[GetSparx] Nova Pro⚡ Nova Pro – Position Calculator
This indicator is a user-friendly TradingView indicator designed to help traders plan and visualize their entry and exit points, calculate position sizing, and instantly display key risk metrics. By simply entering three price levels (Entry, Take Profit and Stop Loss) along with a risk amount in USD, the indicator draws color-coded lines and labels on the chart, and generates a concise table with all computed values. This allows you to assess the risk-reward profile of any trade at a glance, without performing manual calculations.
⚙️ How It Works
When the indicator is added to the chart it will ask to specify the price inputs and the risk amount in USD.
Price Inputs (Entry, TP, SL)
• You specify three price levels: the entry price, the profit target (Take Profit) and the loss threshold (Stop Loss).
• Inputs use TradingView’s native price-picker fields. Any change is immediately reflected on the chart.
Visual Display
• Each level is plotted as a line stretching into the future for enough room.
• Labels on the right show the exact price, color-coded: orange for Entry, green for TP and red for SL.
• Previous lines and labels are automatically removed when parameters change, ensuring the chart remains clean.
Risk Calculations
• The entered risk amount (in USD) is combined with the distance between Entry and SL to compute the optimal number of units (Qty) to trade.
• The script automatically detects whether it’s a long or short trade based on the relative positions of Entry and TP.
• Note that the risk and reward calculations do not factor in exchange fees, slippage, funding rates or any other trading costs. Actual profit and loss may differ once transaction fees and market execution variances are applied, so be sure to adjust your position sizing and expectations accordingly.
🎯 What You Can Do With It
• Consistent Position Sizing
Automate your position size so you consistently risk the same dollar amount, regardless of price volatility or stop distance.
• Clear Risk Management
Instantly view your Reward-to-Risk ratio, potential profit in USD and exact risk amount, so you make well-informed decisions.
• Rapid Scenario Analysis
Adjust TP, SL or Entry on the fly to see how each change affects your potential profit, loss and RR ratio.
• Publication-Ready Charts
The visual elements and integrated table are optimized for TradingView publications, giving your analysis a professional, polished look.
📊 Explanation of Table Values
• Entry
Calculation: rounded to the nearest tick of your entered entry price.
Marks the exact level at which you initiate the trade and serves as the reference point for all further risk and reward calculations.
• Quantity (Qty)
Calculation: Risk USD ÷ (Entry − Stop Loss).
Determines how many units, contracts or shares to trade so that a stop-out at your SL equals exactly your predefined dollar risk, resulting in consistent per-trade exposure.
• Risk to Reward (RR)
Calculation: (Take Profit − Entry) ÷ (Entry − Stop Loss).
Expresses how many dollars of potential profit you target for each dollar you risk. Values above 1 mean the reward exceeds the risk, guiding you to favorable setups.
• Take Profit (TP)
Calculation: rounded to the nearest tick of your entered take-profit price.
Your target exit level for booking gains, highlighted in green on the chart. Shows where you plan to capture profits if the market moves in your favor.
• Profit
Calculation: Qty × (Take Profit − Entry).
Gives the absolute potential gain in USD if price reaches your TP. Useful for comparing total return across different instruments or setups.
• Stop Loss (SL)
Calculation: rounded to the nearest tick of your entered stop-loss price.
The level at which your trade is automatically closed to cap losses, highlighted in red on the chart. Ensures you never lose more than your defined risk amount.
• Risk
Calculation: equals the entered Risk USD.
The maximum dollar amount you’re willing to lose on this trade. Acts as the upper boundary for your exposure, keeping your position sizing disciplined.
📝 Examples
• Long Example 1: Bitcoin/USD
Entry: $11851.1
Take Profit: $123853.9
Stop Loss: $115467.7
Risk USD: $500
The Risk to Reward ratio results in 2.25, which means the reward exceeds the risk.
For each dollar you risk, this setup has potential gains of 2.25 dollars.
• Long Example 2: Algorand/USD
Entry: $0.2919
Take Profit: $0.3491
Stop Loss: $0.2655
Risk USD: $1000
The Risk to Reward ratio on this trade results in 2.17 and has a potential profit target of $2166.67. With a risk of $1000 USD the table conveniently shows a quantity of 37878 ALGO is needed for the trade.
• Short Example 1: Forex EUR/USD
Entry: $1.16666
Take Profit: $1.15459
Stop Loss: $1.17374
Risk USD: $200
With a risk of $200 USD and a RR of 2.17, this example shows how a short trade can be accomplished on EUR/USD.
• Short Example 2: Gold
Entry: $3366.29
Take Profit: $3272.01
Stop Loss: $3386.87
Risk USD: $1500
Within this short setup a risk of $1500 USD is used, which results in a RR of 4.58. The potential profit for this trade is $6871.72.
⚠ Disclaimer
This tool is for educational and analytical use only. It does not provide financial advice or trading signals. Always use proper risk management and do your own due diligence.
Statistics
OTT Volatility [RunRox]📊 OTT Volatility is an indicator developed by the RunRox team to pinpoint the most optimal time to trade across different markets.
OTT stands for Optimal Trade Time Volatility and is designed primarily for markets without a fixed trading session, such as cryptocurrencies that trade 24/7. At the same time, it works equally well on any other market.
🔶 The concept is straightforward. The indicator takes a specified number of historical periods (Samples) and statistically evaluates which hours of the day or which days show the highest volatility for the selected asset.
As a result, it highlights time windows with elevated volatility where traders can focus on searching for trade setups and building positions.
🔶 As the core volatility metric, the indicator uses ATR (Average True Range) to measure intraday volatility. Then it calculates the average ATR value over the last N Samples, creating a statistically stable estimate of typical volatility for the selected asset.
🔶 Statistically, during these highlighted periods the market shows higher-than-average volatility.
This means that in these time windows price is more likely to be subject to stronger moves and potential manipulation, making them attractive for active trade execution and position management.
⚠️ However, historical behavior does not guarantee future results.
These periods should be treated only as zones where volatility has a higher probability of being above normal, not as a promise of movement.
As shown in the screenshot above, the indicator also projects potential future volatility based on historical data. This helps you better plan your trading hours and align your activity with periods where volatility is statistically expected to be higher or lower.
🔶 Current Volatility – as shown in the screenshot above, you can also monitor the real-time volatility of the market without any statistical averaging.
On top of that, you can overlay the current volatility on top of the statistical volatility levels, which makes it easy to see whether the market is now trading in a high- or low-volatility regime relative to its usual behavior.
4 display modes – you can choose any visualization style that fits your trading workflow:
Absolute – displays the raw volatility values.
Relative – shows volatility relative to its typical levels.
Average Centered – centers volatility around its average value.
Trim Low Value – filters out low-volatility noise and highlights only more significant moves.
This indicator helps you define the most effective trading hours on any market by relying on historical volatility statistics.
Use it to quickly see when your market tends to be more active and to structure your trading sessions around those periods.
✅ We hope this tool becomes a useful part of your trading toolkit and helps you improve the quality of your decisions and timing.
BTST Stats BTST Statistical Edge Analyzer — VCR · Volume · SMA · RSI Filtered
This indicator isn’t a trading signal generator.
It’s a research framework designed to answer a simple but valuable question:
“Does Buy-Today-Sell-Tomorrow (BTST) have statistical edge under specific market conditions?”
Most traders assume BTST works because they feel markets gap.
This script measures whether that belief holds true — and under what filters.
🔍 What the Indicator Does
For each bar, the script simulates a BTST trade:
Entry: previous bar’s close
Exit: current bar’s open
Result: Open(next day) − Close(previous day)
But a BTST trade is only counted if the entry bar satisfies the filter logic.
🎯 Entry Filters You Can Tune
A trade is included only if ALL activated conditions are satisfied:
Filter Rule
VCR Filter Candle volatility ratio must exceed threshold: `(High−Low) /
Volume Filter Volume must be greater than n × AverageVolume
SMA Trend Filter (Optional) Close must be above a user-selected SMA length
RSI Condition (Optional) RSI must be between a user-defined min/max band
This allows testing BTST under different volatility, trend, and momentum conditions.
📊 What the Table Shows
For all qualifying trades inside the chosen lookback window, the indicator displays:
Metric Meaning
Profitable Trades Count of BTST trades with positive overnight return
Losing Trades Count of negative overnight returns
Avg Profit Average upside gain on winner trades
Avg Loss Average downside loss on losing trades
Avg Net per Trade Overall expectancy across all trades
Avg High After Entry Average maximum price movement above entry (potential upside)
Avg Low After Entry Average price movement against the entry (risk exposure)
Winner-Only High/Low Stats How far good trades move and how much heat they take
Loser-Only High/Low Stats How bad trades behave, including early fake-outs
Together, these reveal:
Opportunity potential
Risk exposure
Whether trades behave cleanly or chaotically
Whether exits are leaving money on the table
🧠 Why This Matters
BTST edges change drastically across:
Market regimes
Trend direction
Volatility clusters
Earnings cycles
Volume surges
This tool helps identify when BTST should be traded — and when it should be avoided entirely.
Rather than guessing, traders can:
Validate if their BTST assumptions hold,
Apply filters until the expectancy improves,
Rank symbols and conditions where the system performs best.
🚫 Not a Buy/Sell Indicator
This script does not place arrows, signals, alerts, or entries.
It exists for analysis and system development, not live execution.
Use it to:
Build ideas
Validate hypotheses
Compare symbols
Optimize BTST frameworks
Decide if BTST belongs in your playbook — or in the trash
🔧 Who This Is For
✔ System traders
✔ Quant-minded traders
✔ Options/Index traders who rely on gaps
✔ Swing traders testing overnight holds
✔ Developers building automated BTST logic
Final Thought
BTST isn’t magic — it’s just a behavior pattern.
Some markets reward it.
Some punish it.
Some reward it only under the right volatility and volume conditions.
This tool tells you which is which.
BTC ETF Flow Monitor🚀 Bitcoin ETF Flow Monitor - Track Institutional Money Flows
Monitor real-time dollar flows across major Bitcoin ETFs with this professional-grade indicator inspired by Dune Analytics. Perfect for tracking institutional sentiment and Bitcoin adoption trends.
📊 Key Features: • Real Dollar Flows : Display actual estimated flows in millions USD, not abstract indices
• 5 Major ETFs : IBIT (BlackRock), FBTC (Fidelity), ARKB (ARK), BITB (Bitwise), GBTC (Grayscale)
• Dune Analytics Style : Clean, professional visualization with meaningful thresholds
• Smart Alerts : Get notified of significant flow changes and BTC price divergences
• Enhanced Summary Table : Live stats including total flows, trends, and market sentiment
💡 How It Works: Combines volume, price action, and momentum to estimate institutional dollar flows. Positive values = inflows (buying pressure), negative values = outflows (selling pressure). Scale shows millions of USD for easy interpretation.
🎯 Perfect For:
- Tracking institutional Bitcoin adoption
- Identifying accumulation/distribution phases
- Spotting divergences between ETF flows and BTC price
- Understanding market sentiment shifts
⚡ Professional Grade: Built with advanced Pine Script techniques, optimized performance, and real-world trading applications in mind.
Trend Continuation [OmegaTools]Trend Continuation is a trend-following and trend-continuation tool designed to highlight high-probability pullbacks within an existing directional bias. It helps discretionary and systematic traders visually isolate “continuation zones” where a retracement is more likely to resolve in favor of the prevailing trend rather than trigger a full reversal.
1. Concept and Objective
The indicator combines two key components:
1. A trend bias engine (based either on a Rolling VWAP regime or on swing market structure).
2. A pullback pressure model, which quantifies how deep and “aggressive” the recent retracement has been relative to the trend.
The goal is to identify moments where the market pulls back against the trend, builds enough “reversal pressure,” and then shows signs that the trend is likely to **continue** rather than flip. When specific conditions are met, the indicator highlights bars and plots reference levels that can be used as potential continuation zones, filters, or confluence areas in a broader trading plan.
2. Trend Bias Modes
The primary trend direction is defined through the `Trend Mode` input:
* **RVWAP Mode (default)**
The script computes two rolling volume-weighted average prices over different lengths:
* A **shorter-term rolling VWAP**
* A **longer-term rolling VWAP**
When the shorter RVWAP is above the longer one, the bias is set to **bullish (+1)**. When it is below, the bias is **bearish (-1)**.
This creates a smooth, volume-weighted trend definition that tends to adapt to shifting regimes and filters out minor noise.
* **Market Structure Mode**
In this mode, trend bias is derived from **pivot highs and lows**:
* When price breaks above a recent pivot high, the bias flips to **bullish (+1)**.
* When price breaks below a recent pivot low, the bias flips to **bearish (-1)**.
This approach is more structurally oriented and reacts to significant swing breaks rather than just moving-average style relationships.
If no clear condition is met, the internal bias can temporarily be neutral, though the main design assumes working with clearly bullish or bearish environments.
3. Pullback and Reversal Pressure Logic
Once the trend bias is defined, the indicator measures **pullback intensity** against that trend:
* A **lookback window (“Pullback Length”)** scans recent highs and lows:
* In an uptrend, it tracks the **highest high** over the window and measures how far the current low pulls back from that high.
* In a downtrend, it tracks the **lowest low** and measures how far the current high bounces up from that low.
* This distance is converted into a **“reversal pressure” value**:
* In a bullish bias, deeper pullbacks (lower lows relative to the recent high) indicate stronger counter-trend pressure.
* In a bearish bias, stronger rallies (higher highs relative to the recent low) indicate stronger counter-trend pressure.
The raw reversal pressure is then smoothed with a long-term moving average to separate normal retracements from **statistically significant extremes**.
4. Thresholds and Histogram Coloring
To avoid reacting to every minor pullback, the indicator builds a **dynamic threshold** using a combination of:
* Long-term averages of reversal pressure.
* Standard deviation of reversal pressure.
* High-percentile values of reversal behavior over different sample sizes.
From this, a **threshold line** is derived, and the script then compares the current reversal pressure to this adaptive level:
* The **Reversal Histogram** (column plot) represents the excess reversal pressure above its own long-term average.
* When:
* There is a valid bullish or bearish bias, and
* The histogram is above the dynamic threshold,
the bars of the histogram are **colored**:
* Blue (or a similar “positive” color) in bullish bias.
* Red/pink (or a similar “negative” color) in bearish bias.
* When reversal pressure is below threshold or bias is not relevant, the histogram remains **neutral gray**.
These colored histogram segments represent **“high-tension” pullback states**, where counter-trend pressure has reached an extreme that, historically, often resolves with the original trend continuing rather than fully reversing.
5. Continuation Level and Bar Coloring on Price Chart
To connect the oscillator logic back to the chart:
* A **continuation reference level** is computed on the price series:
* In an uptrend, this is derived by subtracting the threshold from recent highs.
* In a downtrend, it is derived by adding the threshold to recent lows.
* This level is plotted as a **line on the price chart** (only when the trend bias is stable), acting as a visual guide for:
* Potential continuation zones,
* Possible stop-placement or invalidation areas,
* Or filters for entries/exits.
The bars are then **colored** when price crosses or interacts with these levels in the direction of the trend:
* In a bullish bias, bars closing below the continuation level can be highlighted as potential **deep pullback/continuation opportunities** or as warning signals, depending on the user’s playbook.
* In a bearish bias, bars closing above the continuation level are similarly highlighted.
This makes it easy to see where the oscillator’s “extreme pullback” conditions align with structural movements on the actual price bars.
6. Embedded Win-Rate Estimation (WR Table)
The script also includes an internal **win-rate style metric (WR%)** displayed in a small table on the chart:
* It tracks occurrences where:
* A valid bullish or bearish bias is present, and
* The Reversal Histogram is **above the threshold** (i.e., histogram is colored).
* It then approximates the **probability that the trend bias does not change** following such high-pressure pullback events.
* The WR value is shown as a percentage and represents, in essence, the **historical trend-continuation rate** under these specific conditions over the most recent sample of events.
This is not a formal statistical test and does not guarantee future performance, but it provides a quick visual indication of how often these continuation setups have led to **trend persistence** in the recent past.
7. How to Use in Practice
Typical applications include:
Trend-following entries on pullbacks
Identify the main trend using either RVWAP or Market Structure mode.
Wait for a colored histogram bar (reversal pressure above threshold).
Use the continuation reference line and bar coloring on the price chart to refine entry zones or invalidation levels.
Filtering signals from other systems
Run the indicator in the background to confirm trend continuation conditions before taking signals from another strategy (e.g., breakouts or momentum entries).
Only act on long signals when the bias is bullish and a high-pressure pullback has recently occurred; similarly for short signals in bearish conditions.
Risk management and trend monitoring
Monitor when reversal pressure is building against your current position.
Use shifts in bias combined with high reversal pressure to re-evaluate or scale out of trend-following trades.
Recommended steps:
1. Choose your Trend Mode:
- RVWAP for smoother, regime-style trend detection.
- Market Structure for swing-based structural changes.
2. Adjust Trend Length and Pullback Length to match your timeframe (shorter for intraday, longer for swing/position trading).
3. Observe where histogram colors appear and how price reacts around the continuation line and highlighted bars.
4. Integrate these signals into a pre-defined trading plan with clear entry, exit, and risk rules.
8. Limitations and Disclaimer
* This tool is a **technical analysis aid**, not a complete trading system.
* Past behavior of trend continuation or reversal pressure does **not** guarantee future results.
* The embedded WR metric is a **descriptive statistic** based on recent historical conditions only; it is not a promise of performance or a robust statistical forecast.
* All parameters (lengths, thresholds, modes) are user-configurable and should be **tested and validated** on your own data, instruments, and timeframes before any live use.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial, investment, or trading advice. Trading and investing in financial markets involve substantial risk, including the possible loss of all capital. You are solely responsible for your own trading decisions and for evaluating all information provided by this tool. OmegaTools and the author of this script expressly disclaim any liability for any direct or indirect loss resulting from the use of this indicator. Always consult with a qualified financial professional before making any investment decisions.
BTC -50% Crash to Recovery ZoneGeneral Overview This is a macro-analysis tool designed to visualize the true duration of Bitcoin’s "Suffering & Recovery Cycles." Unlike standard oscillators that only signal oversold conditions, this script highlights the entire timeline required for the market to flush out leverage and return to All-Time Highs (ATH).
Operational Logic The algorithm tracks Bitcoin’s historical All-Time High (ATH).
The Trigger: It activates automatically when the price drops 50% below the last recorded ATH.
The "Recovery Zone": Once triggered, the chart background turns red (indicating a "Drawdown" state). This zone remains active persistently, even during intermediate relief rallies.
The Reset: The zone deactivates only when the price breaks above the previous ATH, marking the official start of a new Price Discovery phase.
How to Read It
Red Background: We are officially in a Bear Market or Recovery Phase. The asset is technically "underwater." For the long-term investor with a low time preference, this visually defines the accumulation window.
Red Horizontal Line: Indicates the "Target." This is the exact price level of the old ATH that Bitcoin must reclaim to close the bearish cycle.
No Background Color: We are in Price Discovery. The market is healthy and pushing for new highs.
The Financial Lesson This indicator visually demonstrates a fundamental market truth: "Price takes the elevator down, but takes the stairs up." It shows that after a halving of value (-50%), Bitcoin may take months or years to recover previous levels, helping investors filter out the noise of short-term pumps that fail to break the macro-bearish structure.
RSI Driven ATR Trend [NeuraAlgo]
RSI Driven ATR Trend
Dynamic Trend Detection and Strength Analysis
Unlock the market’s hidden rhythm with the RSI Driven ATR Trend , a sophisticated tool designed to measure trend direction and strength using a combination of RSI momentum and ATR-based volatility . This indicator provides real-time insights into bullish and bearish phases, helping traders identify potential turning points and optimize entry and exit decisions.
1.Core In Logic:
Dynamically calculates trend levels based on RSI and ATR interactions.
Highlights trend direction with intuitive color coding: green for bullish, red for bearish.
Displays trend strength as a percentage to quantify momentum intensity.
Automatic visual cues for potential trend reversals with “Turn Up” and “Turn Down” labels.
Advanced smoothing and dynamic gating ensure responsive yet stable trend detection.
Compatible with all timeframes and instruments.
2.Inputs Explained:
Rsi Factor: Adjusts the sensitivity of the RSI in trend calculation. Higher values make the trend detection more responsive to momentum changes.
Multiplier: Multiplies the effect of Rsi Factor to fine-tune trend responsiveness.
Bar Back: Number of bars used for peak and dip calculations, determining how far back the indicator looks for trend changes.
Period: Lookback period used in trend gating and ATR calculations.
Source: Price source for calculations (default is close).
Main Colors: Customize bullish and bearish trend colors.
3.How it Works:
The indicator calculates RSI values and ATR-based dynamic ranges to determine upper and lower trend levels.
Trend direction is determined by price crossing above (bullish) or below (bearish) the dynamic trend line.
Trend strength is expressed as a percentage relative to the trend line, helping you assess momentum intensity.
Visual cues like "Turn Up" and "Turn Down" labels indicate potential trend reversals.
Bars are colored dynamically based on trend direction for quick interpretation.
Ideal for traders seeking a clear, actionable view of market trends without the clutter of multiple indicators. RSI Driven ATR Trend translates complex price behavior into an easy-to-read visual guide, helping you make smarter trading decisions.
Happy Trading!
I4I Inside Vortex Strike RateThis indicator identifies what I call an "Inside Vortex": It's similar to a Doji but more strict in having to be inside a keltner and also have a lower ATR than a blended average.
The bar itself is not that special. But it indicates that a potential big move might come in the next 2 periods.
After the patter: It then looks at what I call the Market Maker High and Low: A % of a blended ATR. It then looks back 100-200 or more bars and calculates the overall strike % in history for the High and low after the pattern happens.
This allows us to know how often these levels are hit within the next 2 periods to find if we have any edge on spread, call or put prices or use them as targets.
So its:
Pattern:
Levels
Strike Rate.
Very unique and EXTREME useful. Especially for options traders.
smartAitrade Complete FocusTrendPajinko-SmartAiTrade Complete is an all-in-one price-action technical system designed for high-precision entries, intelligent trade management, and fully automated exit logic.
The system combines RSI swings, advanced divergence detection, ATR-based PJK Bands, smart retest logic, swing-break POI zones, trend filters (ADX), and automated breakeven/TP management into a single integrated indicator.
It is built to support traders who want structured, rule-based entries with minimal discretion, while still maintaining the flexibility of price-action behavior.
🔍 Core Components
1. RSI System
Standard RSI for overbought/oversold levels.
RSI Swing High/Low detection (using pivots).
Used for:
momentum confirmation
swing structure alignment
divergence detection filters
2. Advanced Divergence Engine
The indicator features a high-accuracy divergence module that detects:
• Bullish Divergence
Price makes a lower low
RSI makes a higher low
Pivot distances must fall within a valid bar-range
Optional filter: RSI must be in oversold zone
• Bearish Divergence
Price makes a higher high
RSI makes a lower high
Optional filter: RSI must be in overbought zone
You can choose to draw divergence lines on either:
RSI only
Price chart
Both
This system is optimized for low repaint and filters weak divergence signals.
3. ATR-Based PJK Bands System
A volatility-adaptive band system similar to Keltner/Bollinger hybrids:
Middle line uses SMA/EMA/VWMA
Upper/lower bands = middle ± ATR × multiplier
Bands detect:
momentum breakouts
band touch signals
high-probability reversal zones
Buy signal:
Price touches lower band and shifts upward
Sell signal:
Price touches upper band and shifts downward
4. Smart Retest System
After a momentum breakout or band touch signal:
A “smart retest zone” is created
The system waits for price to come back to the zone
If retest occurs within a user-defined timeout window, the signal is validated
Used to avoid chasing entries and reduce false breakouts
5. Swing Break & POI Zones
The indicator automatically detects price-swing structure:
Swing High Break → Sell POI box created
Swing Low Break → Buy POI box created
POI zones:
Represent potential liquidity pockets
Drawn with customizable height and width
Work as target areas or confirmation zones
6. ADX Trend Filter
ADX trend strength filter ensures signals are valid only when:
Trend strength > threshold (default 20)
Avoids signals in flat, low-volatility markets
7. Auto Trade Management (Breakeven System)
Fully automated exit logic:
TP1 distance set in pips
Once TP1 is reached → move Stop Loss to breakeven + offset
Additional option:
Close all open positions automatically when trend bias changes
Everything works even with multiple open trades.
8. Dashboard & Visual Interface
The indicator includes a clean dashboard showing:
Trend condition
RSI status
Advanced divergence status
Band and swing conditions
Active signals
Breakeven status
Total signals statistics
All visual components can be enabled/disabled individually.
🎯 Trading Philosophy
The system is built on three core principles:
1. Confirm Trend
ADX + ATR Bands define direction and strength.
2. Identify High-Probability Reversal or Continuation Zones
Smart Retest + Swing Structure + POI + Divergence.
3. Automate the Exit
Breakeven, TP1, and automatic closing keep emotions out of the decision.
Volatility Signal-to-Noise Ratio🙏🏻 this is VSNR: the most effective and simple volatility regime detector & automatic volatility threshold scaler that somehow no1 ever talks about.
This is simply an inverse of the coefficient of variation of absolute returns, but properly constructed taking into account temporal information, and made online via recursive math with algocomplexity O(1) both in expanding and moving windows modes.
How do the available alternatives differ (while some’re just worse)?
Mainstream quant stat tests like Durbin-Watson, Dickey-Fuller etc: default implementations are ALL not time aware. They measure different kinds of regime, which is less (if at all) relevant for actual trading context. Mix of different math, high algocomplexity.
The closest one is MMI by financialhacker, but his approach is also not time aware, and has a higher algocomplexity anyways. Best alternative to mine, but pls modify it to use a time-weighted median.
Fractal dimension & its derivatives by John Ehlers: again not time aware, very low info gain, relies on bar sizes (high and lows), which don’t always exist unlike changes between datapoints. But it’s a geometric tool in essence, so this is fundamental. Let it watch your back if you already use it.
Hurst exponent: much higher algocomplexity, mix of parametric and non-parametric math inside. An invention, not a math entity. Again, not time aware. Also measures different kinds of regime.
How to set it up:
Given my other tools, I choose length so that it will match the amount of data that your trading method or study uses multiplied by ~ 4-5. E.g if you use some kind of bands to trade volatility and you calculate them over moving window 64, put VSNR on 256.
However it depends mathematically on many things, so for your methods you may instead need multipliers of 1 or ~ 16.
Additionally if you wanna use all data to estimate SNR, put 0 into length input.
How to use for regime detection:
First we define:
MR bias: mean reversion bias meaning volatility shorts would work better, fading levels would work better
Momo bias: momentum bias meaning volatility longs would work better, trading breakouts of levels would work better.
The study plots 3 horizontal thresholds for VSNR, just check its location:
Above upper level: significant Momo bias
Above 1 : Momo bias
Below 1 : MR bias
Below lower level: significant MR bias
Take a look at the screenshots, 2 completely different volatility regimes are spotted by VSNR, while an ADF does not show different regime:
^^ CBOT:ZN1!
^^ INDEX:BTCUSD
How to use as automatic volatility threshold scaler
Copy the code from the script, and use VSNR as a multiplier for your volatility threshold.
E.g you use a regression channel and fade/push upper and lower thresholds which are RMSEs multiples. Inside the code, multiply RMSE by VSNR, now you’re adaptive.
^^ The same logic as when MM bots widen spreads with vola goes wild.
How it works:
Returns follow Laplace distro -> logically abs returns follow exponential distro , cuz laplace = double exponential.
Exponential distro has a natural coefficient of variation = 1 -> signal to noise ratio defined as mean/stdev = 1 as well. The same can be said for Student t distro with parameter v = 4. So 1 is our main threshold.
We can add additional thresholds by discovering SNRs of Student t with v = 3 and v = 5 (+- 1 from baseline v = 4). These have lighter & heavier tails each favoring mean reversion or momentum more. I computed the SNR values you see in the code with mpmath python module, with precision 256 decimals, so you can trust it I put it on my momma.
Then I use exponential smoothing with properly defined alphas (one matches cumulative WMA and another minimizes error with WMA in moving window mode) to estimate SNR of abs returns.
…
Lightweight huh?
∞
Z-Score Regime DetectorThe Z-Score Regime Detector is a statistical market regime indicator that helps identify bullish and bearish market conditions based on normalized momentum of three core metrics:
- Price (Close)
- Volume
- Market Capitalization (via CRYPTOCAP:TOTAL)
Each metric is standardized using the Z-score over a user-defined period, allowing comparison of relative extremes across time. This removes raw value biases and reveals underlying momentum structure.
📊 How it Works
- Z-Score: Measures how far a current value deviates from its average in terms of standard deviations.
- A Bullish Regime is identified when both price and market cap Z-scores are above the volume Z-score.
- A Bearish Regime occurs when price and market cap Z-scores fall below volume Z-score.
Bias Signal:
- Bullish Bias = Price Z-score > Market Cap Z-score
- Bearish Bias = Market Cap Z-score > Price Z-score
This provides a statistically consistent framework to assess whether the market is flowing with strength or stress.
✅ Why This Might Be Effective
- Normalizing the data via Z-scores allows comparison of diverse metrics on a common scale.
- Using market cap offers broader insight than price alone, especially for crypto.
- Volume as a reference threshold helps identify accumulation/distribution regimes.
- Simple regime logic makes it suitable for trend confirmation, filtering, or position biasing in systems.
⚠️ Disclaimer
This script is for educational purposes only and should not be considered financial advice. Always perform your own research and risk management. Past performance is not indicative of future results. Use at your own discretion.
NeuraAlgo - Market DynamicsNeuraAlgo – Market Dynamics
Simplyfying the Market Dynamics
Unlock the complexity of financial markets with NeuraAlgo – Market Dynamics. Designed for traders and investors alike, this intelligent tool distills the chaos of price movements, volume fluctuations, and trend directions into clear, actionable insights. With advanced algorithms working behind the scenes, it simplifies market dynamics so you can focus on making informed decisions, spotting opportunities, and managing risk with confidence.
Behind this simple overlay lies a powerful, complex algorithm.
Main Settings -Main Algorithm
Timeframe – Choose the chart timeframe that the indicator will analyze. It adapts the calculations to the selected interval for precise market insights.
Preset – Select the operating mode:
Main Trend: Focuses on the dominant market trend.
Multi Trend: Analyzes multiple trend layers for a broader perspective.
Sensitivity – Adjusts the indicator’s responsiveness to price changes. Higher values make the system more reactive to market fluctuations, while lower values smooth out minor noise.
Smooth Tuner – Controls the smoothing of the underlying calculations, helping to reduce false signals and provide cleaner trend visualization.
Orderflow Statistics – Toggle to display detailed order flow statistics directly on the chart for deeper market analysis.
Performance Statistics – Toggle to enable backtesting tables, showing historical performance metrics of the indicator for strategy evaluation.
2.Art Settings -Change Visuals
Color Scheme – Select a pre-defined visual theme for your charts:
Bright Light – High-contrast, vibrant colors for maximum clarity.
Freezer Mode – Cool-toned palette for calm, visually comfortable analysis.
Standard Mode – Balanced, neutral colors for everyday use.
Delta Mode – Highlights key differences and movements with distinct colors.
Custom – Fully customize the colors of bullish, bearish, and range elements.
Green / Red / Range (Custom Colors) – When “Custom” is selected, these options allow you to define the colors for bullish (Green), bearish (Red), and neutral/range areas (Range) according to your preference.
Candle Coloring Type – Choose how candles are highlighted based on market signals:
Confirmation Simple – Basic signal-based coloring for clear, direct visualization.
Confirmation Gradient – Smooth gradient-based coloring for more dynamic and aesthetic signal representation.
3.Dashboard -Market Statistics
The Dashboard provides a compact, at-a-glance overview of key market conditions and indicator metrics, helping traders make faster and more informed decisions.
Functionality & Layout – The dashboard dynamically displays multiple sections:
Optimal Scale ⚖️ – Shows key market scaling metrics like volatility for better decision-making.
Risk Manager 📊 – Indicates the active risk management strategy (e.g., Risk-Reward, Partial Exits, or Trailing Stop Loss).
Orderflow Statistics 📈 – Displays market sentiment, footprint strength, and delta trends for precise order flow analysis.
Market Status 🌐 – Highlights current trend conditions and trend strength across different timeframes.
Bias Scores 🎯 – Provides trend strength percentages across multiple timeframes (5min, 15min, 30min, 1H, 4H, 1D) to quickly gauge market bias.
Backtest Performance -A summary panel showing the overall performance of the strategy.
Deposit -The starting capital used for backtesting.
Win Trades -Total number of profitable trades.
Winrate -Percentage of winning trades out of all trades.
Max DD -Maximum drawdown — the largest peak-to-trough loss.
PnL -Net profit or loss generated by the strategy.
Return -Percentage growth of the account during the test.
Profit Factor -Ratio of total profits to total losses.
The dashboard uses color-coded indicators (green for bullish, red for bearish, yellow for neutral) and merged cells for a clean and organized display.
It’s designed to simplify complex market dynamics into a visually intuitive interface, giving traders real-time insights without cluttering the chart.
4.Neura Engineering – Enhancements
This section provides advanced filtering options to fine-tune market analysis, reduce noise, and highlight meaningful trends.
Noise Filter – Smoothens minor price fluctuations to reduce false signals.Noise Sensitivity helps Adjust how aggressively the filter suppresses noise.
Gap Filter – Detects and smooths price gaps to improve trend clarity.Gap Sensitivity helps Controls the responsiveness of the gap filter.
Range Filter – Filters out small-range price movements to focus on significant market swings.helps Adjusts how tightly the filter defines meaningful ranges.
Volatility Filter – Highlights periods of high market volatility while filtering less active periods.helps Sets the threshold for what constitutes high volatility.
Trend Filter – Focuses analysis on strong trends by filtering out weaker signals.helps Determines the minimum strength required for a trend to be considered valid.helps Uses Average True Range to dynamically adjust trend filtering based on market movement.
These enhancement tools allow traders to customize signal clarity, reduce noise, and focus on meaningful market dynamics, creating a cleaner and more actionable charting experience.
5.Neura Overlays – Market Visual Enhancements
These overlays add visual intelligence to your chart, helping you instantly understand trend behavior, sentiment shifts, and price structure.
Reversal Cloud - Highlights potential reversal zones where price may change direction.Reversal Sensitivity helps Controls how quickly the cloud reacts to shifts in momentum.
Sentiment Cloud -Maps the underlying market mood—bullish, bearish, or neutral—directly onto the chart.Sentiment Sensitivity helps Adjusts how sensitive the sentiment readings are.
Price Steps -Draws structured “price steps” that reveal hidden market rhythm, impulse strength, and trend flow.Price Step Depth helps Determines the size and spacing of these steps.
Market Bias -Shows directional bias based on deeper trend pressure and underlying orderflow.Bias Sensitivity helps Controls how strict or lenient the bias detection is.
6.Risk Management Settings – Intelligent Trade Control
This module controls how your trades manage themselves after entry. Choose between traditional Risk/Reward exits, partial profit-taking, or an adaptive trailing stop system.
RiskReward
A classic risk-to-reward exit system.You set a risk multiple (e.g., 1:2), and the indicator automatically sets one Stop Loss and one Take Profit based on that ratio.
Partials
Scales out your position at multiple take-profit levels.Instead of closing the entire trade at once, the system secures profits gradually at TP1, TP2, and TP3 while keeping the remainder running.
TrailingStop
Uses a dynamic stop loss that follows price as it moves in your favor.There is no fixed Take Profit; instead, the trailing stop locks in profit and exits the trade automatically when momentum reverses.
7.Automatic Alert System
This is the System that organizes all settings related to the automatic webhook alert creator inside the indicator.
Rule No. 1 is never lose money. Rule No. 2 is never forget Rule No. 1.
Warren Buffet
NeuraAlgo – Market Dynamics transforms complex market behavior into clear, actionable insights for smarter trading decisions.
Relative PerformanceCompare the relative and actual performance of up to 15 tickers against the current market being charted across multiple timeframes. Customisable look back periods and alerts configured. All data is displayed in a dynamic table for the market selected.
Shareline_Momentum_DataFeedupdated version for data feed indicator to feed data to other indicators and strategys.
Shareline_Momentum_DataFeed.V1.0This script is a data feed script which provides data to other indicators and strategys. It is the master to understand how indicators can work.
Leverage LineLeverage Line is an indicator represented by a simple line. This line corresponds to the average of three other values:
- The current price of the listed asset
- The average price calculated since the asset's listing based on TradingView data
- The equilibrium price between supply and demand
This indicator can be used on all assets. Regarding timeframes, they can be used on all of them, although the line's movements and position will not change in any case. However, if you want a broader view, you absolutely can. But for the best views, for bounces or breakout confirmations, I highly recommend the weekly timeframe, and occasionally the daily one as well, but the weekly one is truly the best.
I hope this indicator will allow you to better visualize where the price is supposed to be, and that you will adapt it to your trading or even create your own strategies with it.
Glebesqu,
Sincerely.
P/E, EPS, Price & Price-to-Sales DisplayPrice to earning ratio,
EPS,
Price ANd
Price-to-Sales Display
ATR multiple from High & LowA simple numerical indicator measuring ATR multiple from recent 252 days high and low.
ATR multiples from high (and low) are used as a base in many systematic trading and trend following systems. As an example many systems buy after a 2.5–4 ATR multiple pullback in a strong stock if the regime allows it. This would then be paired with an entry tactic, for example buy as it recaptures the a pivot within the upper range, a MA or breaks out again after this mid term pullback/shakeout.
This indicator uses a function which captures the recent high and low no matter if we have 252 bars or not, which is not how standard high/low works in Tradingview. This means it also works with recent IPO:s.
I prefer to overlay the indicator in one of the lower panes, for example the volume pane and then right click on the indicator and select Pin to scale > No scale (fullscreen).
Static K-means Clustering | InvestorUnknownStatic K-Means Clustering is a machine-learning-driven market regime classifier designed for traders who want a data-driven structure instead of subjective indicators or manually drawn zones.
This script performs offline (static) K-means training on your chosen historical window. Using four engineered features:
RSI (Momentum)
CCI (Price deviation / Mean reversion)
CMF (Money flow / Strength)
MACD Histogram (Trend acceleration)
It groups past market conditions into K distinct clusters (regimes). After training, every new bar is assigned to the nearest cluster via Euclidean distance in 4-dimensional standardized feature space.
This allows you to create models like:
Regime-based long/short filters
Volatility phase detectors
Trend vs. chop separation
Mean-reversion vs. breakout classification
Volume-enhanced money-flow regime shifts
Full machine-learning trading systems based solely on regimes
Note:
This script is not a universal ML strategy out of the box.
The user must engineer the feature set to match their trading style and target market.
K-means is a tool, not a ready made system, this script provides the framework.
Core Idea
K-means clustering takes raw, unlabeled market observations and attempts to discover structure by grouping similar bars together.
// STEP 1 — DATA POINTS ON A COORDINATE PLANE
// We start with raw, unlabeled data scattered in 2D space (x/y).
// At this point, nothing is grouped—these are just observations.
// K-means will try to discover structure by grouping nearby points.
//
// y ↑
// |
// 12 | •
// | •
// 10 | •
// | •
// 8 | • •
// |
// 6 | •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 2 — RANDOMLY PLACE INITIAL CENTROIDS
// The algorithm begins by placing K centroids at random positions.
// These centroids act as the temporary “representatives” of clusters.
// Their starting positions heavily influence the first assignment step.
//
// y ↑
// |
// 12 | •
// | •
// 10 | • C2 ×
// | •
// 8 | • •
// |
// 6 | C1 × •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 3 — ASSIGN POINTS TO NEAREST CENTROID
// Each point is compared to all centroids.
// Using simple Euclidean distance, each point joins the cluster
// of the centroid it is closest to.
// This creates a temporary grouping of the data.
//
// (Coloring concept shown using labels)
//
// - Points closer to C1 → Cluster 1
// - Points closer to C2 → Cluster 2
//
// y ↑
// |
// 12 | 2
// | 1
// 10 | 1 C2 ×
// | 2
// 8 | 1 2
// |
// 6 | C1 × 2
// |
// 4 | 1
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
// (1 = assigned to Cluster 1, 2 = assigned to Cluster 2)
// At this stage, clusters are formed purely by distance.
Your chosen historical window becomes the static training dataset , and after fitting, the centroids never change again.
This makes the model:
Predictable
Repeatable
Consistent across backtests
Fast for live use (no recalculation of centroids every bar)
Static Training Window
You select a period with:
Training Start
Training End
Only bars inside this range are used to fit the K-means model. This window defines:
the market regime examples
the statistical distributions (means/std) for each feature
how the centroids will be positioned post-trainin
Bars before training = fully transparent
Training bars = gray
Post-training bars = full colored regimes
Feature Engineering (4D Input Vector)
Every bar during training becomes a 4-dimensional point:
This combination balances: momentum, volatility, mean-reversion, trend acceleration giving the algorithm a richer "market fingerprint" per bar.
Standardization
To prevent any feature from dominating due to scale differences (e.g., CMF near zero vs CCI ±200), all features are standardized:
standardize(value, mean, std) =>
(value - mean) / std
Centroid Initialization
Centroids start at diverse coordinates using various curves:
linear
sinusoidal
sign-preserving quadratic
tanh compression
init_centroids() =>
// Spread centroids across using different shapes per feature
for c = 0 to k_clusters - 1
frac = k_clusters == 1 ? 0.0 : c / (k_clusters - 1.0) // 0 → 1
v = frac * 2 - 1 // -1 → +1
array.set(cent_rsi, c, v) // linear
array.set(cent_cci, c, math.sin(v)) // sinusoidal
array.set(cent_cmf, c, v * v * (v < 0 ? -1 : 1)) // quadratic sign-preserving
array.set(cent_mac, c, tanh(v)) // compressed
This makes initial cluster spread “random” even though true randomness is hardly achieved in pinescript.
K-Means Iterative Refinement
The algorithm repeats these steps:
(A) Assignment Step, Each bar is assigned to the nearest centroid via Euclidean distance in 4D:
distance = sqrt(dx² + dy² + dz² + dw²)
(B) Update Step, Centroids update to the mean of points assigned to them. This repeats iterations times (configurable).
LIVE REGIME CLASSIFICATION
After training, each new bar is:
Standardized using the training mean/std
Compared to all centroids
Assigned to the nearest cluster
Bar color updates based on cluster
No re-training occurs. This ensures:
No lookahead bias
Clean historical testing
Stable regimes over time
CLUSTER BEHAVIOR & TRADING LOGIC
Clusters (0, 1, 2, 3…) hold no inherent meaning. The user defines what each cluster does.
Example of custom actions:
Cluster 0 → Cash
Cluster 1 → Long
Cluster 2 → Short
Cluster 3+ → Cash (noise regime)
This flexibility means:
One trader might have cluster 0 as consolidation.
Another might repurpose it as a breakout-loading zone.
A third might ignore 3 clusters entirely.
Example on ETHUSD
Important Note:
Any change of parameters or chart timeframe or ticker can cause the “order” of clusters to change
The script does NOT assume any cluster equals any actionable bias, user decides.
PERFORMANCE METRICS & ROC TABLE
The indicator computes average 1-bar ROC for each cluster in:
Training set
Test (live) set
This helps measure:
Cluster profitability consistency
Regime forward predictability
Whether a regime is noise, trend, or reversion-biased
EQUITY SIMULATION & FEES
Designed for close-to-close realistic backtesting.
Position = cluster of previous bar
Fees applied only on regime switches. Meaning:
Staying long → no fee
Switching long→short → fee applied
Switching any→cash → fee applied
Fee input is percentage, but script already converts internally.
Disclaimers
⚠️ This indicator uses machine-learning but does not predict the future. It classifies similarity to past regimes, nothing more.
⚠️ Backtest results are not indicative of future performance.
⚠️ Clusters have no inherent “bullish” or “bearish” meaning. You must interpret them based on your testing and your own feature engineering.
Huli-Huli (Reversal) WindowHuli-Huli (Reversal) Time-Zone Highlighter
Huli (Hawaiian for "turn/flip") highlights specific time regions on your chart where price reversals and pivots are statistically more common during major trading sessions (Asian, London, NY).
This indicator identifies potential turning points based on historical session transitions and market behavior patterns. It does NOT predict or guarantee reversals - it simply marks time zones where pivots frequently occur.
When combined with key support/resistance levels, supply/demand zones, or other confluence factors, these highlighted periods may provide additional context for timing entries and exits.
Use this indicator as one piece of your trading puzzle, not as a standalone signal. Always combine with proper risk management and other technical analysis tools.
Note: Past performance and statistical tendencies do not guarantee future results. Trade responsibly.
***UTC Time should match EST - So depending on Daylight Savings or not you will want to select UTC 4 or UTC 5***
GVI-1 - Guendogan Valuation Index 1The Guendogan Valuation Index 1 (GVI-1) incorporates the total market capitalization of all U.S. companies, U.S. GDP, and the share of revenues generated outside the United States to provide an undistorted long-term valuation of the U.S. equity market across the past decades.
Disclaimer: The Guendogan Valuation Index 1 (GVI-1) is a research-based macro indicator provided solely for educational and informational purposes. It does not constitute financial advice, investment advice, trading advice, or a recommendation to buy or sell any asset. Financial markets involve risk, and past performance does not guarantee future results. All users are solely responsible for their own investment decisions.
Open Interest Anomaly DetectorOpen Interest Anomaly Indicator
This indicator is designed to detect anomalies in Open Interest (OI) and highlight moments when capital is aggressively entering or exiting the market.
The indicator plots raw Open Interest values as a column histogram. A moving average is applied to establish the baseline behavior of OI, while standard deviation bands define thresholds for abnormal deviations. These deviation levels can be customized in the settings.
When Open Interest rises above the upper deviation band, the indicator marks these events in green, signaling positive anomalies, often associated with sudden inflows of capital.
When Open Interest falls below the lower deviation band, it highlights these points in red, indicating negative anomalies, which may reflect capital leaving the market due to stop-loss triggers, take-profit executions, or liquidations.
It is important to note that Open Interest alone does not generate entry signals. Instead, it serves as a contextual layer, helping traders understand market dynamics and confirm other tools. For cleaner signals with reduced noise, we recommend using the indicator on the 15-minute timeframe.
Using Open Interest Together With Delta
The indicator becomes even more powerful when combined with Delta, providing clear insight into who is entering or exiting the market:
Delta > 0 and Open Interest rising → Long positions are entering the market.
Delta < 0 and Open Interest rising → Short positions are entering the market.
Open Interest falling (regardless of Delta) → Money is leaving the market; long or short positions are being closed, either by profit-taking or by forced exits.
This synergy between Open Interest and Delta offers a deeper understanding of market flow and can produce highly informative signals when used together.
Digital Credit Market ValueDigital Credit Frontier
Script for tracking total notional value and total market value for the Digital Credit Market. Needs be manually updated. You can open it twice to get the total value in one pane and the oscillator in the other pane.
