Swing Failure Signals [AlgoAlpha]🟠 OVERVIEW
This script detects swing failure patterns by tracking how price interacts with recent swing highs and lows, then confirming those sweeps with a change in candle behavior. The goal is to highlight areas where price briefly breaks a key level, fails to continue, and then shifts direction. These events often occur around liquidity runs, where stops are triggered before price reverses. The script draws levels, colors bars, and prints clear markers to help visualize where these failures occur and when they are confirmed.
🟠 CONCEPTS
The logic starts with pivot-based swing detection. Recent swing highs and lows are stored and monitored. When price trades beyond one of these levels within a defined historical window, it is treated as a sweep. A sweep alone is not enough. The script then waits for a Change in State of Delivery (CISD), which is defined by a shift in candle structure that shows follow-through in the opposite direction. A tolerance filter measures how far price traveled beyond the level relative to the reaction that followed. If the reaction is strong enough and happens within a limited number of bars, the sweep is validated as a swing failure. In short: the swing defines the reference, the sweep shows intent, and the CISD confirms acceptance or rejection.
🟠 FEATURES
Sweep detection with a maximum lookback to avoid outdated levels
CISD confirmation using candle structure and price expansion
Alert conditions for bullish and bearish swing failures
🟠 USAGE
Setup : Add the script to your chart. It works on any market and timeframe. Lower timeframes highlight intraday liquidity runs, while higher timeframes show structural failures. Start with the default inputs before adjusting.
Read the chart : A bullish swing failure occurs when price sweeps a prior low, then reverses and confirms with a bullish CISD. A bearish swing failure is the opposite, sweeping a prior high and confirming with a bearish CISD. Dashed lines mark the swept swing. Solid lines mark the CISD level. Bars are colored while the SFP state is active.
Settings that matter : Increasing Pivot Detection Length finds more significant swings but fewer signals. Reducing Max Pivot Point Edge limits how far back sweeps are allowed, keeping signals more current. The Patience setting controls how many bars are allowed for confirmation after a sweep. The Trend Noise Filter raises or lowers how strong the reaction must be to qualify as a valid failure.
Indicators and strategies
Volume-Weighted Price Z-Score [QuantAlgo]🟢 Overview
The Volume-Weighted Price Z-Score indicator quantifies price deviations from volume-weighted equilibrium using statistical standardization. It combines volume-weighted moving average analysis with logarithmic deviation measurement and volatility normalization to identify when prices have moved to statistically extreme levels relative to their volume-weighted baseline, helping traders and investors spot potential mean reversion opportunities across multiple timeframes and asset classes.
🟢 How It Works
The indicator's core methodology lies in its volume-weighted statistical approach, where price displacement is measured through normalized deviations from volume-weighted price levels:
volumeWeightedAverage = ta.vwma(priceSource, lookbackPeriod)
logDeviation = math.log(priceSource / volumeWeightedAverage)
volatilityMeasure = ta.stdev(logDeviation, lookbackPeriod)
The script uses logarithmic transformation to capture proportional price changes rather than absolute differences, ensuring equal treatment of percentage moves regardless of price level:
rawZScore = logDeviation / volatilityMeasure
zScore = ta.ema(rawZScore, smoothingPeriod)
First, it establishes the volume-weighted baseline which gives greater weight to price levels where significant trading occurred, creating a more representative equilibrium point than simple moving averages.
Then, the logarithmic deviation measurement converts the price-to-average ratio into a normalized scale:
logDeviation = math.log(priceSource / volumeWeightedAverage)
Next, statistical normalization is achieved by dividing the deviation by its own historical volatility, creating a standardized z-score that measures how many standard deviations the current price sits from the volume-weighted mean.
Finally, EMA smoothing filters noise while preserving the signal's responsiveness to genuine market extremes:
rawZScore = logDeviation / volatilityMeasure
zScore = ta.ema(rawZScore, smoothingPeriod)
This creates a volume-anchored statistical oscillator that combines price-volume relationship analysis with volatility-adjusted normalization, providing traders with probabilistic insights into market extremes and mean reversion potential based on standard deviation thresholds.
🟢 Signal Interpretation
▶ Positive Values (Above Zero): Price trading above volume-weighted average indicating potential overvaluation relative to volume-weighted equilibrium = Caution on longs, potential mean reversion downward = Short/sell opportunities
▶ Negative Values (Below Zero): Price trading below volume-weighted average indicating potential undervaluation relative to volume-weighted equilibrium = Caution on shorts, potential mean reversion upward = Long/buy opportunities
▶ Zero Line Crosses: Mean reversion transitions where price crosses back through volume-weighted equilibrium, indicating shift from overvalued to undervalued (or vice versa) territory
▶ Extreme Positive Zone (Above +2.5σ default): Statistically rare overvaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bullish conditions with high mean reversion probability = Strong correction warning/short signal
▶ Extreme Negative Zone (Below -2.5σ default): Statistically rare undervaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bearish conditions with high mean reversion probability = Strong buying opportunity signal
▶ ±1σ Reference Levels: Moderate deviation zones (±1 standard deviation) marking common price fluctuation boundaries where approximately 68% of price action occurs under normal distribution
▶ ±2σ Reference Levels: Significant deviation zones (±2 standard deviations) marking unusual price extremes where approximately 95% of price action should be contained under normal conditions
🟢 Features
▶ Preconfigured Presets: Three optimized parameter sets accommodate different analytical approaches, instruments and timeframes. "Default" provides balanced statistical measurement suitable for swing trading and daily/4-hour analysis, offering deviation detection with moderate responsiveness to price dislocations. "Fast Response" delivers heightened sensitivity optimized for intraday trading and scalping on 15-minute to 1-hour charts, using shorter statistical windows and minimal smoothing to capture rapid mean reversion opportunities as they develop. "Smooth Trend" offers conservative extreme identification ideal for position trading on daily to weekly charts, employing extended statistical periods and heavy noise filtering to isolate only the most significant market extremes.
▶ Built-in Alerts: Seven alert conditions enable comprehensive automated monitoring of statistical extremes and mean reversion events. Extreme Overbought triggers when z-score crosses above the extreme threshold (default +2.5σ) signaling rare overvaluation, Extreme Oversold activates when z-score crosses below the negative extreme threshold (default -2.5σ) signaling rare undervaluation. Exit Extreme Overbought and Exit Extreme Oversold alert when prices begin reverting from these statistical extremes back toward the mean. Bullish Mean Reversion notifies when z-score crosses above zero indicating shift to overvalued territory, while Bearish Mean Reversion triggers on crosses below zero indicating shift to undervalued territory. Any Extreme Level provides a combined alert for any extreme threshold breach regardless of direction. These notifications allow you to capitalize on statistically significant price dislocations without continuous chart monitoring.
▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast for identifying positive versus negative deviations across trading environments. The adjustable fill transparency control (0-100%) allows fine-tuning of the gradient area prominence between the z-score line and zero baseline, with higher opacity values creating subtle background context while lower values produce bold deviation emphasis. Optional bar coloring extends the z-score gradient directly to the indicator pane bars, providing immediate visual reinforcement of current deviation magnitude and direction without requiring reference to the plotted line itself.
*Note: This indicator requires volume data to function correctly, as it calculates deviations from a volume-weighted price average. Tickers with no volume data or extremely limited volume will not produce meaningful results, i.e., the indicator may display flat lines, erratic values, or fail to calculate properly. Using this indicator on assets without volume data (certain forex pairs, synthetic indices, or instruments with unreported/unavailable volume) will produce unreliable or no results at all. Additionally, ensure your chart has sufficient historical data to cover the selected lookback period, e.g., using a 100-bar lookback on a chart with only 50 bars of history will yield incomplete or inaccurate calculations. Always verify your chosen ticker has consistent, accurate volume information and adequate price history before applying this indicator.
Chainbey Ai - HTF Trend Matrix (Clean)Chainbey Ai – HTF Trend Matrix is a professional, higher-timeframe trend detection indicator designed to give traders a clean, reliable market bias, regardless of the chart timeframe they are trading on.
This indicator automatically analyzes multiple higher timeframes (HTFs) and combines:
EMA trend direction
Trend strength (ADX)
Market structure (trend vs range)
Trend disagreement across HTFs
Reversal probability estimation
All results are displayed in a compact table at the bottom-right, making it perfect for scalpers, day traders, and swing traders who need fast, decision-ready information.
🧠 What This Indicator Solves
❌ No more guessing the higher-timeframe trend
❌ No more trading against the main market bias
❌ No more confusion between trend vs range
✅ Clear BULLISH / BEARISH / RANGE bias
✅ Strength score to avoid weak trends
✅ Reversal probability to manage risk
📊 How to Read the Table (User Manual)
🔹 FINAL Row
Example:
FINAL | BEARISH TREND | -46
Text (BEARISH / BULLISH / RANGE) → Overall market bias
Number (-46) → Trend Strength Score
Trend Score Guide:
Score Meaning
0 to ±20 No trend / Choppy
±20 to ±40 Weak trend
±40 to ±70 Healthy trend
±70+ Very strong / extended trend
📌 Negative = Bearish
📌 Positive = Bullish
🔹 REVERSAL – Possibility (%)
Example:
REVERSAL | Possibility | 45%
This shows the chance of trend exhaustion or reversal.
Reversal % Meaning
0–30% Strong trend continuation
30–50% Normal pullback risk
50%+ High reversal probability
70%+ Dangerous to chase trades
📌 Use this to avoid late entries.
🔹 HTF Rows (60 / 240 / D)
Each row shows:
DIR / STRUCT
Direction from EMA trend
Market structure (TREND / RANGE)
ADX
Trend strength
STRONG / MEDIUM / CHOP
📌 If multiple HTFs agree → higher confidence
📌 If HTFs conflict → reduce position size or wait
🛠 Recommended Trading Usage
✅ Best Practices
Trade in the direction of FINAL trend
Enter on pullbacks, not breakouts
Use lower timeframes only for entries
❌ Avoid
Trading against FINAL bias
Chasing trades when reversal % is high
Over-leveraging in CHOP conditions
🎯 Ideal For
Crypto traders (Spot & Futures)
Forex traders
Gold / Commodity traders
Scalping, Intraday & Swing trading
⚠️ Disclaimer
This indicator is a decision-support tool, not financial advice. Always combine it with proper risk management, confirmations, and your trading plan.
Power Hour Trendlines [LuxAlgo]The Power Hour Trendlines indicator is based on Power Hours detection, and includes up to three displayed trendlines derived from the closing prices of all the bars within the last user-selected Power Hours.
Users can edit the time of Power Hours, choose how many sessions to take into account, enable or disable any trendlines, and change their colors.
🔶 USAGE
The Power Hour is defined as the last hour of the trading session and is set by default from 3:00 p.m. to 4:00 p.m. New York time. During this period, volume and volatility enter the market. Traders using higher timeframes may use this period to enter or exit positions by placing MOC (Market on Close) orders.
This tool works under the hypothesis that prices made during power hours (periods with high trading activity) are more relevant when used for the construction of trendlines.
An initial trendline is fit using linear regression; prices from power hours located above this initial fit are used for the upper trendline, while the ones below the fit are used for the lower one.
As with any trendline, traders can analyze the slope to determine the market's direction:
Positive slope: The market is trending up.
Negative slope: The market is trending down.
No slope: The market is trending sideways.
As we can see in the image, Nasdaq and Bitcoin are clearly in downtrends, gold is clearly in an uptrend, and the euro/U.S. dollar is in a sideways market over the last visible sessions.
As you can see, the trend lines may or may not be parallel to each other. The wider the area, the more volatile the data. The narrower the area, the less volatile the data. Let's look at an example.
In the image, the Dow30 and the euro/U.S. dollar have opposite behaviors. The volatility above the middle trendline is growing in the first case but shrinking in the second. In both cases, the volatility in the bottom area seems steady, so there are no big surprises there.
Traders can adjust the number of sessions for calculations, making the tool ideal for analyzing price behavior over different time frames.
As the image shows, we can clearly see how the market behaves over different time periods. XLY has been moving down over the last 10, 20, and 40 sessions, with a steeper decline over shorter periods. However, it has been moving sideways over the last 70 sessions.
One of the main uses of trendlines is to provide key support and resistance. In the image, SPY is shown with trendlines over the last 20 sessions. These lines provide excellent reference points for trading and observing price behavior in those areas, such as whether prices are accepted or rejected, which may trigger a response from other traders.
🔹 Not Allowed Timeframes
For obvious reasons, timeframes larger than 1H are not allowed. The Power Hour is defined as the last hour of the trading session. The tool will display a warning message if the timeframe is longer than 60 minutes.
🔶 SETTINGS
Power Hour (NY Time): Choose a custom Power Hour in New York time
Sessions Memory: Select how many Power Hours to take into account for calculations.
🔹 Style
Top: Enable or disable the top line and choose the line and background colors.
Middle: Enable or disable the middle line and choose the line color.
Bottom: Enable or disable the bottom line and choose the line and background colors.
Background: Enable or disable the background color for top and bottom lines.
Adaptive Trend Envelope [BackQuant]Adaptive Trend Envelope
Overview
Adaptive Trend Envelope is a volatility-aware trend-following overlay designed to stay responsive in fast markets while remaining stable during slower conditions. It builds a dynamic trend spine from two exponential moving averages and surrounds it with an adaptive envelope whose width expands and contracts based on realized return volatility. The result is a clean, self-adjusting trend structure that reacts to market conditions instead of relying on fixed parameters.
This indicator is built to answer three core questions directly on the chart:
Is the market trending or neutral?
If trending, in which direction is the dominant pressure?
Where is the dynamic trend boundary that price should respect?
Core trend spine
At the heart of the indicator is a blended trend spine:
A fast EMA captures short-term responsiveness.
A slow EMA captures structural direction.
A volatility-based blend weight dynamically shifts influence between the two.
When short-term volatility is low relative to long-term volatility, the fast EMA has more influence, keeping the trend responsive. When volatility rises, the blend shifts toward the slow EMA, reducing noise and preventing overreaction. This blended output is then smoothed again to form the final trend spine, which acts as the structural backbone of the system.
Volatility-adaptive envelope
The envelope surrounding the trend spine is not based on ATR or fixed percentages. Instead, it is derived from:
Log returns of price.
An exponentially weighted variance estimate.
A configurable multiplier that scales envelope width.
This creates bands that automatically widen during volatile expansions and tighten during compression. The envelope therefore reflects the true statistical behavior of price rather than an arbitrary distance.
Inner hysteresis band
Inside the main envelope, an inner band is constructed using a hysteresis fraction. This inner zone is used to stabilize regime transitions:
It prevents rapid flipping between bullish and bearish states.
It allows trends to persist unless price meaningfully invalidates them.
It reduces whipsaws in sideways conditions.
Trend regime logic
The indicator operates with three regime states:
Bullish
Bearish
Neutral
Regime changes are confirmed using a configurable number of bars outside the adaptive envelope:
A bullish regime is confirmed when price closes above the upper envelope for the required number of bars.
A bearish regime is confirmed when price closes below the lower envelope for the required number of bars.
A trend exits back to neutral when price reverts through the trend spine.
This structure ensures that trends are confirmed by sustained pressure rather than single-bar spikes.
Active trend line
Once a regime is active, the indicator plots a single dominant trend line:
In a bullish regime, the lower envelope becomes the active trend support.
In a bearish regime, the upper envelope becomes the active trend resistance.
In neutral conditions, price itself is used as a placeholder.
This creates a simple, actionable visual reference for trend-following decisions.
Directional energy visualization
The indicator uses layered fills to visualize directional pressure:
Bullish energy fills appear when price holds above the active trend line.
Bearish energy fills appear when price holds below the active trend line.
Opacity gradients communicate strength and persistence rather than binary states.
A subtle “rim” effect is added using ATR-based offsets to give depth and reinforce the active side of the trend without cluttering the chart.
Signals and trend starts
Discrete signals are generated only when a new trend regime begins:
Buy signals appear at the first confirmed transition into a bullish regime.
Sell signals appear at the first confirmed transition into a bearish regime.
Signals are intentionally sparse. They are designed to mark regime shifts, not every pullback or continuation, making them suitable for higher-quality trend entries rather than frequent trading.
Candle coloring
Optional candle coloring reinforces regime context:
Bullish regimes tint candles toward the bullish color.
Bearish regimes tint candles toward the bearish color.
Neutral states remain visually muted.
This allows the chart to communicate trend state even when the envelope itself is partially hidden or de-emphasized.
Alerts
Built-in alerts are provided for key trend events:
Bull trend start.
Bear trend start.
Transition from trend to neutral.
Price crossing the trend spine.
These alerts support hands-off trend monitoring across multiple instruments and timeframes.
How to use it for trend following
Trend identification
Only trade in the direction of the active regime.
Ignore counter-trend signals during confirmed trends.
Entry alignment
Use the first regime signal as a structural entry.
Use pullbacks toward the active trend line as continuation opportunities.
Trend management
As long as price respects the active envelope boundary, the trend remains valid.
A move back through the spine signals loss of trend structure.
Market filtering
Periods where the indicator remains neutral highlight non-trending environments.
This helps avoid forcing trades during chop or compression.
Adaptive Trend Envelope is designed to behave like a living trend structure. Instead of forcing price into static rules, it adapts to volatility, confirms direction through sustained pressure, and presents trend information in a clean, readable form that supports disciplined trend-following workflows.
CandleStix Pro Description
CandleStix scans for all major candlestick patterns including single-bar patterns (doji, hammer, shooting star, pin bars), two-bar patterns (engulfing, harami, piercing, dark cloud), and three-bar patterns (morning star, evening star, three soldiers, three crows).
Waves UltimateWaves Ultimate is a comprehensive Elliott Wave analysis tool designed to assist traders in identifying and validating wave structures in real-time. This indicator combines automatic wave detection with strict Elliott Wave rule validation, Fibonacci projections, and visual wave labeling to provide a complete wave analysis suite.
Fair Value Gaps w Signals fair value gaps for resistance and support. It is important to understand ranges with this. An open bearish fair value gaps can indicate a bearish range. A bullish fair value gaps in premium can indicate retracement into the bearish range. A fair value gaps on a high time frame in discount of the range can be a indicator to go long. one can play the fair value gaps in discount or a range back into it for longs. negation of the fair value gaps candle bearish or bullish is stop loss. One would want to see a small time frame turn around story within the fair value gaps you are trading. FVG are support and resistance until the market is balanced. A bearish fair value gaps untouched can indicate the end of a range. The candle before the 1st bullsih fair value gaps could be the beginning of the range. all time frames
Percentile-Based BB% Trend - MattesOverview
The Percentile-Based BB% Trend is a robust momentum oscillator that reimagines the classic Bollinger %B indicator using percentile-based bands and median absolute deviation (MAD). Instead of relying on a simple moving average and standard deviation (which can be heavily influenced by outliers), this version builds dynamic bands from the 25th and 75th percentiles of price, creating a noise-resistant framework for measuring where the current price sits relative to its recent distribution.
How It’s Calculated
Percentile Smoothing : 25th percentile (lower boundary) and 75th percentile (upper boundary) of the selected source.
Basis Line : Midpoint between the 25th and 75th percentiles as a robust central measure.
Robust Volatility : Median Absolute Deviation (MAD) multiplied by a user-defined factor to set band width.
PBB% Value : (Price - Lower Band) / (Band Width), then shifted so the midline is at 0.
Trend Line : Light EMA smoothing applied to the raw value and displayed as colored columns.
How It Differs From Traditional %B
Uses 25th/75th percentiles + MAD instead of SMA + standard deviation → far less sensitive to outliers.
More adaptive to real-world skewed price distributions.
Stronger noise filtering while staying responsive to genuine momentum.
Why It’s Useful
Reduced false signals in choppy or spiky markets
Clear view of momentum strength and price extension
Persistent readings above/below 0 indicate sustained bullish/bearish control
Excellent as a trend-strength filter across all asset classes and timeframes
Application Examples
Trend Confirmation – Midline (0) crossovers confirm direction when paired with trend-following tools.
Overextension Warnings – Extreme readings signal potential exhaustion.
Momentum Filtering – Avoid entries when oscillator shows weak or overstretched conditions.
Divergence Hunting – Spot price making new highs/lows while oscillator fails to confirm.
Great inventions require greate care!
Not a Standalone Strategy: This indicator is designed as a complementary tool and should always be combined with other forms of analysis (price action, volume, higher-timeframe trend, or additional indicators).Potential Lags in Explosive Moves: The robust calculations and smoothing can slightly delay signals during very strong trends.Parameter Sensitivity: Optimal length and multiplier vary by market and timeframe — backtesting is essential.No indicator guarantees profits; past performance is not indicative of future results.
This indicator builds directly on the foundation of the Percentile-Based Bollinger Bands - Mattes, extending its robust methodology into oscillator form for deeper momentum analysis.Shoutout to all my Masterclass Brothers and L4 Gs!
VMDivergences◈ DIVERGENCE DETECTION SYSTEM ◈
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█ 🎯 OVERVIEW █
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VMDiv is a professional-grade divergence detection system built on a unique
hybrid oscillator that combines the best of momentum analysis and mean-reversion
theory. Unlike standard divergence indicators that rely on RSI or MACD, this
system uses a custom Volume Momentum oscillator with adjustable characteristics.
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🔧 THE VM OSCILLATOR ENGINE
═════════════════════════════════════════════════════════════
The core innovation is a hybrid oscillator combining TWO analytical approaches:
┌──────────────────────────────────────────────────────┐
│ COMPONENT 1: EMA MOMENTUM │
│ ════════════════════════ │
│ • Fast EMA minus Slow EMA (similar to MACD) │
│ • Normalized by standard deviation for consistency │
│ • Captures trend strength and directional momentum │
├─────────────────────────────────────────────────────────┤
│ COMPONENT 2: BOLLINGER BAND DISTANCE │
│ ════════════════════════════════════ │
│ • Price distance from Bollinger Band midline │
│ • Normalized to show position within bands (-1 to +1 typically) │
│ • Captures overextension and mean-reversion potential │
├─────────────────────────────────────────────────────────┤
│ THE BLEND │
│ ════════════ │
│ • "Momentum Blend" parameter controls the mix │
│ • 1.0 = Pure momentum oscillator │
│ • 0.0 = Pure mean-reversion oscillator │
│ • 0.5 = Balanced hybrid (often optimal) │
└───────────────────────────────────────────────────┘
═══════════════════════════════════════════════════════
📊 DIVERGENCE TYPES DETECTED
══════════════════════════════════════════════════════
This indicator detects SIX types of divergence patterns:
┌───────────────────────────────────────────────────────┐
│ 🔴 REGULAR BEARISH DIVERGENCE │
│ ══════════════════════════════ │
│ Price: Makes HIGHER HIGH ↗ │
│ Oscillator: Makes LOWER HIGH ↘ │
│ │
│ Interpretation: Momentum is weakening despite higher prices. │
│ Signal: Potential reversal to the DOWNSIDE │
│ Reliability: HIGH - Classic reversal signal at tops │
├────────────────────────────────────────────────────────┤
│ 🟢 REGULAR BULLISH DIVERGENCE │
│ ══════════════════════════════ │
│ Price: Makes LOWER LOW ↘ │
│ Oscillator: Makes HIGHER LOW ↗ │
│ │
│ Interpretation: Momentum is strengthening despite lower prices. │
│ Signal: Potential reversal to the UPSIDE │
│ Reliability: HIGH - Classic reversal signal at bottoms │
├──────────────────────────────────────────────────┤
│ 🟠 HIDDEN BEARISH DIVERGENCE │
│ ════════════════════════════ │
│ Price: Makes LOWER HIGH ↘ │
│ Oscillator: Makes HIGHER HIGH ↗ │
│ │
│ Interpretation: Downtrend showing internal strength. │
│ Signal: Trend CONTINUATION - expect further downside │
│ Best used: During confirmed downtrends │
├──────────────────────────────────────────────────────┤
│ 🟡 HIDDEN BULLISH DIVERGENCE │
│ ════════════════════════════ │
│ Price: Makes HIGHER LOW ↗ │
│ Oscillator: Makes LOWER LOW ↘ │
│ │
│ Interpretation: Uptrend showing internal strength. │
│ Signal: Trend CONTINUATION - expect further upside │
│ Best used: During confirmed uptrends │
├───────────────────────────────────────────────────┤
│ 🟣 DOUBLE TOP DIVERGENCE │
│ ═════════════════════════ │
│ Price: Two SIMILAR HIGHS (within ATR tolerance) │
│ Oscillator: Second high LOWER than first │
│ │
│ Interpretation: Resistance tested twice with weakening momentum. │
│ Signal: Strong reversal setup - HIGH PROBABILITY bearish │
│ Best used: At major resistance levels │
├───────────────────────────────────────────────────────────┤
│ 🔵 DOUBLE BOTTOM DIVERGENCE │
│ ═══════════════════════════ │
│ Price: Two SIMILAR LOWS (within ATR tolerance) │
│ Oscillator: Second low HIGHER than first │
│ │
│ Interpretation: Support tested twice with strengthening momentum. │
│ Signal: Strong reversal setup - HIGH PROBABILITY bullish │
│ Best used: At major support levels │
└──────────────────────────────────────────────────┘
PKS INDIA RSI + VWAP Multi TF Strategy (Backtest)🔥 Strategy Logic
Indicator दो Timeframes पर Market Strength चेक करता है:
SELL Condition
RSI (1 Hour) < 50
RSI (15 Minute) < 50
Price VWAP के नीचे हो
Price VWAP के पास आए (Pullback)
Bearish Confirmation Candle बने
BUY Condition
RSI (1 Hour) > 50
RSI (15 Minute) > 50
Price VWAP के ऊपर हो
Price VWAP के पास आए (Pullback)
Bullish Confirmation Candle बने
इससे Indicator केवल वही Signals देता है जहाँ Market में Clear Direction + Strong Momentum + Smart Entry Point मिलता है।
🎯 Best Timeframe
✔️ Recommended: 15 Minute Chart
✔️ Works on: Forex, Crypto, Indices, Commodities, Stocks
Apex Adaptive TrailApex Adaptive Trail: Adaptive Volatility Trend System
This custom trend-following indicator improves on standard SuperTrend implementations by addressing two key weaknesses: excessive whipsaws during high volatility and false signals in ranging markets.
Core Logic:
- Synthetic Heikin Ashi values are calculated internally (without changing chart candles) to provide smoother source data for trend detection.
- ATR-based trailing stop with adaptive multiplier: dynamically adjusts between 0.8x and 1.5x the base factor based on current volatility (ATR / 50-period SMA of ATR). Widens in volatile conditions, tightens in quiet markets.
- Weighted Confluence Score (0-100%): Combines four independent filters, each contributing 25%:
• Price position relative to 21-period EMA (trend alignment)
• ADX > 20 (momentum strength)
• Choppiness Index < 60 (trending vs ranging detection)
• Alignment with Daily EMA(50) trend direction
Signals are only generated when price crosses the adaptive trail AND the confluence score exceeds 75% (standard) or 90% (MAX 🔥 ultra-strong). This combination significantly reduces low-quality entries compared to traditional SuperTrend crossovers.
Key Features:
- Dynamic confidence cloud (opacity based on score)
- Real-time dashboard showing volatility state, active filters, trend bias, and estimated historical win rate
- Optional dynamic/fixed profit targets
- Fully customizable filters and adaptive behavior
Usage: Best on 15m to 4H timeframes for trend-following strategies (Crypto, Forex, Indices). Enter on APEX signals, use trail as stop-loss, TP lines for partial exits.
This script integrates established concepts into a unique adaptive framework with volatility-responsive risk management and multi-filter validation.
Disclaimer: For educational and analysis purposes only. Past performance is not indicative of future results. Always use proper risk management.
"This script combines established indicators (ATR trailing, ADX, Choppiness Index, EMA, MTF) into a unique adaptive system with dynamic volatility adjustment and weighted confluence scoring – features not found together in standard SuperTrend variations."
Vdubus Momentum Lock (Overlay)The Top Indicator: "Vdubus Momentum Lock (Overlay)"
The Bottom Indicator: "Vdubus TrixStoch HMA"
Purpose: Precision timing. It shows you exactly when the pullbacks happen.
The Trigger Zones (48 / 52):
Buy Zone (Below 48): When the Blue line dips into this zone, the market is "reloading" for a buy.
Sell Zone (Above 52): When the Blue line pops into this zone, the market is "reloading" for a sell.
The Confluence Circles:
Green Dot ("Dip"): Appears only if HMA is Green AND Trix is Rising. This filters out bad buy signals during downtrends.
Red Dot ("Rally"): Appears only if HMA is Red AND Trix is Falling. This filters out bad sell signals during uptrends.
3. The Strategy:
A. Entry Logic (The Sniper)
Trend Check: Is HMA 100 Green or Red?
Momentum Check: Is TRIX 34 agreeing with the HMA?
Trigger:
Buy: Stoch K crosses under 48.
Sell: Stoch K crosses over 52.
Pulse Re-Entry: If Trix momentum was lost briefly but snaps back into alignment, re-enter immediately (even without a Stoch signal).
B. Exit Logic (The Safety)
Momentum Exit: If the TRIX slope flips against you (e.g., you are Long, but Trix turns down), CLOSE IMMEDIATELY.
Hard Deck (HMA Flip): If the HMA line changes color, CLOSE EVERYTHING. This is the emergency brake.
Volume MAs Cloud Trend | Lyro RSVolume MAs Cloud Trend is a volume-weighted trend-following indicator designed to identify market direction, momentum strength, and dynamic trade management directly on price. By combining volume-adjusted moving averages, adaptive deviation bands, and an integrated ATR trailing stop, it delivers clear visual trend structure and actionable signals in a single overlay.
Key Features
Volume-Adjusted Moving Average
Uses a normalized formula: (Price × Volume) MA ÷ Volume MA, ensuring high-participation price moves carry greater influence. Supports 16+ MA types, with VWMA handled natively.
Deviation Band Cloud
Upper and lower bands are built from standard deviation over the MA length, scaled by independent positive and negative multipliers to adapt to volatility.
Cloud & Trail Modes
Cloud Mode visualizes trend structure using a filled band cloud.
Trail Mode switches to an ATR-based trailing stop for trend management.
Automatic Trend Signals
Bullish signals trigger when price crosses above the positive band.
Bearish signals trigger when price crosses below the negative band.
ATR Trailing Stop (Built-In)
A volatility-adjusted trailing stop initializes on each new trend and updates only in the trade direction, helping lock in gains while staying with the trend.
Custom Visuals & Palettes
Choose from Classic, Mystic, Accented, or Royal palettes, or define your own bullish and bearish colors. Includes MA glow, trend cloud fill, and trend-colored candles.
How It Works
MA Construction
Applies the selected moving average to volume-weighted price (or VWMA when selected) to create a participation-aware trend baseline.
Band Calculation
Calculates rolling standard deviation and offsets it using user-defined multipliers to form adaptive upper and lower trend bands.
Trend Detection
Crosses above the upper band confirm bullish momentum.
Crosses below the lower band confirm bearish momentum.
Trailing Stop Logic
On each new trend signal, an ATR-based trailing stop is initialized and dynamically updated in the trend direction.
Visual Synchronization
MA, cloud, trailing stop, and candles all change color in real time to reflect the current trend state.
Practical Use
Trend Confirmation
Sustained price action outside the cloud indicates strong directional momentum.
Breakout Identification
Band crosses highlight potential trend starts, especially when aligned with volatility expansion.
Trade Management
Trail Mode provides objective, volatility-based exits for trend-following strategies.
Quick Market Scanning
Color-coded candles and cloud structure allow fast visual assessment across multiple symbols and timeframes.
Customization
Adjust MA type and length to control responsiveness
Tune band multipliers for volatility sensitivity
Switch between Cloud and Trail modes depending on strategy
Customize color schemes to match your chart layout
⚠️ Disclaimer
This indicator is intended for technical analysis and educational purposes only. It does not guarantee results and should be used alongside proper risk management and additional analysis. The creator is not responsible for any financial decisions made using this tool.
Optimus S/R ZonesEnhanced S/R Zones Pro is a sophisticated Support and Resistance indicator designed for traders who need reliable, validated S/R levels with professional-grade visualization. Unlike basic pivot indicators, this tool validates levels based on historical price interaction and provides comprehensive analysis of your current position within the market structure.
✨ Key Features
📊 Extended Lookback Analysis
Lookback Range: 20-500 bars (far beyond standard 80-bar limits)
Pivot Strength: Adjustable 2-10 bars for confirmation
Separate Controls: Independent max levels for support (1-8) and resistance (1-8)
Smart Filtering: Automatic level spacing with customizable minimum distance (0.3-5%)
🎨 Advanced Zone Visualization
Three Zone Styles:
Filled: Solid colored zones
Outlined: Border-only zones
Both: Combined for maximum visibility
Adjustable Transparency: 50-95% opacity control
Dynamic Extension: Zones extend to the right indefinitely
Custom Zone Width: 0.05-1.0% of price
💪 Level Strength System
Touch Validation: Only shows levels tested multiple times
Minimum Touches: Filter for 1-5 minimum confirmations
Color Intensity: Stronger levels (more touches) display darker/brighter
Touch Detection: Customizable sensitivity (0.1-1.0% range)
Independent Display: Show touch counts without color coding
📱 Enhanced Dashboard
Level Count: Active support/resistance zones
Distance Metrics: Percentage to nearest S/R levels
Range Position: Where price sits between S/R (0-100%)
Color Coding: Visual feedback on market position
Four Positions: Top/Bottom, Left/Right placement
🎭 Customizable Visuals
Label Sizes: Tiny, Small, Normal, Large, Huge
Adjustable Line Width: 1-4 pixels
Custom Colors: Full color picker for support/resistance
Optional Touch Count: Toggle touch numbers on/off
Midpoint Line: Shows equilibrium between nearest S/R
🔔 Smart Alerts
Proximity Alerts: Triggers when approaching support zones
Resistance Alerts: Triggers when nearing resistance zones
Customizable Range: Based on touch detection sensitivity
🔧 How It Works
1. Pivot Detection
The indicator scans historical price action using configurable pivot strength to identify significant highs and lows. Extended lookback allows detection of major structural levels that shorter timeframes might miss.
2. Touch Validation
Each potential level is validated by counting how many times price has tested it within the specified touch detection range. Only levels meeting the minimum touch threshold are displayed.
3. Strength Ranking
Levels are ranked by:
Number of touches (primary)
Proximity to current price (secondary)
This ensures the most reliable and relevant levels are always shown.
4. Smart Filtering
The minimum distance filter prevents level clustering, keeping your chart clean and focusing only on distinct, actionable zones.
💡 Use Cases
Swing Trading
Identify major support/resistance for position entries
Set profit targets at strong resistance levels
Place stops below validated support zones
Day Trading
Quick identification of intraday S/R
Monitor range position for mean reversion trades
Use proximity alerts for entry timing
Position Trading
Extended lookback reveals major structural levels
Touch count validation ensures reliability
Range position helps time accumulation/distribution
Risk Management
Distance metrics help size positions appropriately
Strong levels (high touch count) for tight stops
Midpoint line for partial profit taking
⚙️ Settings Guide
Core Settings
Lookback Period: Start with 100 for swing trading, 50 for day trading
Pivot Strength: Higher values = fewer but stronger levels
Max Levels: 2-3 support and 2-3 resistance recommended
Min Distance: 1.0% prevents clustering, increase for volatile assets
Zone Settings
Zone Width: 0.25% default works well for most assets
Zone Style: "Both" for maximum visibility
Extend Zones: Keep enabled to track levels forward
Transparency: 85% provides good visibility without clutter
Level Strength
Show Level Strength: Enable for color-coded importance
Min Touches: 2-3 for validated levels
Touch Detection: 0.3% for precise levels, increase for volatile markets
Visual Settings
Label Size: Small/Normal for most charts
Show Touch Count: Enable to see level validation
Line Width: 2 for standard, 3-4 for presentation charts
📈 Best Practices
Start Conservative: Begin with default settings, adjust based on asset volatility
Combine Timeframes: Use different lookback periods on multiple charts
Respect Strong Levels: Higher touch counts indicate institutional interest
Watch Range Position: <30% = near support, >70% = near resistance
Use Alerts: Set proximity alerts to avoid constant chart watching
Validate Breaks: Zone width shows where true breaks occur vs. fakeouts
🚀 What Makes This Different
Unlike basic pivot indicators that simply mark highs/lows:
✅ Validates levels through touch count analysis
✅ Ranks levels by actual strength, not just recency
✅ Visualizes zones, not just lines
✅ Quantifies your position within market structure
✅ Extends lookback far beyond standard limits
✅ Separates support and resistance controls
🎓 Tips for New Users
First Time Setup:
Add indicator to chart
Enable dashboard in settings (default on)
Observe which levels price respects
Adjust lookback/strength to match your trading style
Set proximity alerts for your key levels
Optimization:
Forex: 0.2-0.3% zone width, 100-200 lookback
Stocks: 0.3-0.5% zone width, 50-150 lookback
Crypto: 0.4-0.6% zone width, 100-200 lookback
Indices: 0.2-0.4% zone width, 100-250 lookback
⚠️ Disclaimer
This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions. Support and resistance levels are not guarantees of price behavior. Always use proper risk management, combine with other analysis methods, and consider fundamental factors. Past performance does not guarantee future results.
DeeptestDeeptest: Quantitative Backtesting Library for Pine Script
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█ OVERVIEW
Deeptest is a Pine Script library that provides quantitative analysis tools for strategy backtesting. It calculates over 100 statistical metrics including risk-adjusted return ratios (Sharpe, Sortino, Calmar), drawdown analysis, Value at Risk (VaR), Conditional VaR, and performs Monte Carlo simulation and Walk-Forward Analysis.
█ WHY THIS LIBRARY MATTERS
Pine Script is a simple yet effective coding language for algorithmic and quantitative trading. Its accessibility enables traders to quickly prototype and test ideas directly within TradingView. However, the built-in strategy tester provides only basic metrics (net profit, win rate, drawdown), which is often insufficient for serious strategy evaluation.
Due to this limitation, many traders migrate to alternative backtesting platforms that offer comprehensive analytics. These platforms require other language programming knowledge, environment setup, and significant time investment—often just to test a simple trading idea.
Deeptest bridges this gap by bringing institutional-level quantitative analytics directly to Pine Script. Traders can now perform sophisticated analysis without leaving TradingView or learning complex external platforms. All calculations are derived from strategy.closedtrades.* , ensuring compatibility with any existing Pine Script strategy.
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█ ORIGINALITY AND USEFULNESS
This library is original work that adds value to the TradingView community in the following ways:
1. Comprehensive Metric Suite: Implements 112+ statistical calculations in a single library, including advanced metrics not available in TradingView's built-in tester (p-value, Z-score, Skewness, Kurtosis, Risk of Ruin).
2. Monte Carlo Simulation: Implements trade-sequence randomization to stress-test strategy robustness by simulating 1000+ alternative equity curves.
3. Walk-Forward Analysis: Divides historical data into rolling in-sample and out-of-sample windows to detect overfitting by comparing training vs. testing performance.
4. Rolling Window Statistics: Calculates time-varying Sharpe, Sortino, and Expectancy to analyze metric consistency throughout the backtest period.
5. Interactive Table Display: Renders professional-grade tables with color-coded thresholds, tooltips explaining each metric, and period analysis cards for drawdowns/trades.
6. Benchmark Comparison: Automatically fetches S&P 500 data to calculate Alpha, Beta, and R-squared, enabling objective assessment of strategy skill vs. passive investing.
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█ KEY FEATURES
Performance Metrics
Net Profit, CAGR, Monthly Return, Expectancy
Profit Factor, Payoff Ratio, Sample Size
Compounding Effect Analysis
Risk Metrics
Sharpe Ratio, Sortino Ratio, Calmar Ratio (MAR)
Martin Ratio, Ulcer Index
Max Drawdown, Average Drawdown, Drawdown Duration
Risk of Ruin, R-squared (equity curve linearity)
Statistical Distribution
Value at Risk (VaR 95%), Conditional VaR
Skewness (return asymmetry)
Kurtosis (tail fatness)
Z-Score, p-value (statistical significance testing)
Trade Analysis
Win Rate, Breakeven Rate, Loss Rate
Average Trade Duration, Time in Market
Consecutive Win/Loss Streaks with Expected values
Top/Worst Trades with R-multiple tracking
Advanced Analytics
Monte Carlo Simulation (1000+ iterations)
Walk-Forward Analysis (rolling windows)
Rolling Statistics (time-varying metrics)
Out-of-Sample Testing
Benchmark Comparison
Alpha (excess return vs. benchmark)
Beta (systematic risk correlation)
Buy & Hold comparison
R-squared vs. benchmark
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█ QUICK START
Basic Usage
//@version=6
strategy("My Strategy", overlay=true)
// Import the library
import Fractalyst/Deeptest/1 as *
// Your strategy logic
fastMA = ta.sma(close, 10)
slowMA = ta.sma(close, 30)
if ta.crossover(fastMA, slowMA)
strategy.entry("Long", strategy.long)
if ta.crossunder(fastMA, slowMA)
strategy.close("Long")
// Run the analysis
DT.runDeeptest()
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█ METRIC EXPLANATIONS
The Deeptest table displays 23 metrics across the main row, with 23 additional metrics in the complementary row. Each metric includes detailed tooltips accessible by hovering over the value.
Main Row — Performance Metrics (Columns 0-6)
Net Profit — (Final Equity - Initial Capital) / Initial Capital × 100
— >20%: Excellent, >0%: Profitable, <0%: Loss
— Total return percentage over entire backtest period
Payoff Ratio — Average Win / Average Loss
— >1.5: Excellent, >1.0: Good, <1.0: Losses exceed wins
— Average winning trade size relative to average losing trade. Breakeven win rate = 100% / (1 + Payoff)
Sample Size — Count of closed trades
— >=30: Statistically valid, <30: Insufficient data
— Number of completed trades. Includes 95% confidence interval for win rate in tooltip
Profit Factor — Gross Profit / Gross Loss
— >=1.5: Excellent, >1.0: Profitable, <1.0: Losing
— Ratio of total winnings to total losses. Uses absolute values unlike payoff ratio
CAGR — (Final / Initial)^(365.25 / Days) - 1
— >=10%: Excellent, >0%: Positive growth
— Compound Annual Growth Rate - annualized return accounting for compounding
Expectancy — Sum of all returns / Trade count
— >0.20%: Excellent, >0%: Positive edge
— Average return per trade as percentage. Positive expectancy indicates profitable edge
Monthly Return — Net Profit / (Months in test)
— >0%: Profitable month average
— Average monthly return. Geometric monthly also shown in tooltip
Main Row — Trade Statistics (Columns 7-14)
Avg Duration — Average time in position per trade
— Mean holding period from entry to exit. Influenced by timeframe and trading style
Max CW — Longest consecutive winning streak
— Maximum consecutive wins. Expected value = ln(trades) / ln(1/winRate)
Max CL — Longest consecutive losing streak
— Maximum consecutive losses. Important for psychological risk tolerance
Win Rate — Wins / Total Trades
— Higher is better
— Percentage of profitable trades. Breakeven win rate shown in tooltip
BE Rate — Breakeven Trades / Total Trades
— Lower is better
— Percentage of trades that broke even (neither profit nor loss)
Loss Rate — Losses / Total Trades
— Lower is better
— Percentage of unprofitable trades. Together with win rate and BE rate, sums to 100%
Frequency — Trades per month
— Trading activity level. Displays intelligently (e.g., "12/mo", "1.5/wk", "3/day")
Exposure — Time in market / Total time × 100
— Lower = less risk
— Percentage of time the strategy had open positions
Main Row — Risk Metrics (Columns 15-22)
Sharpe Ratio — (Return - Rf) / StdDev × sqrt(Periods)
— >=3: Excellent, >=2: Good, >=1: Fair, <1: Poor
— Measures risk-adjusted return using total volatility. Annualized using sqrt(252) for daily
Sortino Ratio — (Return - Rf) / DownsideDev × sqrt(Periods)
— >=2: Excellent, >=1: Good, <1: Needs improvement
— Similar to Sharpe but only penalizes downside volatility. Can be higher than Sharpe
Max DD — (Peak - Trough) / Peak × 100
— <5%: Excellent, 5-15%: Moderate, 15-30%: High, >30%: Severe
— Largest peak-to-trough decline in equity. Critical for risk tolerance and position sizing
RoR — Risk of Ruin probability
— <1%: Excellent, 1-5%: Acceptable, 5-10%: Elevated, >10%: Dangerous
— Probability of losing entire trading account based on win rate and payoff ratio
R² — R-squared of equity curve vs. time
— >=0.95: Excellent, 0.90-0.95: Good, 0.80-0.90: Moderate, <0.80: Erratic
— Coefficient of determination measuring linearity of equity growth
MAR — CAGR / |Max Drawdown|
— Higher is better, negative = bad
— Calmar Ratio. Reward relative to worst-case loss. Negative if max DD exceeds CAGR
CVaR — Average of returns below VaR threshold
— Lower absolute is better
— Conditional Value at Risk (Expected Shortfall). Average loss in worst 5% of outcomes
p-value — Binomial test probability
— <0.05: Significant, 0.05-0.10: Marginal, >0.10: Likely random
— Probability that observed results are due to chance. Low p-value means statistically significant edge
Complementary Row — Extended Metrics
Compounding — (Compounded Return / Total Return) × 100
— Percentage of total profit attributable to compounding (position sizing)
Avg Win — Sum of wins / Win count
— Average profitable trade return in percentage
Avg Trade — Sum of all returns / Total trades
— Same as Expectancy (Column 5). Displayed here for convenience
Avg Loss — Sum of losses / Loss count
— Average unprofitable trade return in percentage (negative value)
Martin Ratio — CAGR / Ulcer Index
— Similar to Calmar but uses Ulcer Index instead of Max DD
Rolling Expectancy — Mean of rolling window expectancies
— Average expectancy calculated across rolling windows. Shows consistency of edge
Avg W Dur — Avg duration of winning trades
— Average time from entry to exit for winning trades only
Max Eq — Highest equity value reached
— Peak equity achieved during backtest
Min Eq — Lowest equity value reached
— Trough equity point. Important for understanding worst-case absolute loss
Buy & Hold — (Close_last / Close_first - 1) × 100
— >0%: Passive profit
— Return of simply buying and holding the asset from backtest start to end
Alpha — Strategy CAGR - Benchmark CAGR
— >0: Has skill (beats benchmark)
— Excess return above passive benchmark. Positive alpha indicates genuine value-added skill
Beta — Covariance(Strategy, Benchmark) / Variance(Benchmark)
— <1: Less volatile than market, >1: More volatile
— Systematic risk correlation with benchmark
Avg L Dur — Avg duration of losing trades
— Average time from entry to exit for losing trades only
Rolling Sharpe/Sortino — Dynamic based on win rate
— >2: Good consistency
— Rolling metric across sliding windows. Shows Sharpe if win rate >50%, Sortino if <=50%
Curr DD — Current drawdown from peak
— Lower is better
— Present drawdown percentage. Zero means at new equity high
DAR — CAGR adjusted for target DD
— Higher is better
— Drawdown-Adjusted Return. DAR^5 = CAGR if max DD = 5%
Kurtosis — Fourth moment / StdDev^4 - 3
— ~0: Normal, >0: Fat tails, <0: Thin tails
— Measures "tailedness" of return distribution (excess kurtosis)
Skewness — Third moment / StdDev^3
— >0: Positive skew (big wins), <0: Negative skew (big losses)
— Return distribution asymmetry
VaR — 5th percentile of returns
— Lower absolute is better
— Value at Risk at 95% confidence. Maximum expected loss in worst 5% of outcomes
Ulcer — sqrt(mean(drawdown^2))
— Lower is better
— Ulcer Index - root mean square of drawdowns. Penalizes both depth AND duration
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█ MONTE CARLO SIMULATION
Purpose
Monte Carlo simulation tests strategy robustness by randomizing the order of trades while keeping trade returns unchanged. This simulates alternative equity curves to assess outcome variability.
Method
Extract all historical trade returns
Randomly shuffle the sequence (1000+ iterations)
Calculate cumulative equity for each shuffle
Build distribution of final outcomes
Output
The stress test table shows:
Median Outcome: 50th percentile result
5th Percentile: Worst 5% of outcomes
95th Percentile: Best 95% of outcomes
Success Rate: Percentage of simulations that were profitable
Interpretation
If 95% of simulations are profitable: Strategy is robust
If median is far from actual result: High variance/unreliability
If 5th percentile shows large loss: High tail risk
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█ WALK-FORWARD ANALYSIS
Purpose
Walk-Forward Analysis (WFA) is the gold standard for detecting strategy overfitting. It simulates real-world trading by dividing historical data into rolling "training" (in-sample) and "validation" (out-of-sample) periods. A strategy that performs well on unseen data is more likely to succeed in live trading.
Method
The implementation uses a non-overlapping window approach following AmiBroker's gold standard methodology:
Segment Calculation: Total trades divided into N windows (default: 12), IS = ~75%, OOS = ~25%, Step = OOS length
Window Structure: Each window has IS (training) followed by OOS (validation). Each OOS becomes the next window's IS (rolling forward)
Metrics Calculated: CAGR, Sharpe, Sortino, MaxDD, Win Rate, Expectancy, Profit Factor, Payoff
Aggregation: IS metrics averaged across all IS periods, OOS metrics averaged across all OOS periods
Output
IS CAGR: In-sample annualized return
OOS CAGR: Out-of-sample annualized return ( THE key metric )
IS/OOS Sharpe: In/out-of-sample risk-adjusted return
Success Rate: % of OOS windows that were profitable
Interpretation
Robust: IS/OOS CAGR gap <20%, OOS Success Rate >80%
Some Overfitting: CAGR gap 20-50%, Success Rate 50-80%
Severe Overfitting: CAGR gap >50%, Success Rate <50%
Key Principles:
OOS is what matters — Only OOS predicts live performance
Consistency > Magnitude — 10% IS / 9% OOS beats 30% IS / 5% OOS
Window count — More windows = more reliable validation
Non-overlapping OOS — Prevents data leakage
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█ TABLE DISPLAY
Main Table — Organized into three sections:
Performance Metrics (Cols 0-6): Net Profit, Payoff, Sample Size, Profit Factor, CAGR, Expectancy, Monthly
Trade Statistics (Cols 7-14): Avg Duration, Max CW, Max CL, Win, BE, Loss, Frequency, Exposure
Risk Metrics (Cols 15-22): Sharpe, Sortino, Max DD, RoR, R², MAR, CVaR, p-value
Color Coding
🟢 Green: Excellent performance
🟠 Orange: Acceptable performance
⚪ Gray: Neutral / Fair
🔴 Red: Poor performance
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█ IMPLEMENTATION NOTES
Data Source: All metrics calculated from strategy.closedtrades , ensuring compatibility with any Pine Script strategy
Calculation Timing: All calculations occur on barstate.islastconfirmedhistory to optimize performance
Limitations: Requires at least 1 closed trade for basic metrics, 30+ trades for reliable statistical analysis
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█ QUICK NOTES
➙ This library has been developed and refined over two years of real-world strategy testing. Every calculation has been validated against industry-standard quantitative finance references.
➙ The entire codebase is thoroughly documented inline. If you are curious about how a metric is calculated or want to understand the implementation details, dive into the source code -- it is written to be read and learned from.
➙ This description focuses on usage and concepts rather than exhaustively listing every exported type and function. The library source code is thoroughly documented inline -- explore it to understand implementation details and internal logic.
➙ All calculations execute on barstate.islastconfirmedhistory to minimize runtime overhead. The library is designed for efficiency without sacrificing accuracy.
➙ Beyond analysis, this library serves as a learning resource. Study the source code to understand quantitative finance concepts, Pine Script advanced techniques, and proper statistical methodology.
➙ Metrics are their own not binary good/bad indicators. A high Sharpe ratio with low sample size is misleading. A deep drawdown during a market crash may be acceptable. Study each function and metric individually -- evaluate your strategy contextually, not by threshold alone.
➙ All strategies face alpha decay over time. Instead of over-optimizing a single strategy on one timeframe and market, build a diversified portfolio across multiple markets and timeframes. Deeptest helps you validate each component so you can combine robust strategies into a trading portfolio.
➙ Screenshots shown in the documentation are solely for visual representation to demonstrate how the tables and metrics will be displayed. Please do not compare your strategy's performance with the metrics shown in these screenshots -- they are illustrative examples only, not performance targets or benchmarks.
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█ HOW-TO
Using Deeptest is intentionally straightforward. Just import the library and call DT.runDeeptest() at the end of your strategy code in main scope. .
//@version=6
strategy("My Strategy", overlay=true)
// Import the library
import Fractalyst/Deeptest/1 as DT
// Your strategy logic
fastMA = ta.sma(close, 10)
slowMA = ta.sma(close, 30)
if ta.crossover(fastMA, slowMA)
strategy.entry("Long", strategy.long)
if ta.crossunder(fastMA, slowMA)
strategy.close("Long")
// Run the analysis
DT.runDeeptest()
And yes... it's compatible with any TradingView Strategy! 🪄
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█ CREDITS
Author: @Fractalyst
Font Library: by @fikira - @kaigouthro - @Duyck
Community: Inspired by the @PineCoders community initiative, encouraging developers to contribute open-source libraries and continuously enhance the Pine Script ecosystem for all traders.
if you find Deeptest valuable in your trading journey, feel free to use it in your strategies and give a shoutout to @Fractalyst -- Your recognition directly supports ongoing development and open-source contributions to Pine Script.
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█ DISCLAIMER
This library is provided for educational and research purposes. Past performance does not guarantee future results. Always test thoroughly and use proper risk management. The author is not responsible for any trading losses incurred through the use of this code.
ACP ProDescription
ACP (Advanced Chart Patterns) detects complex multi-point patterns including Head & Shoulders (both regular and inverse), triangles (symmetrical, ascending, descending), wedges (rising, falling), and channels (ascending, descending, horizontal).
Ultimate Auto Trendlines Improved No lag, No Repaint with TableA major update - cleanest, most accurate non-repainting trendline tool.
What's new in this version:
• Connects MULTIPLE recent pivots (not just consecutive) → stronger, more reliable levels
• Solid lines extended far right → instant future S/R projection
• Built-in table (top-right): Price + EMA 10/20/50 (Above/Below) + MACD (Bull/Bear) + RSI (Bull/Bear) + ADX (Strong/Weak)
• Alerts for new trendlines — get notified the moment a fresh level forms
• Optional "R"/"S" pivot labels — clean visual swing confirmation
• Max 8 lines total → keeps your chart readable and focused
Why traders are adding this right now:
• 100% non-repainting – safe for live entries & alerts
• 80–85%+ touch/bounce rate in trending markets (SPY/QQQ/NASDAQ daily & 4H backtests)
• Angle filter kills flat/noise lines
• Works killer on stocks, indices, forex majors, crypto
Best settings to start:
Pivot Left/Right: 5/5
Min Angle: 12–15°
Max Trendlines: 8
Line Extension: 100–200 bars
Show Labels: On
Want the latest updates, settings tweaks, or new versions first?
Please Follow me on X → @TrendRiderPro1
Drop a like/favorite/comment if you add it – I read every one and reply to as many as I can.
Any feedback (bugs, ideas, your best settings) is super welcome!
Happy trading – let’s catch those clean bounces & big moves! 🚀📈
If you add it, drop a like/favorite/comment — I read every one and reply to as many as I can.
Any feedback (settings, bugs, ideas) is super welcome — helps me keep improving it.
Happy trading — let’s catch those clean bounces & big moves! 🚀
Chainbey Ai - Swing High/Low Range📈 Chainbey Ai – Swing High / Swing Low Range
Chainbey Ai – Swing High / Swing Low Range is a clean and powerful market-structure indicator designed to automatically identify key swing levels and visualize the active price range on any chart.
This tool helps traders clearly see where price is reacting, consolidating, or preparing for a breakout.
🔹 What This Indicator Does
✔ Automatically detects the latest confirmed Swing High
✔ Automatically detects the latest confirmed Swing Low
✔ Draws horizontal levels for both swings
✔ Labels levels clearly as “Swing High” and “Swing Low”
✔ Highlights the range between swings using a background fill
✔ Updates dynamically as new market structure forms
🔹 Why It’s Useful
Identify support & resistance without manual drawing
Visualize consolidation zones instantly
Spot breakout and fake-out areas faster
Ideal for range trading, breakout trading, and trend confirmation
Works perfectly with price action, volume, and order-flow concepts
🔹 Best Use Cases
Crypto (Spot & Futures)
Forex
Indices
Commodities (Gold, Silver, Oil)
Timeframes: Works on all timeframes (especially strong on 15M, 30M, 1H)
🔹 How to Trade With It
Buy bias when price holds above Swing Low inside the range
Sell bias when price rejects from Swing High
Breakout confirmation when price closes strongly outside the range
Combine with volume, momentum, or liquidity concepts for higher accuracy
🔹 Customization
Adjust Swing Length to control sensitivity
Enable/disable range background fill
Customize colors and transparency
Extend swing levels to the right for forward guidance
⚠️ Disclaimer
This indicator is a technical analysis tool, not financial advice.
Always manage risk and confirm signals with your own strategy.
🔗 Built by Chainbey Ai
Smart Structure • Clean Levels • Clear Ranges 🚀
ICT-SMC ProMarket Structure** (Swing Highs/Lows, HH, HL, LH, LL)
- ✅ **Break of Structure (BOS)** — Trend continuation signals
- ✅ **Change of Character (CHoCH)** — Early reversal warnings
- ✅ **Order Blocks (OB)** — Institutional supply/demand zones
- ✅ **Fair Value Gaps (FVG)** — Price imbalances & magnets
- ✅ **Inverse Fair Value Gaps (iFVG)** — Validated support/resistance
- ✅ **Liquidity Pools (BSL/SSL)** — Stop hunt targets
- ✅ **Liquidity Sweeps** — Reversal confirmation signals
Chainbey AI - Pattern Memory Table (v2)Chainbey AI – Pattern Memory & Market Outcome Table
Chainbey AI Pattern Memory is an advanced market behavior reference indicator designed to help traders understand how the current price structure compares with historical market patterns.
Instead of repainting signals or forcing trades, this tool focuses on context awareness:
It analyzes the current price pattern range
Matches it against selected historical price structures
Displays how price reacted after similar patterns in the past
Shows an estimated directional outcome and momentum strength
All results are presented in a lightweight on-chart table, keeping the chart clean and readable.
🔍 What this indicator shows
📅 Matched historical date & time
📈 Expected direction (UP / DOWN / FLAT)
📊 Historical move percentage
⚡ Estimated momentum strength
🧠 Similarity score (lower = closer pattern match)
🎯 How traders use it
Confirm bias before entering a trade
Understand historical reactions at similar market structures
Avoid emotional decisions by referencing past behavior
Combine with support/resistance, volume, RSI, or trend tools
⚠️ This indicator does NOT generate buy/sell signals.
It is a decision-support & market insight tool, best used alongside your own strategy.
🧩 Best use cases
Crypto, Forex, Commodities, Indices
Intraday & swing trading
Market structure and pattern-based strategies
Bias confirmation before entries
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
It does not guarantee future performance and should not be considered financial advice.
AutoTrend Trader Description
AT_Trader automatically detects and draws trendlines by connecting swing highs (resistance trendlines) and swing lows (support trendlines). The system also detects trendline breakouts with optional buffer zones to filter false breaks.
Weekly RSI + EMA Bias (FREE)Weekly RSI + EMA Bias — FREE
This indicator provides a clean, non-repainting weekly directional bias using:
• EMA trend filter
• RSI strength confirmation
• One controlled flip per week
• IST-based weekly entry & exit logic
• Holiday-safe exit handling (no missed exits)
WHAT THIS IS:
• A bias / confirmation tool
• Designed for positional & weekly traders
• Works on all intraday and higher timeframes
WHAT THIS IS NOT:
• Not a strategy
• No backtesting or performance metrics
• No buy/sell guarantees
METRICS TABLE:
The weekly metrics table is intentionally locked (🔒).
A fully unlocked metrics + strategy version is available separately.
Best used as a decision-support tool alongside your own execution rules.
