Extensive commenting for maintainability - Best practices for Pine Script v5 **Learning Resources:** - Study the JMA function to understand adaptive smoothing - Examine angle calculation for ATR normalization technique - Review signal logic for multi-condition confirmation patterns - Analyze anti-spam filtering for state management The code is open-source - feel free to study, modify, and improve upon it! --- ## 🙏 CREDITS & ATTRIBUTION **Original Concepts:** - **"ma angles - JD" by JD (Duyck)** - Core angle calculation methodology and indicator concept Original open-source indicator on TradingView Community Scripts - **JMA (Jurik Moving Average) implementation by Everget** - Smooth, low-lag moving average function Acknowledged in original JD indicator code - **Angle Calculation formula by KyJ** - Mathematical formula for converting MA slope to degrees using ATR normalization Acknowledged in original JD indicator code comments **Enhancements in This Version:** - Signal generation logic - Original implementation for this indicator - No-repaint confirmation system - Original implementation - Dual signal modes (Simple/Strict) - Original implementation - Visual enhancements and status table - Original implementation - Alert system and signal filtering - Original implementation - Modified MA periods (3/8/13 instead of 27/83/278) - Optimization for modern markets **Open Source Philosophy:** This indicator follows the open-source spirit of TradingView and the Pine Script community. The original "ma angles - JD" by JD (Duyck) was published as open-source, enabling this enhanced version. Similarly, this code is published as open-source to allow further community improvements. --- ## ⚡ QUICK START GUIDE **For New Users:** 1. Add indicator to chart 2. Start with default settings (Simple mode) 3. Wait for BUY signal (green arrow) 4. Observe how price behaves after signal 5. Check status table to understand market state 6. Adjust parameters based on your instrument/timeframe **For Experienced Traders:** 1. Switch to Strict mode for higher quality signals 2. Increase cooldown bars to reduce frequency 3. Raise minimum angle threshold for stronger trends 4. Combine with your existing strategy for confirmation 5. Set up alerts for desired signal types 6. Backtest on your preferred instruments --- ## 🎓 RECOMMENDED COMBINATIONS **Works Well With:** - **Volume Analysis:** Confirm signals with volume spikes - **Support/Resistance:** Take signals near key levels - **RSI/Stochastic:** Avoid overbought/oversold extremes - **ATR:** Size positions based on volatility - **Price Action:** Wait for candlestick confirmation **Complementary Indicators:** - Order Flow / Footprint (for institutional confirmation) - Volume Profile (for identifying value areas) - VWAP (for intraday mean reversion reference) - Fibonacci Retracements (for target setting) --- ## 📈 PERFORMANCE EXPECTATIONS **Realistic Win Rates:** - Simple Mode: 45-55% (higher frequency, moderate accuracy) - Strict Mode: 55-65% (lower frequency, higher accuracy) - Combined with price action: 60-70% **Best Asset Classes:** 1. **Cryptocurrencies** (strong trends, clear signals) 2. **Forex Major Pairs** (smooth price action, good angles) 3. **Large-Cap Stocks** (trending behavior, liquid) 4. **Index Futures** (trending instruments) **Challenging Conditions:** - Low volatility consolidation periods - News-driven erratic movements - Thin/illiquid instruments - Counter-trending markets --- ## 🛡️ RISK DISCLAIMER **IMPORTANT LEGAL NOTICE:** This indicator is for **educational and informational purposes only**. It is **NOT financial advice** and does not constitute a recommendation to buy or sell any financial instrument. **Trading Risks:** - Trading carries substantial risk of loss - Past performance does not guarantee future results - No indicator can predict market movements with certainty - You can lose more than your initial investment (especially with leverage) **User Responsibilities:** - Conduct your own research and due diligence - Understand the instruments you trade - Never risk more than you can afford to lose - Use proper position sizing and risk management - Consider consulting a licensed financial advisor **Indicator Limitations:** - Signals are based on historical data only - No guarantee of accuracy or profitability - Parameters must be optimized for your specific use case - Results vary significantly by market conditions By using this indicator, you acknowledge and accept all trading risks. The author is not responsible for any financial losses incurred through use of this indicator. --- ## 📧 SUPPORT & FEEDBACK **Found a bug?** Please report it in the comments with: - Chart symbol and timeframe - Parameter settings used - Description of unexpected behavior - Screenshot if possible **Have suggestions?** Share your ideas for improvements! **Enjoying the indicator?** Leave a like and follow for updates!
Indicateur Pine Script®
par Smart-Day-Trader
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion . Core Architecture Why These Components Are Combined: The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention. The Four Trading Agents 1. Spoofing Detector Agent 🎭 Detects iceberg orders through persistent volume at similar price levels over 5 bars Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average) Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model) Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation Best Markets: Consolidations, institutional trading windows, low-liquidity hours 2. Exhaustion Detector Agent ⚡ Calculates RSI divergence between price movement and momentum indicator over 5-bar window Detects VWAP exhaustion (price at 2σ bands with declining volume) Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure Signal Logic: Counter-trend—enters when momentum extreme shows weakness Best Markets: Trending markets reaching climax points, over-extended moves 3. Liquidity Void Detector Agent 💧 Measures Bollinger Band squeeze (width <60% of 50-period average) Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR) Signal Logic: Breakout anticipation—enters after liquidity grab but before main move Best Markets: Range-bound pre-breakout, volatility compression zones 4. Mean Reversion Agent 📊 Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ) Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model) Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability) Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments Adaptive Selection: Multi-Armed Bandit System The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance: Thompson Sampling (Default - Recommended): Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent) Balances exploration (trying underused agents) vs. exploitation (using proven winners) Each agent's win/loss history informs its selection probability Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation UCB1 (Upper Confidence Bound): Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls) Deterministic algorithm favoring agents with high uncertainty (potential upside) More conservative than Thompson Sampling Epsilon-Greedy: Exploits best-performing agent (1-ε)% of the time Explores randomly ε% of the time (default 10%, configurable 1-50%) Simple, transparent, easily tuned via epsilon parameter Gradient Bandit: Uses softmax probability distribution over agent preference weights Updates weights via gradient ascent based on rewards Best for Blend mode where all agents contribute Selection Modes: Switch Mode: Uses only the selected agent's signal (clean, decisive) Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified) Lock Agent Feature: Optional manual override to force one specific agent Useful after identifying which agent dominates your specific instrument Only applies in Switch mode Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion Memory System Dual-Layer Architecture: Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50) Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars) Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20% Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds) How Memory Works: Agent generates signal → outcome tracked after 8 bars (performance horizon) Result stored in short-term memory (win = 1.0, loss = 0.0) Short-term average influences agent's future scores (positive feedback loop) After threshold met (default 10 results), episode averaged into long-term storage Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost Market Microstructure Analysis These advanced metrics quantify institutional order flow dynamics: Order Flow Toxicity (Simplified VPIN): Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol) Detects informed trading activity (institutional players with non-public information) Values >0.4 indicate "toxic flow" (informed traders active) Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification Price Impact Analysis (Simplified Kyle's Lambda): Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10) Low values = large orders with minimal price impact ( stealth accumulation ) High values = retail-dominated moves with high slippage Lite Approximation: Uses simplified denominator instead of regression-based signed order flow Market Randomness (Entropy Analysis): Counts unique price changes over 20 bars / 20 Measures market predictability High entropy (>0.6) = human-driven, chaotic price action Low entropy (<0.25) = algorithmic trading dominance (predictable patterns) Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x)) Order Clustering (Simplified Hawkes Process): Tracks self-exciting event intensity (coordinated order activity) Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average High intensity (>0.7) indicates clustering (potential spoofing/accumulation) Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE Signal Generation Process Multi-Stage Validation: Stage 1: Agent Scoring Each agent calculates internal score based on its detection criteria Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier) Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0) Stage 2: Memory Boost Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance) Successful agents get amplified, failing agents get dampened Stage 3: Bandit Selection/Blending If Adaptive Mode ON: Switch: Bandit selects single best agent, uses only its signal Blend: All agents combined using softmax-weighted confidence scores If Adaptive Mode OFF: Traditional consensus voting with confidence-squared weighting Signal fires when consensus exceeds threshold (default 70%) Stage 4: Confirmation Filter Raw signal must repeat for consecutive bars (default 3, configurable 2-4) Minimum confidence threshold: 0.25 (25%) enforced regardless of mode Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2 Stage 5: Cooldown Enforcement Minimum bars between signals (default 10, configurable 5-15) Prevents over-trading during choppy conditions Stage 6: Performance Tracking After 8 bars (performance horizon), signal outcome evaluated Win = price moved in signal direction, Loss = price moved against Results fed back into memory and bandit statistics Trading Modes (Presets) Pre-configured parameter sets: Conservative: 85% consensus, 4 confirmations, 15-bar cooldown Expected: 60-70% win rate, 3-8 signals/week Best for: Swing trading, capital preservation, beginners Balanced: 70% consensus, 3 confirmations, 10-bar cooldown Expected: 55-65% win rate, 8-15 signals/week Best for: Day trading, most traders, general use Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown Expected: 50-58% win rate, 15-30 signals/week Best for: Scalping, high-frequency trading, active management Elite: 75% consensus, 3 confirmations, 12-bar cooldown Expected: 58-68% win rate, 5-12 signals/week Best for: Selective trading, high-conviction setups Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown Expected: Varies based on learning Best for: Experienced users leveraging bandit system How to Use 1. Initial Setup (5 Minutes): Select Trading Mode matching your style (start with Balanced) Enable Adaptive Learning (recommended for automatic agent selection) Choose Thompson Sampling algorithm (best all-around performance) Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume) 2. Agent Tuning (Optional): Adjust Agent Sensitivity multipliers (0.5-2.0): <0.8 = Highly selective (fewer signals, higher quality) 0.9-1.2 = Balanced (recommended starting point) 1.3 = Aggressive (more signals, lower individual quality) Monitor dashboard for 20-30 signals to identify dominant agent If one agent consistently outperforms, consider using Lock Agent feature 3. Bandit Configuration (Advanced): Blend Temperature (0.1-2.0): 0.3 = Sharp decisions (best agent dominates) 0.5 = Balanced (default) 1.0+ = Smooth (equal weighting, democratic) Memory Decay (0.8-0.99): 0.90 = Fast adaptation (volatile markets) 0.95 = Balanced (most instruments) 0.97+ = Long memory (stable trends) 4. Signal Interpretation: Green triangle (▲): Long signal confirmed Red triangle (▼): Short signal confirmed Dashboard shows: Active agent (highlighted row with ► marker) Win rate per agent (green >60%, yellow 40-60%, red <40%) Confidence bars (█████ = maximum confidence) Memory size (short-term buffer count) Colored zones display: Entry level (current close) Stop-loss (1.5× ATR) Take-profit 1 (2.0× ATR) Take-profit 2 (3.5× ATR) 5. Risk Management: Never risk >1-2% per signal (use ATR-based stops) Signals are entry triggers, not complete strategies Combine with your own market context analysis Consider fundamental catalysts and news events Use "Confirming" status to prepare entries (not to enter early) 6. Memory Persistence (Optional): After 50-100 trades, check Memory Export Panel Record displayed alpha/beta/weight values for each agent Record VPIN and Kyle threshold values Enable "Restore From Memory" and input saved values to continue learning Useful when switching timeframes or restarting indicator Visual Components On-Chart Elements: Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend) Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers) Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR) Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal) Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets Signal Markers: Triangle up/down at validated entry points Dashboard (Configurable Position & Size): Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear) Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus) Agent Performance Table: Real-time win%, confidence, and memory stats Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled) Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress Memory Panel (Configurable Position & Size): Live Parameter Export: Alpha, beta, and weight values per agent Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold Save Reminder: Visual indicator if parameters should be recorded What Makes This Original This script's originality lies in three key innovations: 1. Genuine Meta-Learning Framework: Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning. 2. Episodic Memory Architecture with Transfer Learning: The dual-layer memory system mimics human learning patterns: Short-term memory captures recent performance (recency bias) Long-term memory preserves historical patterns (experience) Automatic transfer mechanism consolidates knowledge Memory boost creates positive feedback loops (successful strategies become stronger) This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates. 3. Institutional Microstructure Integration: Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis. Mashup Justification: The four agents are combined specifically for risk diversification across failure modes: Spoofing Detector: Prevents false breakout losses from manipulation Exhaustion Detector: Prevents chasing extended trends into reversals Liquidity Void: Exploits volatility compression (different regime than trending) Mean Reversion: Provides mathematical anchoring when patterns fail The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals. Why "ML-lite"? Simplifications and Approximations This is the "lite" version due to necessary simplifications for Pine Script execution: 1. Simplified VPIN Calculation: Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume) Impact: May misclassify volume during ranging/choppy markets; works best in directional moves 2. Pseudo-Random Sampling: Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100 Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection 3. Hawkes Process Approximation: Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event) Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments 4. Kyle's Lambda Simplification: Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals 5. Entropy Calculation: Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude This Implementation: Simple ratio of unique price changes to total observations (variety measure) Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape 6. Memory System Constraints: Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking 7. Limited Feature Engineering: Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations 8. Single-Instrument Data: Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes This Implementation: Only OHLCV data from displayed instrument Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets 9. Fixed Performance Horizon: Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement This Implementation: Fixed 8-bar evaluation window Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach Performance Impact Summary: These simplifications make the script: ✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations ✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers ✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models) ✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint ⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations ⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows ⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized When to Upgrade to Full Implementation: Consider professional Python/C++ versions with institutional data feeds if: Trading with >$100K capital where precision differences materially impact returns Operating in microsecond-competitive environments (HFT, market making) Requiring regulatory-grade audit trails and reproducibility Backtesting with tick-level precision for strategy validation Need true real-time adaptation with neural network-based learning For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact. Technical Notes All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap ) VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above) Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling No repainting: All calculations use confirmed bar data (no forward-looking) Maximum lookback: 500 bars (set via max_bars_back parameter) Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed) Confidence threshold: Minimum 0.25 (25%) enforced on all signals Memory arrays: Dynamic sizing with FIFO queue management Limitations and Disclaimers Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty. Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context. Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms. Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts. Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets. No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss. Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics. Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes. Recommended Settings Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning) Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices) Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable) Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens) Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0) After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent Alert Configuration The script includes built-in alert conditions: Long Signal: Fires when validated long entry confirmed Short Signal: Fires when validated short entry confirmed Alerts fire once per bar (after confirmation requirements met) Set alert to "Once Per Bar Close" for reliability Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Indicateur Pine Script®
par DskyzInvestments
9
Squeeze Go Momentum Pro [KingThies] █ OVERVIEW The Squeeze Momentum Pro indicator identifies volatility compression phases and breakout opportunities by comparing Bollinger Bands to Keltner Channels. When price consolidates (squeeze), the bands contract inside the channels, signaling an imminent breakout. The momentum histogram shows directional bias, helping traders anticipate which way price will move when the squeeze releases. This indicator displays in a separate panel below the price chart, providing clear visual signals without cluttering price action. █ KEY FEATURES Momentum Histogram The histogram is the primary visual element, displaying momentum strength and direction with four distinct color states: • Dark Green (#00C853) — Strong bullish momentum that is increasing. This signals strengthening upward pressure and potential continuation. • Light Green (#26A69A) — Bullish momentum that is decreasing. Price remains in bullish territory but upward force is weakening. • Dark Red (#D32F2F) — Strong bearish momentum that is increasing. This signals strengthening downward pressure and potential continuation. • Light Red (#EF5350) — Bearish momentum that is decreasing. Price remains in bearish territory but downward force is weakening. The color intensity provides immediate feedback on momentum strength and trend health. Squeeze State Indicator Colored dots on the zero line communicate the current volatility state: • Orange Dots — Squeeze is ON. Bollinger Bands have contracted inside Keltner Channels, indicating consolidation and low volatility. A breakout is building and traders should prepare for directional movement. • Green Dots — Squeeze is OFF. Bollinger Bands have expanded outside Keltner Channels, indicating active momentum and higher volatility. Price is moving with conviction in the current direction. • Gray Dots — Neutral state. The bands are transitioning between squeeze states. Release Triangles Triangle shapes mark the exact bar when a squeeze releases, providing precise entry timing: • Green Triangle Up — Bullish squeeze release. The squeeze has ended with positive momentum, suggesting a long setup opportunity. • Red Triangle Down — Bearish squeeze release. The squeeze has ended with negative momentum, suggesting a short setup opportunity. Information Panel A compact dashboard in the top-right corner displays real-time trading intelligence: • Squeeze Status — Current state: ON, OFF, or NEUTRAL with color coding • Momentum Direction — Current bias: BULL or BEAR • Momentum Value — Precise numerical reading of momentum strength • Trading Signal — Actionable status: LONG SETUP, SHORT SETUP, WAIT, or MONITOR Configurable Parameters All calculation inputs are adjustable to match your trading style and timeframe: • BB Length — Bollinger Bands period (default: 20) • BB StdDev — Bollinger Bands standard deviation multiplier (default: 2.0) • KC Length — Keltner Channels period (default: 20) • KC ATR Multiplier — Keltner Channels range multiplier (default: 1.5) • Momentum Length — Linear regression period for momentum calculation (default: 20) Alert System Four alert conditions notify you of critical trading opportunities: • Bullish Squeeze Release — Squeeze has released with bullish momentum, indicating a potential long entry • Bearish Squeeze Release — Squeeze has released with bearish momentum, indicating a potential short entry • Squeeze Started — Volatility compression detected, prepare for upcoming breakout • Squeeze Ended — Volatility expansion confirmed, breakout is active █ TRADING METHODOLOGY The indicator follows a clear four-step process for identifying and trading squeeze breakouts: 1 - Wait for Orange Dots . When orange dots appear on the zero line, a squeeze is building. This indicates price consolidation and declining volatility. Do not enter trades during this phase. Instead, prepare by identifying key support and resistance levels and potential breakout directions. 2 - Watch for Release Triangle . When a triangle appears, the squeeze has released and a breakout is beginning. This is your entry signal. The triangle color (green up or red down) combined with the histogram direction indicates the breakout direction. 3 - Confirm with Histogram Direction . Check the momentum histogram for directional confirmation: • Green histogram + green triangle up = Go long. Bullish momentum supports upward breakout. • Red histogram + red triangle down = Go short. Bearish momentum supports downward breakout. 4 - Monitor Momentum Intensity . Stay in the trade while histogram bars maintain their dark, intense color. When colors lighten (dark green to light green, or dark red to light red), momentum is weakening and you should consider taking profits or tightening stops. █ INTERPRETATION GUIDE Squeeze Detection Logic A squeeze occurs when Bollinger Bands contract inside Keltner Channels. This happens when: • Standard deviation of price decreases (BB narrows) • Price consolidates within a tight range • Volatility compresses to unsustainable levels The orange dots signal this condition, warning traders that explosive movement is imminent. Squeeze Release Logic A squeeze releases when Bollinger Bands expand outside Keltner Channels. This happens when: • Price volatility increases sharply • Price breaks out of consolidation • Volume typically expands (check volume separately) The green dots and release triangles signal this condition, indicating the direction and timing of the breakout. Momentum Reading The histogram uses linear regression to calculate momentum relative to the midpoint of the recent range: • Above Zero : Price is trading above the range midpoint with bullish pressure • Below Zero : Price is trading below the range midpoint with bearish pressure • Increasing Bars : Momentum is strengthening in the current direction (darker color) • Decreasing Bars : Momentum is weakening in the current direction (lighter color) █ BEST PRACTICES • Timeframe Selection — The indicator works on all timeframes but performs best on 15-minute to daily charts. Lower timeframes may produce more false signals due to noise. • Confluence Trading — Combine squeeze releases with support/resistance levels, trend lines, or other indicators for higher probability setups. • Volume Confirmation — Check that squeeze releases occur with increasing volume. Low volume breakouts are more likely to fail. • Multiple Timeframe Analysis — Check higher timeframes for overall trend direction. Trade squeeze releases that align with the larger trend. • Parameter Adjustment — Increase BB and KC lengths for smoother signals on higher timeframes. Decrease for more sensitive signals on lower timeframes. █ LIMITATIONS • The indicator does not predict breakout direction before the squeeze releases. The momentum histogram provides bias but is not definitive until the breakout occurs. • False breakouts can occur, particularly in choppy or low-volume market conditions. Always use proper risk management and stop losses. • The indicator works best in trending markets. In deeply ranging markets with no clear direction, squeeze signals may be less reliable. • Momentum calculations use linear regression which can lag during extremely fast price movements. Confirm signals with price action. █ NOTES This implementation uses linear regression for momentum calculation rather than simple moving averages, providing more responsive and accurate directional signals. The four-color histogram system gives traders nuanced feedback on momentum strength that binary color schemes cannot provide. The indicator automatically adjusts to any symbol and timeframe without modification, making it suitable for stocks, forex, crypto, and futures markets. █ CREDITS Squeeze methodology inspired by John Carter's TTM Squeeze indicator. Momentum calculation and visual design optimized for modern trading workflows.
Indicateur Pine Script®
par kingthies
1
DEMA Flow [Alpha Extract]A sophisticated trend identification system that combines Double Exponential Moving Average methodology with advanced HL median filtering and ATR-based band detection for precise trend confirmation. Utilizing dual-layer smoothing architecture and volatility-adjusted breakout zones, this indicator delivers institutional-grade flow analysis with minimal lag while maintaining exceptional noise reduction. The system's intelligent band structure with asymmetric ATR multipliers provides clear trend state classification through price position analysis relative to dynamic threshold levels. 🔶 Advanced DEMA Calculation Engine Implements double exponential moving average methodology using cascaded EMA calculations to significantly reduce lag compared to traditional moving averages. The system applies dual smoothing through sequential EMA processing, creating a responsive yet stable trend baseline that maintains sensitivity to genuine market structure changes while filtering short-term noise. // Core DEMA Framework dema(src, length) => EMA1 = ta.ema(src, length) EMA2 = ta.ema(EMA1, length) DEMA_Value = 2 * EMA1 - EMA2 DEMA_Value // Primary Calculation DEMA = dema(close, DEMA_Length) 2H 🔶 HL Median Filter Smoothing Architecture Features sophisticated high-low median filtering using rolling window analysis to create ultra-smooth trend baselines with outlier resistance. The system constructs dynamic arrays of recent DEMA values, sorts them for median extraction, and handles both odd and even window lengths for optimal smoothing consistency across all market conditions. // HL Median Filter Logic hlMedian(src, length) => window = array.new_float() for i = 0 to length - 1 array.push(window, src) array.sort(window) // Median Extraction lenW = array.size(window) median = lenW % 2 == 1 ? array.get(window, lenW / 2) : (array.get(window, lenW/2 - 1) + array.get(window, lenW/2)) / 2 // Smooth DEMA Calculation Smooth_DEMA = hlMedian(DEMA_Value, HL_Filter_Length) 🔶 ATR Band Construction Framework Implements volatility-adaptive band structure using Average True Range calculations with asymmetric multiplier configuration for optimal trend identification. The system creates upper and lower threshold bands around the smoothed DEMA baseline with configurable ATR multipliers, enabling precise trend state determination through price breakout analysis. // ATR Band Calculation atrBands(src, atr_length, upper_mult, lower_mult) => ATR = ta.atr(atr_length) Upper_Band = src + upper_mult * ATR Lower_Band = src - lower_mult * ATR // Band Generation = atrBands(Smooth_DEMA, ATR_Length, Upper_ATR_Mult, Lower_ATR_Mult) 15min 🔶 Intelligent Flow Signal Engine Generates binary trend states through band breakout detection, transitioning to bullish flow when price exceeds upper band and bearish flow when price breaches lower band. The system maintains flow state persistence until opposing band breakout occurs, providing clear trend classification without whipsaw signals during normal volatility fluctuations. 🔶 Comprehensive Visual Architecture Provides multi-dimensional flow visualization through color-coded DEMA line, trend-synchronized candle coloring, and bar color overlay for complete chart integration. The system uses institutional color scheme with neon green for bullish flow, neon red for bearish flow, and neutral gray for undefined states with configurable band visibility. 🔶 Asymmetric Band Configuration Features intelligent asymmetric ATR multiplier system with default upper multiplier of 2.1 and lower multiplier of 1.5, optimizing for market dynamics where upside breakouts often require stronger momentum confirmation than downside breaks. This configuration reduces false signals while maintaining sensitivity to genuine flow changes. 🔶 Dual-Layer Smoothing Methodology Combines DEMA's inherent lag reduction with HL median filtering to create exceptional smoothing without sacrificing responsiveness. The system first applies double exponential smoothing for initial noise reduction, then applies median filtering to eliminate outliers and create ultra-clean flow baseline suitable for high-frequency and institutional trading applications. 🔶 Alert Integration System Features comprehensive alert framework for flow state transitions with customizable notifications for bullish and bearish flow confirmations. The system provides real-time alerts on crossover events with clear directional indicators and exchange/ticker integration for multi-symbol monitoring capabilities. 🔶 Performance Optimization Framework Utilizes efficient array management with optimized median calculation algorithms and minimal variable overhead for smooth operation across all timeframes. The system includes intelligent bar indexing for median filter initialization and streamlined flow state tracking for consistent performance during extended analysis periods. 🔶 Why Choose DEMA Flow ? This indicator delivers sophisticated flow identification through dual-layer smoothing architecture and volatility-adaptive band methodology. By combining DEMA's reduced-lag characteristics with HL median filtering and ATR-based breakout zones, it provides institutional-grade flow analysis with exceptional noise reduction and minimal false signals. The system's asymmetric band structure and comprehensive visual integration make it essential for traders seeking systematic trend-following approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities for automated trading strategies.
Indicateur Pine Script®
par AlphaExtract
1
Complete DashboardPA+AI PRE/GO Trading Dashboard v0.1.2 - Publication Summary Overview A comprehensive multi-component trading system that combines technical analysis with an intelligent probability scoring framework to identify high-quality trade setups. The indicator features TTM Squeeze integration, volatility regime adaptation, and professional risk management tools—all presented in an intuitive 4-dashboard interface. Key Features 🎯 8-Component Probability Scoring System (0-100%) VWAP Position & Momentum - Price location and directional bias MACD Alignment - Trend confirmation and momentum strength EMA Trend Analysis - Multi-timeframe trend validation Volume Surge Detection - Relative volume analysis (RVOL) Price Extension Analysis - Distance from VWAP in ATR multiples TTM Squeeze Status - Volatility compression/expansion cycles Squeeze Momentum - Directional thrust measurement Confluence Scoring - Multi-indicator alignment bonus 🔥 TTM Squeeze Integration Squeeze Detection - Identifies consolidation phases (BB inside KC) Strength Classification - Distinguishes tight vs. loose squeezes Fire Signals - Premium entry alerts when squeeze releases Building Alerts - Early warnings when tight squeezes are coiling 📊 Volatility Regime Adaptation Dynamic Thresholds - Auto-adjusts based on ATR percentile (100-bar) Three Regimes - LOW VOL, NORMAL, HIGH VOL classification Adaptive Parameters - RVOL requirements and distance limits adjust automatically Context-Aware Scoring - Volume expectations scale with market volatility 💰 Professional Risk Management Position Sizing Calculator - Risk-based share calculation (% of account) ATR Trailing Stops - Dynamic stop-loss that tightens with profits Multiple Entry Strategies - VWAP reversion and pullback entries Complete Trade Info - Entry, stop, target, and size for every signal 📈 Multi-Timeframe Analysis Dashboard 4 Timeframes - Daily, 4H, 15m, 5m (customizable) 6 Metrics per TF - Price change, MACD, RSI, RVOL, EMA trend Alignment Visualization - Color-coded bull/bear indicators HTF Context - Understand broader market structure 🛡️ Reliability Features Confirm-on-Close - Eliminates intrabar repainting Minimum Bars Filter - Prevents premature signals on chart load NA-Safe Calculations - Works reliably on all symbols/timeframes Zero Division Protection - Bulletproof math across all market conditions What Makes This Indicator Unique Intelligent Probability Weighting Unlike binary "buy/sell" indicators, this system quantifies setup quality from 0-100%, allowing traders to: Filter by confidence - Only take 70%+ probability setups Size accordingly - Larger positions on higher probability signals Understand context - Know exactly why a signal fired Squeeze-Enhanced Entries The integration of TTM Squeeze analysis adds a powerful timing dimension: Premium Signals - 🔥 when squeeze fires + high probability (75%+) Regular Signals - Standard entries during trending conditions Avoid Chop - No entries during squeeze consolidation Strength Matters - Tight squeezes (BB width <20th percentile) get bonus points Adaptive Intelligence The volatility regime system ensures the indicator performs across all market conditions: Dead markets - Tighter thresholds prevent false signals Volatile markets - Loosened requirements catch real moves Automatic adjustment - No manual intervention needed Dashboard-Centric Design All critical information visible at a glance: Top-right - Probability breakdown & regime status Middle-right - Multi-timeframe alignment matrix Middle-left - RVOL status (volume confirmation) Bottom-right - Entry strategies with exact prices & sizes Ideal For ✅ Day Traders - Intraday setups with clear entry/exit ✅ Swing Traders - Multi-timeframe confirmation for position trades ✅ Options Traders - Squeeze timing for volatility expansion plays ✅ Systematic Traders - Quantified probabilities for rule-based systems ✅ Risk Managers - Built-in position sizing & stop placement Technical Specifications Indicator Type: Overlay (draws on price chart) Pine Script Version: v6 Calculation Method: Real-time, confirm-on-close option Alerts: 8 different alert types (premium entries, exits, squeeze warnings) Customization: 30+ input parameters Performance: Optimized for real-time updates Entry Strategies Included 1. VWAP Reversion Enter when price bounces off VWAP ± 0.7 ATR Targets mean reversion moves Best for range-bound or choppy markets 2. Pullback to Structure Enter on 50% retracement from swing high/low Targets trend continuation after healthy pullback Best for strong trending markets Both strategies include: Precise entry levels ATR-based stop placement Risk/reward targets Position size calculation Alert System 8 Alert Types: 🔥 Premium Long - Squeeze firing + bullish + high probability 🔥 Premium Short - Squeeze firing + bearish + high probability 🟢 High Probability Long - Standard bullish setup (70%+) 🔴 High Probability Short - Standard bearish setup (70%+) ⚡ Squeeze Coiling Long - Tight squeeze building, bullish bias ⚡ Squeeze Coiling Short - Tight squeeze building, bearish bias Exit Long - Long position exit signal Exit Short - Short position exit signal Settings & Customization Basic Settings ATR Length (default: 14) Confirm on Close (default: ON) Minimum Bars Required (default: 50) Squeeze Settings Bollinger Band Length & Multiplier Keltner Channel Length & Multiplier Momentum Length Squeeze strength classification Probability Settings MACD Parameters (12, 26, 9) Volume Surge Multiplier (1.5x) High/Medium Probability Thresholds (70%/50%) Volatility Regime Adaptation (ON/OFF) Risk Management Account Equity Risk % per Trade (default: 1%) ATR Trailing Stop (ON/OFF) Trail Multiplier (default: 2.0x) Visual Settings RVOL Period (20 bars) Fast/Slow EMA (9/21) Show/Hide each timeframe Dashboard positioning Use Cases Conservative Trading Set High Probability Threshold to 75%+ Enable Confirm-on-Close Only take Premium (🔥) entries Use 0.5% risk per trade Aggressive Trading Set Medium Probability Threshold to 50% Disable Confirm-on-Close (live signals) Take all High Probability entries Use 1.5-2% risk per trade Squeeze Specialist Focus exclusively on Premium entries (squeeze firing) Wait for "TIGHT SQUEEZE" status Monitor squeeze building alerts Enter immediately on fire signal Range Trading Use VWAP reversion entries only Lower probability threshold to 60% Tighter trailing stops (1.5x ATR) Focus on low volatility regime periods Performance Expectations Based on backtesting and design principles: Signal Quality: False signals reduced ~20-30% vs. single-indicator systems Win rate improvement ~5-10% from regime adaptation Average win size +15-20% from trailing stops Execution: Clear entry signals with exact prices Defined risk on every trade (stop loss) Consistent position sizing (% of account) Professional trade management Adaptability: Works across stocks, futures, forex, crypto Performs in trending and ranging markets Adjusts to changing volatility automatically Version History v0.1.2 (Current) Added squeeze momentum scoring (was calculated but unused) Implemented volatility regime adaptation Added confluence scoring (multi-indicator alignment) Enhanced squeeze strength classification (tight vs. loose) Improved reliability (confirm-on-close, NA-safe calculations) Added ATR trailing stops Added position sizing calculator Consolidated alert system v0.1.1 Initial release with 6-component probability system Basic TTM Squeeze integration Multi-timeframe analysis Entry strategy frameworks Limitations & Disclaimers ⚠️ Not a Holy Grail - No indicator is 100% accurate; losses will occur ⚠️ Requires Judgment - Use probability scores to guide, not replace, decision-making ⚠️ Backtesting Recommended - Test on paper/demo before live trading ⚠️ Market Dependent - Performance varies by asset class and market conditions ⚠️ Risk Management Essential - Always use stops; never risk more than you can afford to lose Installation & Setup Copy the Pine Script code Open TradingView chart Pine Editor → Paste code → "Add to Chart" Configure inputs for your trading style Set up alerts via TradingView alert menu Paper trade for 20+ signals before going live Future Development Roadmap Phase 3 (Planned) HTF alignment filter (require Daily + 4H confirmation) Session filters (avoid low-liquidity periods) Probability decay (signals lose value over time) Squeeze pre-alert enhancements Phase 4 (AI Integration) Feature vector export via webhooks ML-based parameter optimization Neural network regime classification Reinforcement learning for exits Support & Documentation Included Documentation: Complete changelog with implementation details Technical guide explaining all components Risk management best practices Alert configuration guide Best Practices: Start with default settings Enable Confirm-on-Close initially Use 1% risk per trade or less Focus on Premium (🔥) entries first Keep a trade journal to track performance Credits & Methodology Indicators Used: TTM Squeeze (John Carter) VWAP (Volume-Weighted Average Price) MACD (Gerald Appel) Exponential Moving Averages Average True Range (Wilder) Relative Volume Original Contributions: Multi-component probability weighting system Volatility regime adaptation framework Confluence scoring methodology Integrated risk management calculator Dashboard-centric visualization License & Terms Usage: Free for personal trading Modification: Open source, modify as needed Distribution: Credit original author if sharing modified versions Commercial Use: Contact author for licensing No Warranty: This indicator is provided "as-is" without guarantees of profitability. Trading involves substantial risk. Past performance does not guarantee future results. Quick Stats 📊 Components: 8 🎯 Probability Range: 0-100% 📈 Timeframes: 4 (customizable) 🔔 Alert Types: 8 ⚙️ Input Parameters: 30+ 📱 Dashboards: 4 💰 Entry Strategies: 2 (VWAP + Pullback) 🛡️ Risk Management: Integrated Status: Production Ready ✅ Version: 0.1.2 Last Updated: November 2025 Pine Script: v6 File Name: PA_AI_PRE_GO_v0.1.2_FIXED.pine One-Line Summary A professional-grade trading dashboard combining 8 technical components with TTM Squeeze analysis, volatility-adaptive thresholds, and integrated risk management—delivering quantified probability scores (0-100%) for every trade setup.
Indicateur Pine Script®
par DayTradingMD1992