parademi super📌 Indicator Information: EMA 5-8-13 with Noise Reduction
This Pine Script indicator is designed to highlight EMA crossovers and filter out weak or noisy signals by combining multiple confirmation tools.
🔹 Core Logic
Plots three EMAs: 5, 8, and 13.
Colors bars:
Green when price is above all EMAs.
Red when price is below all EMAs.
Orange when price crosses EMA 8.
Displays arrows for 5/8 and 8/13 EMA crossovers (up = bullish, down = bearish).
🔹 Noise Reduction Filters
The script integrates several optional filters to reduce false signals:
Trend alignment: Only signals when EMAs are properly aligned (5>8>13 for bullish, 5<8<13 for bearish).
Close confirmation: Requires bar close beyond EMA 8 by a margin.
ADX filter: Ensures sufficient trend strength (custom ADX calculation).
MFI filter: Confirms with Money Flow Index thresholds.
Volatility filter: Blocks signals when EMAs are too close or ATR is too low.
Higher timeframe (HTF) filter: Confirms direction with EMA 8/13 crossover on a higher timeframe.
Debounce: Minimum bar distance between signals to avoid repetition.
🔹 Customization
All filters and thresholds are adjustable in the input menu:
Enable/disable specific filters.
Change EMA lengths, ADX/MFI parameters, ATR threshold, or HTF resolution.
Adjust the minimum bars between signals for cleaner charts.
🔹 Alerts
Built-in alerts are included for each crossover type (Bull/Bear for 5/8 and 8/13).
⚠️ Note: This is an educational tool for technical analysis. Always backtest and confirm with your own strategy before making trading decisions.
Cari dalam skrip untuk "backtest"
Deviation Rate Crash SignalDescription
This indicator provides entry signals for contrarian trades that aim to capture rebounds after sharp declines, such as during market crashes.
A signal is triggered when the deviation rate from the 25-day moving average falls below -25% (default setting). On the chart, a red circle is displayed below the candlestick to indicate the signal.
Backtest (2000–2024, Nikkei 225 stocks):
Win rate: 64.73%
Payoff ratio: 1.141
Probability of ruin: 0.0% (with proper risk control)
Trading Rules (Long only):
Entry: Market buy at next day’s open when the closing price is 25% or more below the 25-day MA.
Exit: Market sell at next day’s open when:
The closing price is 10% above the entry price (take profit), or
The closing price is 10% below the entry price (stop loss), or
40 days have passed since entry.
Notes:
This indicator is tuned for crisis periods (e.g., 2008 Lehman Shock, 2011 Great East Japan Earthquake, 2020 COVID-19 crash, 2024 Yen carry trade reversal).
In normal market conditions, signals will be rare.
Pine Screener BETA Support:
Add this indicator to your favorites and scan with long condition = true.
Screener results display both the MA deviation rate and current price.
When multiple signals occur, use the deviation rate as a reference to prioritize setups.
説明
このインジケーターは、暴落時など短期間で急落した銘柄のリバウンドを狙う逆張りトレードのエントリーシグナルを提供します。
25日移動平均線からの乖離率が -25% を下回ったときにシグナルが点灯します（初期設定）。シグナルはメインチャートのローソク足の下に赤い丸印で表示されます。
バックテスト結果（2000～2024年、日経225銘柄）:
勝率: 64.73%
ペイオフレシオ: 1.141
破産確率: 0.0%（適切なリスク管理を行った場合）
トレードルール（買いのみ）:
エントリー: 終値が25日移動平均線から25%以上下方乖離した場合、翌日の寄り付きで成行買い。
手仕舞い: 翌日の寄り付きで成行売り（以下のいずれかの条件を満たした場合）
終値が買値より10%以上上昇（利確）
終値が買値より10%以上下落（損切り）
エントリーから40日経過
注意点:
このインジケーターは、2008年リーマンショック、2011年東日本大震災、2020年コロナショック、2024年円キャリートレード巻き戻しショックなど、危機的局面で効果を発揮するように調整されています。
通常の相場ではシグナルはほとんど出現しません。
Pine Screener BETA 対応:
このインジケーターをお気に入り登録し、long condition = true をフィルター条件にしてスキャンしてください。
スクリーナー結果には移動平均乖離率と現在値が表示されます。
シグナルが同時に多数出現した場合は、移動平均乖離率を参考に優先順位をつけてください。
EMA Cross By Crypto collective Xეს ინდიკატორი გაძლევთ საშუალებას ნახოთ ყველაზე პოპულარული EMA წყვილები ერთ გრაფიკზე:
EMA 9/21
EMA 20/50
EMA 50/200
EMA 100/200
და საკუთარი, მომხმარებლის მიერ შერჩეული Custom წყვილი.
👉 თითოეულ წყვილს შეგიძლია ჩართო/გამორთო ინდიკატორის პარამეტრებიდან.
👉 შესაძლებელია ფერების შეცვლა, ასევე სურვილის შემთხვევაში EMA-ების higher timeframe-ზე გამოტანა (მაგ. 1D EMA 4H გრაფიკზე).
ეს ინსტრუმენტი განსაკუთრებით გამოსადეგია:
ტრენდების დადგენისთვის
გრძელვადიანი და მოკლევადიანი გადაკვეთების შესადარებლად
საკუთარი სტრატეგიის ტესტირებისთვის
This indicator lets you plot and compare the most commonly used EMA pairs on a single chart:
EMA 9/21
EMA 20/50
EMA 50/200
EMA 100/200
plus a fully customizable user-defined EMA pair.
👉 Each pair can be toggled on/off from the settings.
👉 Colors are customizable, and you can optionally display EMAs from a higher timeframe (e.g., show Daily EMAs on a 4H chart).
This tool is especially useful for:
Trend confirmation
Comparing short-term vs. long-term crosses
Backtesting your own strategies
Iani SMC Sniper XAU v2.2 (Long+Short + News Countdown, v6)Iani SMC Sniper v2.6 — Anytime • Auto Pip • FVG 50% • OB • News Panel
Smart-Money Concepts made simple for intraday XAU/USD (works on any symbol).
Finds BOS, 50% FVG “sniper” entries, optional Order Blocks, London H/L, news countdown, and a mini info panel.
What it does
BOS (Break of Structure): detects bullish/bearish BOS after London sweep logic.
FVG 50% entries: plots precise long/short entry dots at the midpoint of the gap.
Auto TP/SL: TP = RR × risk, SL below/above recent swing with a small buffer.
Order Blocks (optional): marks the last opposite candle after BOS and alerts on OB revisit.
London High/Low: tracks session range; session filter is optional.
News countdown: shows next event time and minutes left (user-selectable timezone).
Mini Panel: top-left table with Trend (last BOS), Next news, R:R, Pip size.
Inputs (key)
Auto pip size: uses syminfo.mintick. Manual override available.
Risk:Reward (RR): default 2.0.
Pivot length: swing sensitivity.
Sessions: enable if you want signals only 12:00–20:00 (symbol timezone). Off = anytime.
News timezone: pick your own (e.g., Europe/Brussels, America/New_York).
Absolute & daily times: add your events (strings like 2025-09-17 20:00 or 14:30,16:00…).
Show labels/levels/OBs: toggle on/off.
Alerts included
BOS Bullish / BOS Bearish
BUY Entry / SELL Entry (return to 50% FVG)
Bullish OB revisit / Bearish OB revisit
TP Long/Short reached, SL Long/Short hit
NEWS WARNING (warning window only; does not block signals)
To use: Add Alert → Condition: this indicator → choose any of the alertconditions.
Best use
Bias: H1 for structure.
Execution: M15 (standard) or M5 (aggressive).
Works great on XAUUSD, but is symbol-agnostic (auto pip adapts).
Notes
News times display in the timezone you pick in settings.
OBs are a simple implementation meant for quick visual guidance.
Labels: BUY/SELL near entries, TP/SL on set and when hit, BOS up/down.
Risk disclaimer
This tool is for education only. Not financial advice. Backtest and manage risk.
Percentage Change per 5 Candles
🔎 What this indicator does
This indicator calculates and displays the percentage change of each candlestick directly on the chart.
• If a candle closed higher than it opened (bullish candle), it shows a positive % change (green).
• If a candle closed lower than it opened (bearish candle), it shows a negative % change (red).
• Small moves below your chosen threshold (e.g., 0.1%) are ignored to avoid clutter.
• The labels are placed above, below, or in the center of the candle (you choose).
So essentially, every candle “tells you in numbers” exactly how much it changed relative to its opening price.
________________________________________
⚙️ How it operates (the logic inside)
1. Calculate the change
o Formula:
\text{% Change} = \frac{(\text{Close} - \text{Open})}{\text{Open}} \times 100
o Example: If a candle opens at 100 and closes at 105, that’s a +5% change.
2. Round it nicely
o You can control decimals (e.g., show 2 decimals → +5.23%).
3. Filter out noise
o If a candle barely moved (say 0.02%), the label won’t appear unless you reduce the threshold.
4. Style the labels
o Bullish = green text, slightly transparent green background.
o Bearish = red text, slightly transparent red background.
o Neutral (0%) = gray.
5. Place the labels
o Options: above the candle, below the candle, or centered.
o Small vertical offset is applied so labels don’t overlap the candle itself.
________________________________________
📊 How this helps traders
This indicator turns visual candles into quantifiable numbers at a glance. Instead of guessing whether a move was “big” or “small,” you see it clearly.
Key Benefits:
1. Quick volatility analysis
o You can instantly see if candles are making big % swings or just small moves.
o This is especially useful on higher timeframes (daily/weekly) where moves can be large.
2. Pattern confirmation
o For example, you might spot a strong bullish engulfing candle — the % change label helps confirm whether it was truly significant (e.g., +4.5%) or just modest (+0.7%).
3. Noise filtering
o By setting a minimum % threshold, you only see labels when moves are meaningful (say > 0.5%). This keeps focus on important candles.
4. Backtesting & comparison
o You can compare moves across time:
“How strong was this breakout candle compared to the last one?”
“Are today’s bearish candles weaker or stronger than yesterday’s bullish candles?”
5. Better decision-making
o If you’re trading breakouts, reversals, or trend-following, knowing the % size of each candle helps confirm if the move has enough momentum.
________________________________________
✅ In short:
This indicator quantifies price action. Instead of just seeing “green” or “red” candles, you now know exactly how much the price changed in percentage terms, directly on the chart, in real time. It helps you distinguish between strong and weak moves and makes your analysis more precise.
________________________________________
High-and-Tight Impulse + Micro ConsolidationThis indicator detects a specific bullish continuation setup on daily charts:
- An impulse move (X% rise within N bars, mostly green candles)
- Immediately followed by a tight consolidation (small ranges, small bodies)
- Closes holding in the top zone of the impulse
On the chart, signals are plotted as orange dots above bars.
Labels show the last detected setup date, and a counter displays total matches in history.
Useful for backtesting "high-and-tight flag" type momentum patterns or any symbol.
Adjust inputs (impulse % threshold, bars, ATR ratios, top zone %) to make it stricter or looser.
Alerts are included when a new setup is detected.
This tool is not financial advice. For educational and research purposes only.
by fiyatherseydir
Multiple Colored Moving AveragesMULTIPLE COLORED MOVING AVERAGES - USER GUIDE
DISCLAIMER
----------
Both the code and this documentation were created heavily using artificial intelligence. I'm lazy...
This indicator was inspired by repo32's "Moving Average Colored EMA/SMA" indicator. *
What is this indicator?
-----------------------
This is a TradingView indicator that displays up to 4 different moving averages on your chart simultaneously. Each moving average can be customized with different calculation methods, colors, and filtering options.
Why would I use multiple moving averages?
-----------------------------------------
- See trend direction across different timeframes at once
- Identify support and resistance levels
- Spot crossover signals between fast and slow MAs
- Reduce false signals with filtering options
- Compare how different MA types react to price action
What moving average types are available?
----------------------------------------
11 different types:
- SMA: Simple average, equal weight to all periods
- EMA: Exponential, more weight to recent prices
- WMA: Weighted, linear weighting toward recent data
- RMA: Running average, smooth like EMA
- DEMA: Double exponential, reduced lag
- TEMA: Triple exponential, even less lag
- HMA: Hull, fast and smooth combination
- VWMA: Volume weighted, includes volume data
- LSMA: Least squares, based on linear regression
- TMA: Triangular, double-smoothed
- ZLEMA: Zero lag exponential, compensated for lag
How do I set up the indicator?
------------------------------
Each MA has these settings:
- Enable/Disable: Turn each MA on or off
- Type: Choose from the 11 calculation methods
- Length: Number of periods (21, 50, 100, 200 are common)
- Smoothing: 0-10 levels of extra smoothing
- Noise Filter: 0-5% to ignore small changes
- Colors: Bullish (rising) and bearish (falling) colors
- Line Width: 1-5 pixels thickness
What does the smoothing feature do?
-----------------------------------
Smoothing applies extra calculations to make the moving average line smoother. Higher levels reduce noise but make the MA respond slower to price changes. Use higher smoothing in choppy markets, lower smoothing in trending markets.
What is the noise filter?
--------------------------
The noise filter ignores small percentage changes in the moving average. For example, a 0.3% filter will ignore any MA movement smaller than 0.3%. This helps eliminate false signals from minor price fluctuations.
When should I use this indicator?
---------------------------------
- Trend analysis: See if market is going up, down, or sideways
- Entry timing: Look for price bounces off MA levels
- Exit signals: Watch for MA slope changes or crossovers
- Support/resistance: MAs often act as dynamic levels
- Multi-timeframe analysis: Use different lengths for different perspectives
What are some good settings to start with?
-------------------------------------------
Conservative approach:
- MA 1: EMA 21 (short-term trend)
- MA 2: SMA 50 (medium-term trend)
- MA 3: SMA 200 (long-term trend)
- Low noise filtering (0.1-0.3%)
Active trading:
- MA 1: HMA 9 (very responsive)
- MA 2: EMA 21 (short-term)
- MA 3: EMA 50 (medium-term)
- Minimal or no smoothing
How do I interpret the colors?
------------------------------
Each MA changes color based on its direction:
- Bullish color: MA is rising (upward trend)
- Bearish color: MA is falling (downward trend)
- Gray: MA is flat or unchanged
What should I look for in crossovers?
-------------------------------------
- Golden Cross: Fast MA crosses above slow MA (bullish signal)
- Death Cross: Fast MA crosses below slow MA (bearish signal)
- Multiple crossovers in same direction can confirm trend changes
- Wait for clear separation between MAs after crossover
How do I use MAs for support and resistance?
---------------------------------------------
- In uptrends: MAs often provide support when price pulls back
- In downtrends: MAs may act as resistance on rallies
- Multiple MAs create support/resistance zones
- Stronger levels where multiple MAs cluster together
Can I use this with other indicators?
-------------------------------------
Yes, it works well with:
- Volume indicators for confirmation
- RSI or MACD for timing entries
- Bollinger Bands for volatility context
- Price action patterns for setup confirmation
What if I get too many signals?
-------------------------------
- Increase smoothing levels
- Raise noise filter percentages
- Use longer MA periods
- Focus on major crossovers only
- Wait for multiple MA confirmation
What if signals are too slow?
-----------------------------
- Reduce smoothing to 0
- Lower noise filter values
- Switch to faster MA types (HMA, ZLEMA, DEMA)
- Use shorter periods
- Focus on the fastest MA only
Which MA types work best in different markets?
----------------------------------------------
Trending markets: EMA, DEMA, TEMA (responsive to trends)
Choppy markets: SMA, TMA, HMA with smoothing (less whipsaws)
High volatility: Use higher smoothing and noise filtering
Low volatility: Use minimal filtering for better responsiveness
Do I need all the advanced features?
------------------------------------
No. Start with basic settings:
- Choose MA type and length
- Set colors you prefer
- Leave smoothing at 0
- Leave noise filter at 0
Add complexity only if needed to improve signal quality.
How do I know if my settings are working?
-----------------------------------------
- Backtest on historical data
- Paper trade the signals first
- Adjust based on market conditions
- Keep a trading journal to track performance
- Be willing to modify settings as markets change
Can I save different configurations?
------------------------------------
Yes, save different indicator templates in TradingView for:
- Different trading styles (scalping, swing trading)
- Different market conditions (trending, ranging)
- Different instruments (stocks, forex, crypto)
BTCUSD Dual Thrust (1H)BTCUSD Dual Thrust (1H) — Indicator
Overview
The Dual Thrust is a classic breakout-type strategy designed to capture strong directional moves when markets show imbalance between buyers and sellers. This indicator adapts the method specifically for BTCUSD on the 1-Hour timeframe, showing dynamic Buy/Sell trigger levels and live signals.
Origin
The Dual Thrust system was originally introduced by Michael Vitucci and has been widely used in futures and high-volatility markets. It was designed as a day-trading breakout framework, where daily high/low and close data define the range for the next session’s trade triggers.
How it Works
Each new day, the indicator calculates a “breakout range” using daily price data.
Two trigger levels are projected from the daily open:
Buy Trigger: Open + Range × KUp
Sell Trigger: Open - Range × KDn
Range can be built from either:
Classic Dual Thrust formula: max(High - Close , Close - Low) over a lookback period, or
ATR-based range: for volatility-adaptive signals.
A LONG signal fires when price crosses above the Buy Trigger.
An EXIT signal fires when price crosses below the Sell Trigger.
Buy/Sell lines step forward across each intraday bar until recalculated at the next daily open.
Practical Use
Optimized for BTCUSD 1-Hour charts (crypto’s volatility provides stronger follow-through).
Use the Buy/Sell levels as dynamic breakout lines or as confluence with your own setups.
Alerts are built in, so you can receive notifications when a LONG or EXIT condition triggers.
Designed as an indicator only (not a backtest strategy).
Key Features
✅ Daily Buy/Sell trigger lines auto-calculated and forward-filled
✅ LONG / EXIT labels on signals
✅ Optional ATR mode for volatility regimes
✅ Optional bar coloring for easy visual scanning
✅ Alerts ready for live monitoring
⚡️ Tip: While this indicator highlights breakout opportunities, effectiveness can improve when combined with trend filters (e.g., 200-SMA) or when aligned with higher timeframe supply/demand zones.
Liquidity Void Detector (Zeiierman)█ Overview
Liquidity Void Detector (Zeiierman) is an oscillator highlighting inefficient price displacements under low participation. It measures the most recent price move (standardized return) and amplifies it only when volume is below its own trend.
Positive readings ⇒ strong up-move on low volume → potential Buy-Side Imbalance (void below) that often refills.
Negative readings ⇒ strong down-move on low volume → potential Sell-Side Imbalance (void above) that often refills.
This tool provides a quantitative “void” proxy: when price travels far with unusually thin volume, the move is flagged as likely inefficient and prone to mean-reversion/mitigation.
█ How It Works
⚪ Volume Shock (Participation Filter)
Each bar, volume is compared to a rolling baseline. This is then z-scored.
// Volume Shock calculation
volTrend = ta.sma(volume, L)
vs = (volume > 0 and volTrend > 0) ? math.log(volume) - math.log(volTrend) : na
vsZ = zScore(vs, vzLen) // z-scored volume shock
lowVS = (vsZ <= vzThr) // low-volume condition
Bars with VolShock Z ≤ threshold are treated as low-volume (thin).
⚪ Prior Return Extremeness
The 1-bar log return is computed and z-scored.
// Prior return extremeness
r1 = math.log(close / close )
retZ = zScore(r1, rLen) // z-scored prior return
This shows whether the latest move is unusually large relative to recent history.
⚪ Void Oscillator
The oscillator is:
// Oscillator construction
weight = lowVS ? 1.0 : fadeNoLow
osc = retZ * weight
where Weight = 1 when volume is low, otherwise fades toward a user-set factor (0–1).
Osc > 0: up-move emphasized under low volume ⇒ Buy-Side Imbalance.
Osc < 0: down-move emphasized under low volume ⇒ Sell-Side Imbalance.
█ Why Use It
⚪ Targets Inefficient Moves
By filtering for low participation, the oscillator focuses on moves most likely driven by thin books/noise trading, which are statistically more likely to retrace.
⚪ Simple, Robust Logic
No need for tick data or order-book depth. It derives a practical void proxy from OHLCV, making it portable across assets and timeframes.
⚪ Complements Price-Action Tools
Use alongside FVG/imbalance zones, key levels, and volume profile to prioritize voids that carry the highest reversal probability.
█ How to Use
Sell-Side Imbalance = aggressive sell move (price goes down on low volume) → expect price to move up to fill it.
Buy-Side Imbalance = aggressive buy move (price goes up on low volume) → expect price to move down to fill it.
█ Settings
Volume Baseline Length — Bars for the volume trend used in VolShock. Larger = smoother baseline, fewer low-volume flags.
Vol Shock Z-Score Lookback — Bars to standardize VolShock; larger = smoother, fewer extremes.
Low-Volume Threshold (VolShock Z ≤) — Defines “thin participation.” Typical: −0.5 to −1.0.
Return Z-Score Lookback — Bars to standardize the 1-bar log return; larger = smoother “extremeness” measure.
Fade When Volume Not Low (0–1) — Weight applied when volume is not low. 0.00 = ignore non-low-volume bars entirely. 1.00 = treat volume condition as irrelevant (pure return extremeness).
Upper Threshold (Osc ≥) — Trigger for Sell-Side Imbalance (void below).
Lower Threshold (Osc ≤) — Trigger for Buy-Side Imbalance (void above).
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
HUll Dynamic BandEducational Hull Moving Average Wave Analysis Tool
**MARS** is an innovative educational indicator that combines multiple Hull Moving Average timeframes to create a comprehensive wave analysis system, similar in concept to Ichimoku Cloud but with enhanced smoothness and responsiveness.
---
🎯 Key Features
**Triple Wave System**
- **Peak Wave (34-period)**: Fast momentum signals, similar to Ichimoku's Conversion Line
- **Primary Wave (89-period)**: Main trend identification with retest detection
- **Swell Wave (178-period)**: Long-term trend context and major wave analysis
**Visual Wave Analysis**
- **Wave Power Fill**: Dynamic area between primary and swell waves showing trend strength
- **Peak Power Fill**: Short-term momentum visualization
- **Smooth Curves**: Hull MA-based calculations provide cleaner signals than traditional moving averages
**Intelligent Signal System**
- **Trend Shift Signals**: Clear visual markers when trend changes occur
- **Retest Detection**: Identifies potential retest opportunities with specific conditions
- **Correction Alerts**: Early warning signals for market corrections
---
📊 How It Works
The indicator uses **Hull Moving Averages** with **Fibonacci-based periods** (34, 89, 178) and a **Golden Ratio multiplier (1.64)** to create natural market rhythm analysis.
**Key Signal Types:**
- 🔵 **Circles**: Major trend shifts (primary wave crossovers)
- 💎 **Diamonds**: Retest opportunities with multi-wave confirmation
- ❌ **X-marks**: Correction signals and structural breaks
- 🌊 **Wave Fills**: Visual trend strength and direction
---
🎓 Educational Purpose
This indicator demonstrates:
- Advanced moving average techniques using Hull MA
- Multi-timeframe analysis in a single view
- Wave theory application in technical analysis
- Dynamic support/resistance concept visualization
**Similar to Ichimoku but Different:**
- Ichimoku uses price-based calculations → Angular cloud shapes
- MARS uses weighted averages → Smooth, flowing wave patterns
- Both identify trend direction, but MARS offers faster signals with cleaner visualization
---
⚙️ Customizable Settings
- **Wave Periods**: Adjust primary wave length (default: 89)
- **Multipliers**: Fine-tune wave sensitivity (default: 1.64 Golden Ratio)
- **Visual Style**: Customize line widths and signal displays
- **Peak Analysis**: Independent fast signal system (default: 34)
---
🔍 Usage Tips
1. **Trend Identification**: Watch wave fill colors and line positions
2. **Entry Timing**: Look for retest diamonds after trend shift circles
3. **Risk Management**: Use wave boundaries as dynamic support/resistance
4. **Confirmation**: Combine with price action and market structure analysis
---
⚠️ Important Notes
- **Educational Tool**: Designed for learning wave analysis concepts
- **Not Financial Advice**: Always use proper risk management
- **Backtesting Recommended**: Test on historical data before live trading
- **Combine with Analysis**: Works best with additional confirmation methods
---
🚀 Innovation
MARS represents a unique approach to wave analysis by:
- Combining Hull MA smoothness with Ichimoku-style visualization
- Providing multi-timeframe analysis without chart clutter
- Offering retest detection with specific wave conditions
- Creating an educational bridge between different analytical methods
---
*This indicator is shared for educational purposes to help traders understand advanced moving average techniques and wave analysis concepts. Always practice proper risk management and combine with your own analysis.*
Shadow Mimicry🎯 Shadow Mimicry - Institutional Money Flow Indicator
📈 FOLLOW THE SMART MONEY LIKE A SHADOW
Ever wondered when the big players are moving? Shadow Mimicry reveals institutional money flow in real-time, helping retail traders "shadow" the smart money movements that drive market trends.
🔥 WHY SHADOW MIMICRY IS DIFFERENT
Most indicators show you WHAT happened. Shadow Mimicry shows you WHO is acting.
Traditional indicators focus on price movements, but Shadow Mimicry goes deeper - it analyzes the relationship between price positioning and volume to detect when large institutional players are accumulating or distributing positions.
🎯 The Core Philosophy:
When price closes near highs with volume = Institutions buying
When price closes near lows with volume = Institutions selling
When neither occurs = Wait and observe
📊 POWERFUL FEATURES
✨ 3-Zone Visual System
🟢 BUY ZONE (+20 to +100): Institutional accumulation detected
⚫ NEUTRAL ZONE (-20 to +20): Market indecision, wait for clarity
🔴 SELL ZONE (-20 to -100): Institutional distribution detected
🎨 Crystal Clear Visualization
Background Colors: Instantly see market sentiment at a glance
Signal Triangles: Precise entry/exit points when zones are breached
Real-time Status Labels: "BUY ZONE" / "SELL ZONE" / "NEUTRAL"
Smooth, Non-Repainting Signals: No false hope from future data
🔔 Smart Alert System
Buy Signal: When indicator crosses above +20
Sell Signal: When indicator crosses below -20
Custom TradingView notifications keep you informed
🛠️ TECHNICAL SPECIFICATIONS
Algorithm Details:
Base Calculation: Modified Money Flow Index with enhanced volume weighting
Smoothing: EMA-based smoothing eliminates noise while preserving signals
Range: -100 to +100 for consistent scaling across all markets
Timeframe: Works on all timeframes from 1-minute to monthly
Optimized Parameters:
Period (5-50): Default 14 - Perfect balance of sensitivity and reliability
Smoothing (1-10): Default 3 - Reduces false signals while maintaining responsiveness
📚 COMPREHENSIVE TRADING GUIDE
🎯 Entry Strategies
🟢 LONG POSITIONS:
Wait for indicator to cross above +20 (green triangle appears)
Confirm with background turning green
Best entries: Early in uptrends or after pullbacks
Stop loss: Below recent swing low
🔴 SHORT POSITIONS:
Wait for indicator to cross below -20 (red triangle appears)
Confirm with background turning red
Best entries: Early in downtrends or after rallies
Stop loss: Above recent swing high
⚡ Exit Strategies
Profit Taking: When indicator reaches extreme levels (±80)
Stop Loss: When indicator crosses back to neutral zone
Trend Following: Hold positions while in favorable zone
🔄 Risk Management
Never trade against the prevailing trend
Use position sizing based on signal strength
Avoid trading during low volume periods
Wait for clear zone breaks, avoid boundary trades
🎪 MULTI-TIMEFRAME MASTERY
📈 Scalping (1m-5m):
Period: 7-10, Smoothing: 1-2
Quick reversals in Buy/Sell zones
High frequency, smaller targets
📊 Day Trading (15m-1h):
Period: 14 (default), Smoothing: 3
Swing high/low entries
Medium frequency, balanced risk/reward
📉 Swing Trading (4h-1D):
Period: 21-30, Smoothing: 5-7
Trend following approach
Lower frequency, larger targets
💡 PRO TIPS & ADVANCED TECHNIQUES
🔍 Market Context Analysis:
Bull Markets: Focus on buy signals, ignore weak sell signals
Bear Markets: Focus on sell signals, ignore weak buy signals
Sideways Markets: Trade both directions with tight stops
📈 Confirmation Techniques:
Volume Confirmation: Stronger signals occur with above-average volume
Price Action: Look for breaks of key support/resistance levels
Multiple Timeframes: Align signals across different timeframes
⚠️ Common Pitfalls to Avoid:
Don't chase signals in the middle of zones
Avoid trading during major news events
Don't ignore the overall market trend
Never risk more than 2% per trade
🏆 BACKTESTING RESULTS
Tested across 1000+ instruments over 5 years:
Win Rate: 68% on daily timeframe
Average Risk/Reward: 1:2.3
Best Performance: Trending markets (crypto, forex majors)
Drawdown: Maximum 12% during 2022 volatility
Note: Past performance doesn't guarantee future results. Always practice proper risk management.
🎓 LEARNING RESOURCES
📖 Recommended Study:
Books: "Market Wizards" for institutional thinking
Concepts: Volume Price Analysis (VPA)
Psychology: Understanding smart money vs. retail behavior
🔄 Practice Approach:
Demo First: Test on paper trading for 2 weeks
Small Size: Start with minimal position sizes
Journal: Track all trades and signal quality
Refine: Adjust parameters based on your trading style
⚠️ IMPORTANT DISCLAIMERS
🚨 RISK WARNING:
Trading involves substantial risk of loss
Past performance is not indicative of future results
This indicator is a tool, not a guarantee
Always use proper risk management
📋 TERMS OF USE:
For personal trading use only
Redistribution or modification prohibited
No warranty expressed or implied
User assumes all trading risks
💼 NOT FINANCIAL ADVICE:
This indicator is for educational and analytical purposes only. Always consult with qualified financial advisors and trade responsibly.
🛡️ COPYRIGHT & CONTACT
Created by: Luwan （IMTangYuan）
Copyright © 2025. All Rights Reserved.
Follow the shadows, trade with the smart money.
Version 1.0 | Pine Script v5 | Compatible with all TradingView accounts
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
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🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
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🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
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💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
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⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
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📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
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🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
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📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
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🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
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💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
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⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
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🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
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Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
Custom Buy/Sell Pattern BuilderAre you tired of using trading indicators that only let you follow fixed, pre-designed rules? Do you wish you could build your own “Buy” or “Sell” signals, experiment with your own ideas, or see instantly if your unique pattern works—without learning coding or hiring a developer?
The Custom Buy/Sell Pattern Builder is designed for YOU.
This TradingView indicator lets ANY trader—even a complete beginner—define exactly what kind of price and volume conditions should create a BUY or SELL label on any chart, in any market, at any timeframe.
You don’t need to know programming. You don’t need to know the definition of a hammer, doji, volume spike, or Engulfing pattern.
With a few clicks and easy dropdown choices, you can:
Make your own rules for buying or selling
Choose how many candles your pattern should look at
Decide if you want the biggest body, the lowest volume, the biggest movement, or any combination you can imagine
The result?
You’ll see clear “BUY” or “SELL” labels automatically show up on your chart whenever the exact rule YOU built matches current price action.
No more guessing. No more forced strategies. Just pure control and visual feedback!
Why Is This Powerful?
Traditional indicators (like MACD, RSI, or even classic candlestick scanners) work the same for everyone—and only as their inventors defined.
But every trader, and every market, is unique.
What if you could say:
“Show me a ‘SELL’ every time the newest candle is bigger than the one before, but with LESS volume, while the bar before that had an even smaller body—but more volume than all others?”
With this tool, it’s EASY!
You simply pick which candle you want to compare (most recent, previous, etc), what to compare (body or volume—body means the candle’s “thickness”, from open to close), choose “greater than”, “less than”, or “equal to”, and set a multiplier if you want (like “half as much”, “twice as big”, etc).
After this, if any bar on the chart fits all your rules, it will mark it as a BUY or SELL, depending on your selection.
This means—
Beginners can start experimenting with their intuition or small ideas, without tech hurdles
Experienced traders can visualize and fine-tune any possible logic, before they commit to backtesting or automating a real strategy
Every “what if” or “I wonder” setup is just 2–3 clicks away
How Does It Work? Simple Steps
1. Choose Your Signal Type
“Buy” or “Sell”
This tells the indicator whether to mark the qualifying bars with a green “BUY” or red “SELL” label
2. Pick How Many Candles To Use
“Pattern Candle Count” input (2, 3, or 4)
Example: If you use 4, the pattern will be applied to the most recent 4 candles at every step
3. Define Your Pattern With Inputs
For each candle (from newest “0” to oldest “3”), you can set:
Body Condition (example: “is this candle’s body bigger/smaller/equal to another?”)
Pick which candle to compare against
Pick “>”, “<”, “>=”, “<=”, or “=”
Set a multiplier if needed (like “0.5” to mean “half as big as” or “2” for “twice as big as”)
Volume Condition (exact same choices, but based on trading volume—not the candle’s price body)
For example:
“Candle0 Body > Candle2 Body”
means “the latest candle’s real-body (open–close) is bigger than the one two bars ago.”
“Candle1 Volume <= Candle2 Volume”
means “the previous candle’s volume is less than or equal to the volume of the bar two periods ago.”
You can leave a comparison blank if you don’t want to use it for a particular candle.
What Happens After You Set Your Rules?
Every bar on your chart is checked for your logic:
If ALL body AND volume conditions are true (for each candle you specified),
AND
The signal side (“Buy” or “Sell”) matches your dropdown,
Then a green “BUY” or red “SELL” label will show right on the bar, so you can visually spot exactly where your logic works!
Practical Example:
Suppose you want an entry setup that is:
“Sell whenever the newest candle’s body is bigger than two bars ago, body before that is bigger than three bars ago, AND the newest candle’s volume is less than or equal to two bars ago, AND the candle three bars ago’s volume is less than or equal to half the candle two bars ago’s volume.”
You’d set:
Pattern Candle Count: 4
Side: Sell
Candle0 Body Ref#: 2, Op: >, Mult: 1
Candle1 Body Ref#: 3, Op: >, Mult: 1
Candle0 Vol Ref#: 2, Op: <=, Mult: 1
Candle3 Vol Ref#: 2, Op: <=, Mult: 0.5
And the script will find all “SELL” bars on your chart matching these conditions.
Inputs Section: What Does Each Setting Do?
Let’s break down each input in the indicator’s Settings one by one, so even if you’re new, you’ll understand exactly how to use it!
1. Pattern Candle Count (2–4)
What is it?
This sets how many candles in a row you want your rule to look at.
Example:
“4” means your rules are based on the most recent candle and the 3 before it.
“2” means you are only comparing the current and previous candles.
Tip:
Beginners often use 4 to spot stronger patterns, but you can experiment!
2. Signal Side
What is it?
Choose “Buy” or “Sell”. The word you pick here decides which colored label (green for Buy, red for Sell) appears if your pattern matches.
Example:
Want to spot where “Sell” is likely? Pick “Sell”.
Change to “Buy” if you want bullish signals instead.
3. Body & Volume Comparison Settings (per Candle)
For each candle (#0 is newest/current, #3 is oldest in your pattern window):
Body Comparison
Candle# Body Ref#
Choose which other candle you want to compare this one’s body to.
“0” = newest, “1” = previous, “2” = two bars ago, “3” = three bars ago
Candle# Body Op (Operator; >, <, >=, <=, =)
How do you want to compare?
“>” means “greater than” (is bigger than)
“<” means “less than” (is smaller than)
“=” means “equal to”
Candle# Body Mult (Multiplier)
If you want relative comparisons. For example, with Mult=1:
“Candle0 body > Candle2 body x 1” means just “0 is larger than 2.”
“Candle0 body > Candle2 body x 2” means “0 is more than double 2.”
Volume Comparison
Candle# Vol Ref# / Op / Mult
Exact same logic as body, but works on the “Volume” of each candle (how much was traded during that bar).
How to Set Up a Rule (Step by Step Example)
Say you want to mark a Sell every time:
The most recent candle’s real body is BIGGER than the candle 2 bars ago;
The previous candle’s body is also BIGGER than the candle 3 bars ago;
The current candle’s volume is LESS than or equal to the volume of candle 2;
The previous candle’s volume is LESS than or equal to candle 2’s volume;
The candle 3 bars ago’s volume is LESS than or equal to HALF candle 2’s volume.
You’d set:
Pattern Candle Count: 4
Side: "Sell"
Candle0 Body Ref#: 2, Op: “>”, Mult: 1
Candle1 Body Ref#: 3, Op: “>”, Mult: 1
Candle0 Vol Ref#: 2, Op: “<=”, Mult: 1
Candle1 Vol Ref#: 2, Op: “<=”, Mult: 1
Candle3 Vol Ref#: 2, Op: “<=”, Mult: 0.5
All other comparisons (operators) can be left blank if you don’t want to use them!
When these rules are met, a bright red “SELL” label will appear right above the bar matching all your conditions.
Practical Tips & FAQ for Beginners
What does “body” mean?
It’s the “true range” of the candle: the difference between open and close. This ignores wicks for simple setups.
What does “volume” mean?
This is the total trading activity during that candle/bar. Many traders believe that patterns with different volume “meaning” (such as low-volume up bars, or high-volume down bars) signal a meaningful change.
What if nothing shows on chart?
It just means your current rules are rarely or never matched! Try making your comparisons simpler (maybe just 2-body and 2-volume conditions to start).
You can always hit “Reset Settings” to go back to default.
Can I use this for both buying and selling?
YES! You can detect both bullish (Buy) and bearish (Sell) custom conditions; just switch “Signal Side.”
Do I need to know coding?
Not at all! Everything is in simple input panels.
Creative Use Cases, Example Recipes & Troubleshooting
Creative Ways to Use
Spotting Reversals
Example:
Buy when: the newest candle body is LARGER than the previous 3 bars, but ALL volumes are lower than their neighbors.
Why? Sometimes, a big candle with surprisingly low volume after a sequence of small bars can signal a reversal.
Finding Exhaustion Moves
Example:
Sell when: the current bar body is twice as big as two bars ago, but volume is half.
Why? A very big candle with very little volume compared to similar bars may show the move is “running out of steam.”
Custom “Breakout + Confirmation” Patterns
Example:
Buy when:
Candle 0’s body is greater than Candle 2’s by at least 1.5x,
Candle 0’s volume is greater than Candle 1 and Candle 2,
Candle 1’s volume is less than Candle 0.
Why? This could catch strong breakouts but filter out noisy moves.
Multi-bar Bias/Squeeze Filter
Use “Pattern Candle Count: 4”
Set all 4 volume conditions to “<” and each reference to the previous candle.
Now, a BUY or SELL only marks when each bar is “dryer”/less active than the last — a classic squeeze or low-volatility buildup.
Troubleshooting Guide
“I don’t see any Buy/Sell label; is something broken?”
Most likely, your rules are too strict or rare! Try using only two comparisons and leave other “Op” inputs blank as a test.
Double-check you have enough candles on the chart: you need at least as many bars as your pattern count.
“Why does a label appear but not where I expect?”
Remember, the script checks your rules for every NEW candle. The candle “0” is always the most recent, then “1” is one bar back, etc.
Check the color and type chosen: “Signal Side” must be “Buy” for green, “Sell” for red.
“What if I want a more complex pattern?”
Stack conditions! You can demand the body/volume of each candle in your window meet a different rule or all follow the same rule in sequence.
Mini Glossary — For Newcomers
Candle/Bar: Each bar on the chart, shows price movement during a fixed time (e.g., one minute, one hour, one day).
Body: The colored (or filled) part of the candle — the open-to-close price range.
Volume: How much of the asset was actually traded that candle/bar.
Reference Index: When you pick “2” as a reference, it means “the candle two bars ago in the pattern window.”
Operator (“Op”): The math symbol used to compare (>, <, =, etc).
Signal Side: Whether you want to highlight bullish (“Buy”) or bearish (“Sell”) bars.
Tips for Getting More Value
Start Simple—try just one or two conditions at first. See what lights up. Slowly add more logic as you get comfortable.
Watch the chart live as you change settings. The labels update instantly—this makes strategy design fast and visual!
Try flipping your ideas: If a certain pattern doesn’t work for buys, try reversing the direction for possible “sell” setups.
Remember: There is NO wrong idea. This indicator is only limited by your creativity—it’s a “strategy playground.”
Example Quick-Start Recipes
Classic Sell:
4 candles, side = Sell
Candle0 Body > Candle2; Candle1 Body > Candle3
Candle0 Vol <= Candle2; Candle1 Vol <= Candle2; Candle3 Vol <= Candle2 × 0.5
Simple Buy After Pause:
3 candles, side = Buy
Candle0 Body > Candle1; Candle0 Vol > Candle1
All other Ops blank
Low-Volume Pullback for Entry:
4 candles, side = Buy
Candle0 Body > Candle2
Candle0 Vol < Candle1; Candle1 Vol < Candle2; Candle2 Vol < Candle3
Final Words
Think of this as your “pattern lab.” No code, no guesswork—just experiment, see what the market actually gives, and design your own visual rulebook.
If you’re stuck, reset the script to defaults—it’s always safe to start again!
If you want more ready-made “recipes” for different strategies/styles, just ask and I’ll send some more setups for you.
Happy building—and may your edge always be YOUR edge!
AI-Weighted RSI (Zeiierman)█ Overview
AI-Weighted RSI (Zeiierman) is an adaptive oscillator that enhances classic RSI by applying a correlation-weighted prediction layer. Instead of looking only at RSI values directly, this indicator continuously evaluates how other price- and volume-based features (returns, volatility, volume shifts) correlate with RSI, and then weights them accordingly to project the next RSI state.
The result is a smoother, forward-looking RSI framework that adapts to market conditions in real time.
By leveraging feature correlation instead of static formulas, AI-Weighted RSI behaves like a lightweight learning model, adjusting its emphasis depending on which features are most aligned with RSI behavior during the current regime.
█ How It Works
⚪ Feature Extraction
Each bar, the script computes features: log returns, RSI itself, ATR% (volatility), volume, and volume log-change.
⚪ Correlation Screening
Over a rolling learning window, it measures the correlation of each feature against RSI. The strongest relationships are ranked and selected.
⚪ Adaptive Weighting
Features are standardized (z-scored), then combined using their signed correlations as weights, building a rolling, adaptive prediction of RSI.
⚪ Prediction to RSI Weight
The predicted RSI is mapped back into a “weight” scale (±2 by default). Above 0 = bullish bias, below 0 = bearish bias, with color-graded fills to visualize overbought/oversold pressure.
⚪ Signal Line
A smoothing option (signal length) overlays a moving average of the AI-Weighted RSI for clearer trend confirmation.
█ Why AI-Weighted RSI
⚪ Adaptive to Market Regime
Because the model re-evaluates correlations continuously, it naturally shifts which features dominate, sometimes volatility explains RSI best, sometimes volume, sometimes returns.
⚪ Forward-Looking Bias
Instead of simply reflecting RSI, the model provides a projection, helping anticipate shifts in momentum before RSI itself flips.
█ How to Use
⚪ Directional Bias
Read the RSI relative to 0. Above = bullish momentum bias, below = bearish.
⚪ Overbought / Oversold Zones
Shaded fills beyond +0.5 or -0.5 highlight extremes where RSI pressure often exhausts.
⚪ Divergences
When price makes new highs/lows but AI-Weighted RSI fails to confirm, it often signals weakening momentum.
█ Settings
RSI Length: Lookback for the core RSI calculation.
Signal Length: Smoothing applied to the AI-Weighted RSI output.
Learning Window: Bars used for correlation learning and z-scoring.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Stop Loss vs Take Profit Probability and EVThis stop loss and take profit calculator uses a Monte Carlo simulation to calculate the probability of hitting your Stop Loss or Take Profit levels across different time horizons (expressed in bars).
It provides data-driven insights to optimize your risk management and position sizing by showing Expected Value for each scenario.
As a quant, I love using statistical data to help my decisions and get better EV from my trades.
🔬 How It's Calculated
Monte Carlo Simulation: Runs 1,000-10,000 price simulations using a random walk model
Volatility Analysis: Combines ATR-based and Historical Volatility for accurate price movement modeling
Expected Value: Calculates profit/loss expectation using formula: (TP_Probability × Reward) - (SL_Probability × Risk)
Time Horizons: Tests multiple timeframes (1, 5, 10, 20, 50 bars) to find optimal holding periods
Risk/Reward Ratios: Automatically calculates and displays R:R ratios for quick assessment
💡 Use Cases
Position Sizing - Determine optimal risk per trade based on Expected Value
Time Horizon Optimization - Find the best holding period for your strategy
Stop Loss Placement - Validate SL levels using probability analysis
Take Profit Optimization - Set TP levels with statistical backing
Strategy Backtesting - Compare different R:R setups before entering trades
Risk Management - Avoid trades with negative Expected Value
Swing vs Day Trading - Choose timeframes with highest success probability
🎯 How to Use
Setup Trade: Enter your entry price, stop loss, and take profit levels
You can add or remove time horizons denominated in bars. Say you are looking at 1h candles, adding a 24-bar time horizon means you are looking into 24 hours
Choose Direction: Select Long or Short position
Review Table
Analyze Expected Value: Focus on positive EV scenarios (green background)
Optimize Timing: Select time horizons with best risk/reward profile
Adjust Parameters: Modify volatility calculation method and simulation count if needed
Examples
Here's how you can read the tables.
Example 1:
In this chart, we are analyzing the TP and SL probabilities as well as the EV (expected value) for a stock. I want to check what the likelihood is that my SL and TP get triggered over the next 5 days. The stock market is open for 6.5 hours per day, which is 13 bars in this 30-minute bar chart. 26 bars is 2 days, 39 bars is 3 days and so on.
Although this trade is more likely to trigger my SL than my TP, in some of the time horizons we have a positive expected value because of the risk/reward of our trade (i.e. distance of the SL and TP from the price) and the probability of hitting SL and TP.
Example 2:
In this example, we have applied the indicator to gold. Because the TP is much closer to the price, the probability of hitting the TP is much higher.
We can also observe that the expected Value in the shorter time frames is better than in the longer ones. This can give us some clues to set up our trade. If we know that the EV is positive, we can allocate more to that specific trade.
Enjoy, and please let me know your feedback! 😊🥂
4 DU DINHSample Indicator Introduction (English)
Title:
Adaptive Trend & Momentum Indicator
Short Description:
An adaptive indicator that combines trend detection and momentum confirmation to help identify potential entry and exit points in various markets.
Full Description:
This indicator is designed to provide traders with a clear view of both trend direction and momentum strength. It dynamically adjusts to different market conditions, making it suitable for cryptocurrencies, stocks, and forex.
Main Features:
Trend Identification: Uses adaptive moving averages to detect bullish or bearish market phases.
Momentum Confirmation: Integrates oscillator-based signals to reduce false entries during sideways markets.
Customizable Inputs: Adjustable sensitivity, smoothing factors, and signal thresholds.
Non-repainting Logic: Signals are only confirmed after candle close to avoid misleading entries.
How to Use:
A bullish signal occurs when trend direction turns positive and momentum confirms.
A bearish signal occurs when trend direction turns negative with momentum confirmation.
Recommended for H1 and higher timeframes, but can be tuned for intraday strategies.
⚠️ Disclaimer: This indicator is for educational purposes only. It does not guarantee profits. Always combine with proper risk management and backtesting before trading live.
Simplified Market ForecastSimplified Market Forecast Indicator
This indicator pairs nicely with the Contrarian 100 MA and can be located here:
Overview
The "Simplified Market Forecast" (SMF) indicator is a streamlined technical analysis tool designed for traders to identify potential buy and sell opportunities based on a momentum-based oscillator. By analyzing price movements relative to a defined lookback period, SMF generates clear buy and sell signals when the oscillator crosses customizable threshold levels. This indicator is versatile, suitable for various markets (e.g., forex, stocks, cryptocurrencies), and optimized for daily timeframes, though it can be adapted to other timeframes with proper testing. Its intuitive design and visual cues make it accessible for both novice and experienced traders.
How It Works
The SMF indicator calculates a momentum oscillator based on the price’s position within a specified range over a user-defined lookback period. It then smooths this value to reduce noise and plots the result as a line in a separate lower pane. Buy and sell signals are generated when the smoothed oscillator crosses above a user-defined buy level or below a user-defined sell level, respectively. These signals are visualized as triangles either on the main chart or in the lower pane, with a table displaying the current ticker and oscillator value for quick reference.
Key Components
Momentum Oscillator: The indicator measures the price’s position relative to the highest high and lowest low over a specified period, normalized to a 0–100 scale.
Signal Generation: Buy signals occur when the oscillator crosses above the buy level (default: 15), indicating potential oversold conditions. Sell signals occur when the oscillator crosses below the sell level (default: 85), suggesting potential overbought conditions.
Visual Aids: The indicator includes customizable horizontal lines for buy and sell levels, shaded zones for clarity, and a table showing the ticker and current oscillator value.
Mathematical Concepts
Oscillator Calculation: The indicator uses the following formula to compute the raw oscillator value:
c1I = close - lowest(low, medLen)
c2I = highest(high, medLen) - lowest(low, medLen)
fastK_I = (c1I / c2I) * 100
The result is smoothed using a 5-period Simple Moving Average (SMA) to produce the final oscillator value (inter).
Signal Logic:
A buy signal is triggered when the smoothed oscillator crosses above the buy level (ta.crossover(inter, buyLevel)).
A sell signal is triggered when the smoothed oscillator crosses below the sell level (ta.crossunder(inter, sellLevel)).
Entry and Exit Rules
Buy Signal (Blue Triangle): Triggered when the oscillator crosses above the buy level (default: 15), indicating a potential oversold condition and a buying opportunity. The signal appears as a blue triangle either below the price bar (if plotted on the main chart) or at the bottom of the lower pane.
Sell Signal (White Triangle): Triggered when the oscillator crosses below the sell level (default: 85), indicating a potential overbought condition and a selling opportunity. The signal appears as a white triangle either above the price bar (if plotted on the main chart) or at the top of the lower pane.
Exit Rules: Traders can exit positions when an opposite signal occurs (e.g., exit a buy on a sell signal) or based on additional technical analysis tools (e.g., support/resistance, trendlines). Always apply proper risk management.
Recommended Usage
The SMF indicator is optimized for the daily timeframe but can be adapted to other timeframes (e.g., 1H, 4H) with careful testing. It performs best in markets with clear momentum shifts, such as trending or range-bound conditions. Traders should:
Backtest the indicator on their chosen asset and timeframe to validate signal reliability.
Combine with other indicators (e.g., moving averages, support/resistance) or price action for confirmation.
Adjust the lookback period and buy/sell levels to suit market volatility and trading style.
Customization Options
Intermediate Length: Adjust the lookback period for the oscillator calculation (default: 31 bars).
Buy/Sell Levels: Customize the threshold levels for buy (default: 15) and sell (default: 85) signals.
Colors: Modify the colors of the oscillator line, buy/sell signals, and threshold lines.
Signal Display: Toggle whether signals appear on the main chart or in the lower pane.
Visual Aids: The indicator includes dotted horizontal lines at the buy (green) and sell (red) levels, with shaded zones between 0–buy level (green) and sell level–100 (red) for clarity.
Ticker Table: A table in the top-right corner displays the current ticker and oscillator value (in percentage), with customizable colors.
Why Use This Indicator?
The "Simplified Market Forecast" indicator provides a straightforward, momentum-based approach to identifying potential reversals in overbought or oversold markets. Its clear signals, customizable settings, and visual aids make it easy to integrate into various trading strategies. Whether you’re a swing trader or a day trader, SMF offers a reliable tool to enhance decision-making and improve market timing.
Tips for Users
Test the indicator thoroughly on your chosen asset and timeframe to optimize settings.
Use in conjunction with other technical tools for stronger trade confirmation.
Adjust the buy and sell levels based on market conditions (e.g., lower levels for less volatile markets).
Monitor the ticker table for real-time oscillator values to gauge market momentum.
Happy trading with the Simplified Market Forecast indicator!
Stock Scoring SystemThe EMA Scoring System is designed to help traders quickly assess market trend strength and decide portfolio allocation. It compares price vs. key EMAs (21, 50, 100) and also checks the relative strength between EMAs. Based on these conditions, it assigns a score (-6 to +6) and a corresponding allocation percentage.
+6 Score = 100% allocation (strong bullish trend)
-6 Score = 10% allocation (strong bearish trend)
Scores in between represent intermediate trend strength.
📌 Key Features
✅ Scoring Model: Evaluates price vs. EMA alignment and EMA cross relationships.
✅ Allocation % Display: Converts score into suggested portfolio allocation.
✅ Background Highlighting: Green shades for bullish conditions, red shades for bearish.
✅ Customizable Table Position: Choose between Top Right, Top Center, Bottom Right, or Bottom Center.
✅ Toggleable EMAs: Show/Hide 21 EMA, 50 EMA, and 100 EMA directly from indicator settings.
✅ Simple & Intuitive: One glance at the chart tells you trend strength and suggested allocation.
📈 How It Works
Score Calculation:
Price above an EMA = +1, below = -1
Faster EMA above slower EMA = +1, else -1
Maximum score = +6, minimum = -6
Allocation Mapping:
+6 → 100% allocation
+4 to +5 → 100% allocation
+2 to +3 → 75% allocation
0 to +1 → 50% allocation
-1 to -2 → 30% allocation
-3 to -4 → 20% allocation
-5 to -6 → 10% allocation
Visual Output:
Table shows SCORE + Allocation %
Background color shifts with score (green for bullish, red for bearish)
⚠️ Disclaimer
This indicator is for educational purposes only. It does not constitute financial advice. Always backtest and combine with your own analysis before making trading decisions.
Analyst Targets ProbabilityThis indicator calculates the probability of the current stock price reaching or exceeding the analyst-provided high, average, and low price targets within a one-year time horizon. It utilizes a geometric Brownian motion (GBM) model, a standard approach in financial modeling that assumes log-normal price distribution with constant volatility.
### Key Features:
- **Analyst Targets**: Automatically pulls the high, average, and low one-year price targets from TradingView's syminfo data.
- **Risk-Free Rate**: Fetched from the 1-year US Treasury yield (symbol: TVC:US01Y). Defaults to 4% if unavailable.
- **Dividend Yield**: Uses trailing twelve-month (TTM) dividends per share (DPS) from financial data, divided by current price. Defaults to 0% if unavailable.
- **Volatility**: Computed as annualized historical volatility based on 252 trading days of daily log returns. Falls back to a 20-day period if insufficient data, or defaults to 30% if still unavailable.
- **Probability Calculation**: Employs the barrier hitting probability formula under GBM:
- Drift (μ) = risk-free rate - dividend yield - (volatility² / 2)
- The formula for probability P of hitting target H from current price S₀ over time T is:
P = Φ(d₊) + (H / S₀)^p ⋅ Φ(d₋) for H > S₀ (or adjusted for H < S₀)
Where l = ln(max(H, S₀)/min(H, S₀)), ν = drift, p = -2ν / σ², d₊ = (-l + νT) / (σ√T), d₋ = (-l - νT) / (σ√T), and Φ is the standard normal CDF (approximated using a polynomial method for accuracy).
- **Output Display**: A table in the top-right corner shows each target type, its value, and the estimated probability (as a percentage). "N/A" appears if data is unavailable or calculations cannot proceed (e.g., zero volatility).
### Assumptions and Limitations:
- Assumes constant volatility and drift, no transaction costs, and continuous trading (real markets may deviate due to jumps, news events, or changing conditions).
- Probabilities are model-based estimates and not guarantees; they represent the likelihood under risk-neutral measure.
- Best suited for stocks with available analyst targets and historical data; may default to assumptions for less-liquid symbols.
- No user inputs required—fully automated using TradingView's data sources.
This script is provided under the Mozilla Public License 2.0. For educational and informational purposes only; not financial advice. Test on your charts and consider backtesting for validation.
Vagas-dctang(8~13)Overview
The Vegas Tunnel EMA 8-13 is a refined technical analysis indicator that utilizes two key exponential moving averages (8-period and 13-period EMAs) to create a dynamic tunnel system for identifying trend direction and potential support/resistance zones. This indicator is specifically designed to help traders visualize price action within the context of short-term trend dynamics.
Key Features
✅ Dual EMA Tunnel System: Creates a visual tunnel between 8 EMA (fast) and 13 EMA (slow) to identify trend channels ✅ Dynamic Support Detection: The tunnel acts as dynamic support during uptrends and resistance during downtrends ✅ Trend Confirmation: Price position relative to the tunnel helps confirm the current market trend ✅ Entry/Exit Signals: Tunnel crossovers and price interactions provide clear trading signals ✅ Multi-Timeframe Compatible: Works effectively across various timeframes from scalping to swing trading
How It Works
The Vegas Tunnel EMA 8-13 operates on the principle that shorter-period EMAs react more quickly to price changes, creating a responsive tunnel system:
Bullish Tunnel: When 8 EMA > 13 EMA, the tunnel indicates an upward trend with potential support zones
Bearish Tunnel: When 8 EMA < 13 EMA, the tunnel indicates a downward trend with potential resistance zones
Tunnel Width: The distance between EMAs indicates trend strength and volatility
Price Interaction: Bounces off the tunnel boundaries suggest trend continuation, while breaks may signal reversals
Trading Applications
Trend Following: Use tunnel direction to align trades with the prevailing trend
Support/Resistance Trading: Enter long positions when price bounces off tunnel support, short when rejected at resistance
Breakout Strategy: Trade tunnel breaks as potential trend continuation or reversal signals
Risk Management: Use tunnel boundaries as dynamic stop-loss levels
Advantages Over Traditional Moving Averages
Reduced Noise: The tunnel system filters out minor price fluctuations
Visual Clarity: Easy identification of trend channels and key levels
Faster Response: 8-13 period combination provides quicker signals than longer-term systems
Versatile Application: Suitable for various trading styles and market conditions
Best Practices
Combine with volume analysis for stronger signal confirmation
Consider higher timeframe tunnel direction for context
Use proper risk management with position sizing
Backtest on your preferred instruments and timeframes
This indicator is ideal for traders seeking a clean, effective tool for trend analysis and dynamic support/resistance identification in fast-moving markets.
Triple Tap Sniper Triple Tap Sniper v3 – EMA Retest Precision System
Triple Tap Sniper is a precision trading tool built around the 21, 34, and 55 EMAs, designed to capture high-probability retests after EMA crosses. Instead of chasing the first breakout candle, the system waits for the first pullback into the EMA21 after a trend-confirming cross — the spot where professional traders often enter.
🔑 Core Logic
EMA Alignment → Trend defined by EMA21 > EMA34 > EMA55 (bullish) or EMA21 < EMA34 < EMA55 (bearish).
Cross Detection → Signals are only armed after a fresh EMA cross.
Retest Entry → Buy/Sell signals fire only on the first retest of EMA21, with trend still intact.
Pro Filters →
📊 Higher Timeframe Confirmation: Aligns signals with larger trend.
📈 ATR Volatility Filter: Blocks weak signals in low-vol chop.
📏 EMA Spread Filter: Ignores tiny “fake crosses.”
🕯️ Price Action Filter: Requires a proper wick rejection for valid entries.
🚀 Why Use Triple Tap Sniper?
✅ Filters out most false signals from sideways markets.
✅ Focuses only on clean trend continuations after pullbacks.
✅ Beginner-friendly visuals (Buy/Sell labels) + alert-ready for automation.
✅ Flexible: works across multiple timeframes & asset classes (stocks, crypto, forex).
⚠️ Notes
This is a signal indicator, not a full strategy. For backtesting and optimization, convert to a strategy and adjust filters per market/timeframe.
No indicator guarantees profits — use with sound risk management.
MA Availability ETA (SMA100/EMA200)This tool helps traders understand when long-term moving averages become available on any chosen timeframe.
Many new symbols, pairs, or timeframes don’t have enough price history to immediately plot long moving averages like SMA(100) and EMA(200). This script calculates and displays:
✅ Bars Remaining – how many bars are still needed before each moving average can be plotted reliably.
✅ ETA Duration – an estimate of how long (in chart time units) it will take until each MA is available.
✅ Status Table & Label – compact visual summary on the chart and in a table at the top-right corner.
✅ Vertical Marker – a dotted line showing exactly where both SMA(100) & EMA(200) first appear together.
✅ Alerts – optional alerts notify you the moment SMA(100) or EMA(200) become available.
🔑 Features
Works on any timeframe and instrument.
Highlights SMA(100) and EMA(200) on the chart for reference.
Lets you choose whether EMA(200) should be considered ready immediately, or only after a full 200-bar history.
Useful for traders who rely on long-term MA signals (golden cross, dynamic support/resistance, trend confirmation) and want to know when these tools will be ready on fresh charts.
🎯 Use Cases
New listings / low-history assets → See when SMA100 & EMA200 become usable.
Backtesting or forward-testing → Anticipate when long-term signals will first appear.
Trend-following strategies → Prepare in advance for crossovers or key support/resistance confluence zones.
⚠️ Note: ETAs are based on chart resolution and assume continuous data; real-world session gaps, weekends, or illiquid trading can make availability slightly later.
👉 Add this to your chart and you’ll always know when the big moving averages arrive — a critical moment for many upside moves and long-term strategies.
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
