DV Master RSIDV Master RSI
Executive Summary
The Relative Strength Index (RSI) is one of the most foundational and widely utilized momentum oscillators in technical analysis. While traditionally used to gauge overbought and oversold conditions, its true power lies in identifying subtle shifts in market momentum and divergence from price action. The DV Master RSI Indicator is a sophisticated Pine Script tool designed to leverage the full strategic potential of the RSI by integrating multiple advanced signaling methods, comprehensive visual customization, and a robust anti-repainting feature. This indicator transforms the classic RSI into a complete, multi-signal trading system.
Key Advanced Features of the DV Master RSI
This indicator is engineered to provide traders with comprehensive momentum analysis and actionable signals through several integrated modules:
Features
Momentum Signaling:
RSI Midline Cross (50-line) Confirms shifts from bearish to bullish momentum and vice-versa.
RSI Moving Average Crossover:
Provides smoothed, less noisy trend confirmation and early entry/exit signals.
Trend Confirmation:
RSI MA Midline Cross uses the trend of the RSI's Moving Average to confirm the overall market bias.
Overbought/Oversold Signals
Visually highlights extreme momentum conditions for potential reversals.
Predictive Analysis
Bullish & Bearish Divergence identifies classic market turning points when price makes new highs/lows but RSI does not.
Hidden Divergence
Signals trend continuation, indicating strong internal momentum supporting the current trend.
Performance Assurance
Anti-Repainting Switch ensures signal integrity for backtesting and live trading by locking critical values on bar closure.
Visual Customization
10 Color Palettes & Background Painting enhances clarity and trading focus with custom colors and visual alerts on the chart and indicator panel.
Strategic Application for Traders
The integration of these features allows traders to employ strategies far beyond simple overbought/oversold monitoring.
Divergence Trading (Predictive Edge):
Divergence is often considered the most powerful signal from a momentum oscillator.
Regular Divergence (Reversal):
When the price makes a Lower Low but the RSI makes a Higher Low, it suggests the downward momentum is weakening, signaling a potential Bullish Reversal. The indicator plots this signal directly, giving traders an early warning to cover shorts or initiate long positions.
Hidden Divergence (Continuation):
This feature is crucial for trend-following. When the price makes a Higher Low but the RSI makes a Lower Low (during an uptrend), it signals that the trend is strong and likely to continue. Traders can use this for confident re-entry into established trends.
Signal Integrity and Backtesting Reliability:
The dedicated Anti-Repainting Switch is paramount for serious algorithmic and discretionary traders.
Problem: Indicators that use real-time price data (like close on the current bar) can change their signal retroactively as the current bar develops. This leads to illusory performance in backtesting.
Solution: By enabling the non-repainting mode, the indicator ensures that all crucial signals (MA Crosses, Midline Crosses, etc.) are only finalized and plotted upon the full confirmation of the bar's closure. This guarantees that your backtested results accurately reflect what would have been tradable in real-time.
Customizable Smoothing:
The inclusion of nine different Moving Average types (EMA, DEMA, TEMA, HMA, SMA, SMA + Bollinger Bands, SMMA, WMA, VWMA) for the RSI line allows a trader to fine-tune the indicator's responsiveness to market noise.
A trader expecting a fast reaction to short-term events might use an EMA.
A trader looking for robust, volume-weighted confirmation might select the VWMA.
Furthermore, the dedicated switches for background color on the chart and the indicator panel provide immediate, non-intrusive visual confirmation of extreme conditions, allowing traders to quickly manage multiple charts.
The DV Master RSI is an essential upgrade for any trader who relies on momentum analysis, providing the precision, assurance, and strategic versatility required for modern market navigation.
震盪指標
Kuytrade - Super Scalping Pro V1.0📘 Strategy "Kuytrade - Super Scalping Pro"
What is this strategy?
This is a scalping trading that helps you catch quick profits from short-term price movements. It's perfect for traders who want to make multiple small wins throughout the day.
How does it work?
The strategy uses a 3-level filter system to find high-quality trading signals:
Level 1: CORE Indicators (Must Pass)
- EMA (Moving Averages): Checks if the trend is going up or down
- MACD: Confirms momentum is building in the right direction
Level 2: MOMENTUM Indicators
- RSI: Looks for oversold (ready to bounce up) or overbought (ready to drop) conditions
- Stochastic: Finds reversal points where price might change direction
Level 3: BOOST Indicators
- RSI Divergence: Spots hidden opportunities when price and momentum disagree
- Strong Candles: Identifies powerful price movements
- ATR Filter: Makes sure the market is active enough to trade
Trading Setup
Each Signal Opens 3 Orders:
Order 1: Closes at TP1 (quick small profit)
Order 2: Closes at TP2 (medium profit)
Order 3: Closes at TP3 (big profit target)
Default Settings:
TP1: 1,000 points
TP2: 1,500 points
TP3: 2,500 points
Stop Loss: 1,200 points
Lot Size: 0.01 per order (3 orders total)
Smart Features
- Trailing Stop Loss
- When TP1 hits, the Stop Loss for TP3 automatically moves to breakeven + 150 points, protecting your profit!
- Auto Asset Detection
The strategy automatically recognizes what you're trading:
- Forex pairs (EURUSD, GBPUSD, etc.)
- Gold, Silver, Platinum
- Crypto (Bitcoin, Ethereum)
- Stock Indices (US30, NASDAQ, S&P500)
Indicators:
You can enable/disable each indicator level
Mix and match to find what works for your style
Visuals:
Show/Hide TP/SL lines
Show/Hide entry boxes
Mobile view for smaller screens
When to Use This Strategy?
✅ Best for:
Active markets (London/NY sessions)
Lower timeframes (1m, 5m, 15m)
Volatile pairs with clear trends
❌ Avoid during:
Major news releases
Very quiet markets
Weekends/holidays
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กลยุทธ์นี้คืออะไร?
Scalping ที่ออกแบบมาให้ช่วยทำกำไรเล็กๆ จากการเคลื่อนไหวของราคาระยะสั้น เหมาะสำหรับเทรดเดอร์ที่ต้องการทำกำไรเล็กน้อยบ่อยๆ ตลอดทั้งวัน
ทำงานยังไง?
กลยุทธ์ใช้ระบบกรองสัญญาณ 3 ระดับ เพื่อหาจุดเข้าที่มีคุณภาพสูง
Level 1: ตัวบ่งชี้หลัก (ต้องผ่าน)
- EMA (เส้นค่าเฉลี่ย): เช็คว่าเทรนด์กำลังขึ้นหรือลง
- MACD: ยืนยันว่าแรงซื้อ/ขายกำลังมาถูกทาง
Level 2: ตัวบ่งชี้โมเมนตัม
- RSI: หาจุด Oversold (ราคาถูกเกินไป พร้อมกลับตัว) หรือ Overbought (ราคาแพงเกิน พร้อมลง)
- Stochastic: หาจุดกลับตัวที่ราคาอาจจะเปลี่ยนทิศ
Level 3: ตัวบ่งชี้เสริม
- RSI Divergence: เจอโอกาสแอบแฝงเมื่อราคาและโมเมนตัมไม่สอดคล้องกัน
- Strong Candles: จับแท่งเทียนที่แรงมาก
- ATR Filter: ตรวจว่าตลาดมีความผันผวนพอจะเทรดไหม
การตั้งค่าการเทรด
แต่ละสัญญาณเปิด 3 ออเดอร์:
ออเดอร์ 1: ปิดที่ TP1 (กำไรเล็กเร็ว)
ออเดอร์ 2: ปิดที่ TP2 (กำไรกลางๆ)
ออเดอร์ 3: ปิดที่ TP3 (กำไรใหญ่)
ค่าเริ่มต้น:
TP1: 800 จุด
TP2: 1,500 จุด
TP3: 2,500 จุด
Stop Loss: 1,200 จุด
ขนาดล็อต: 0.01 ต่อออเดอร์ (รวม 3 ออเดอร์)
ฟีเจอร์พิเศษ
- Trailing Stop Loss (ขยับ SL ตาม)
- เมื่อ TP1 โดน SL ของ TP3 จะเลื่อนมาที่ราคาเข้า + 150 จุด ทำให้คุณไม่ขาดทุน!
- ตรวจจับสินทรัพย์อัตโนมัติ
กลยุทธ์จะจำคู่เงินที่คุณเทรดได้เอง:
คู่เงิน Forex (EURUSD, GBPUSD ฯลฯ)
- ทองคำ, เงิน, แพลตตินั่ม
- คริปโต (Bitcoin, Ethereum)
- ดัชนีหุ้น (US30, NASDAQ, S&P500)
แดชบอร์ดผลงาน (ล่างซ้าย)
- แสดง Win Rate แต่ละ TP
- ติดตามกำไร/ขาดทุนรวม
- แสดงสถิติทั้งหมด
แดชบอร์ดสถานะ Level (บนขวา)
สถานะตัวบ่งชี้แบบเรียลไทม์
เขียว = สัญญาณพร้อม
แดง = รอเงื่อนไข
ตั้งค่าที่ปรับได้
คุณภาพสัญญาณ:
เปิด "Strict Filter" = สัญญาณน้อยแต่คุณภาพสูง
ปิด "Strict Filter" = สัญญาณเยอะแต่อาจเสี่ยงขึ้น
ตัวบ่งชี้:
- เปิด/ปิดแต่ละ Level ได้
- ผสมผสานหาสูตรที่เหมาะกับคุณ
การแสดงผล:
- แสดง/ซ่อนเส้น TP/SL
- แสดง/ซ่อนกล่องข้อมูล Entry
- โหมดมือถือสำหรับจอเล็ก
เมื่อไหร่ควรใช้กลยุทธ์นี้?
✅ เหมาะกับ:
- ตลาดที่คึกคัก (เซสชั่นลอนดอน/นิวยอร์ก)
- ไทม์เฟรมเล็ก (1m, 5m, 15m)
- คู่เงินที่มีความผันผวนและเทรนด์ชัด
❌ หลีกเลี่ยง:
- ช่วงมีข่าวเศรษฐกิจสำคัญ
- ตลาดเงียบมาก
- วันหยุดสุดสัปดาห์
Alpha-Vector Unconstrained [GG_DOGE]
Alpha-Vector: Variance-Weighted Trend Capture Protocol
Authored by: GG_DOGE
Executive Summary
This algorithm represents the culmination of an exhaustive quantitative regression analysis, designed to exploit fat-tail distribution events in the SOL/USD cryptographic pair. By leveraging recursive historical data modeling on the 8-Hour timeframe, the strategy identifies high-probability momentum asymmetry—specifically isolating periods where directional volatility aligns with institutional order flow.
Unlike static heuristic models, this protocol utilizes a Dynamic Variance-Weighted Allocation Engine. This ensures that capital exposure is inversely correlated to market noise (entropy) while maximizing geometric compounding during high-conviction momentum phases. It essentially acts as a volatility filter, capitalizing on the statistical skew of the asset's return profile while enforcing rigorous drawdown mitigation via adaptive liquidity exits.
Key Algorithmic Features
Asymmetric Risk Architecture: The strategy deploys decoupled risk profiles for Long and Short vectors. Through backtest optimization, we have mathematically determined that bullish drift requires aggressive variance targeting, while bearish mean-reversion requires strictly constrained capital exposure to mitigate "short-squeeze" tail risks.
Volatility-Adjusted Position Sizing: Trade depth is not static. The algorithm calculates the instantaneous Average True Range (ATR) to normalize position size based on current market turbulence. This maintains a constant Risk-of-Ruin probability, regardless of price velocity.
Quantitatively Optimized Trend Filter: The entry signal is governed by a proprietary lookback period derived from computational brute-forcing of historical pivot points, designed to filter out Gaussian noise and only execute during significant structural market shifts.
Operational Guide (Strict Adherence Required)
This script comes pre-loaded with the statistically optimal parameters for the analyzed asset. No manual calibration is required.
Deployment Target:
Asset: CRYPTO:SOLUSD (Solana / US Dollar)
Timeframe: 8h (8-Hour Candle)
Exchange: Any major liquidity venue (Binance, Coinbase, Kraken, etc.)
Configuration:
Strategy Mode: Select "Long & Short" for the fully optimized protocol (captures upside momentum and hedges downside crashes).
Risk Parameters: The default values are mathematically tuned for maximum geometric growth (Highest PnL). Do not alter these unless you wish to artificially suppress the algorithm's volatility targeting.
Execution:
Capital Allocation: The logic is designed for compounding growth. It will automatically calculate the maximum lot size allowed based on your account equity, ensuring 100% capital efficiency without crossing into margin-call territory
Smart Divergence Engine [ChartNation]SMART DIVERGENCE ENGINE — REPAINTING-PROOF RSI DIVERGENCE WITH EXHAUSTION CONFIRMATION
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Smart Divergence Engine solves three critical problems that plague free RSI divergence indicators:
PROBLEM 1: REPAINTING DIVERGENCES
Most divergence scripts detect divergence in real-time as bars form. This causes signals to appear, disappear, and reappear unpredictably—making them unusable for alerts or systematic trading.
OUR SOLUTION: Pivot-Locked Detection
Smart Divergence Engine evaluates RSI at the exact bar where price structure confirms (rsi ), not at the current bar. Once a divergence prints, it NEVER disappears. This is implemented via:
Full swing confirmation (Pivot Left + Pivot Right bars must complete)
RSI evaluation at historical bar: rsi , not rsi
Divergence triggers AFTER structure lock, not during formation
Technical implementation: The script stores RSI values at confirmed pivot bars using var floats (lowRsiPrev, lowRsiCurr, highRsiPrev, highRsiCurr), then compares these locked values when new pivots confirm. This prevents any possibility of historical repaint.
PROBLEM 2: FALSE POSITIVE OVERLOAD
Divergence scripts trigger on ANY price-RSI mismatch, flooding charts with weak signals during choppy conditions. No filtering means traders must manually screen out noise.
OUR SOLUTION: Shark Fin Exhaustion Filter
Before any divergence can be considered actionable, Smart Divergence Engine requires RSI to demonstrate genuine momentum exhaustion through our proprietary "Shark Fin" detection:
Shark Fin Logic (Not Found in Free Scripts):
RSI must pierce the outer volatility band by a configurable buffer (default 1.5 RSI points)
RSI must re-enter the band with directional confirmation (positive slope for bullish, negative slope for bearish)
Band width must exceed minimum standard deviation threshold (volatility qualification)
Cooldown period enforced (default 25 bars) to prevent signal clustering
This multi-condition filter dramatically reduces false divergences by requiring RSI to physically demonstrate exhaustion BEFORE structure confirmation matters.
Technical implementation: The Shark Fin state machine uses boolean flags (bullFinForming, bearFinForming) to track when RSI is stretched beyond bands, then validates re-entry using ta.crossover(rsi, lower) / ta.crossunder(rsi, upper) with slope checks (ta.change(rsi) > 0 / < 0) and volatility gates (dev >= finMinDev).
PROBLEM 3: NO VOLATILITY CONTEXT
Divergence scripts use fixed RSI levels (30/70 or similar) that fail to adapt to changing market conditions. What's "overbought" in a low-volatility regime differs drastically from high-volatility conditions.
OUR SOLUTION: Adaptive Volatility Bands
Smart Divergence Engine calculates dynamic overbought/oversold zones using:
34-period SMA of RSI as basis
1.618 standard deviation multiplier (golden ratio expansion)
Real-time band expansion/contraction based on RSI volatility
The bands provide three advantages:
Shark Fin events only qualify when RSI breaches ADAPTIVE thresholds, not arbitrary fixed levels
Band width (standard deviation) serves as volatility filter—narrow bands = low conviction moves get rejected
50-line midline provides regime context (above 50 = bullish bias, below 50 = bearish bias)
Technical implementation: basis = ta.sma(rsi, 34), dev = ta.stdev(rsi, 34), upper/lower = basis ± dev * 1.618. Shark Fin logic requires rsi < (lower - finBuffer) or rsi > (upper + finBuffer) to trigger, ensuring exhaustion is measured relative to CURRENT volatility, not historical constants.
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METHODOLOGY COMPARISON VS FREE ALTERNATIVES
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STANDARD DIVERGENCE SCRIPTS:
Detection timing: Real-time (current bar)
Historical stability: Repaints continuously
Signal filtering: None or minimal
Volatility adaptation: Fixed levels (30/70)
Exhaustion confirmation: Not implemented
Confirmation layers: 1 (divergence only)
Alert reliability: Unreliable (signals disappear)
SMART DIVERGENCE ENGINE:
Detection timing: Pivot-confirmed (rsi )
Historical stability: Locked at structure bar
Signal filtering: Shark Fin + cooldown + stdev gate
Volatility adaptation: Dynamic bands (34-SMA + 1.618σ)
Exhaustion confirmation: Required via Shark Fin
Confirmation layers: 3 (structure + exhaustion + volatility)
Alert reliability: Stable (never repaints)
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TECHNICAL SPECIFICATIONS
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RSI ENGINE:
Base calculation: ta.rsi(src, 14)
Smoothing: ta.rma(rsiRaw, 2) — reduces whipsaw noise
Source: Configurable (default close)
VOLATILITY BANDS:
Basis: 34-period SMA of RSI
Multiplier: 1.618 (golden ratio)
Upper band: basis + (stdev * 1.618)
Lower band: basis - (stdev * 1.618)
Purpose: Creates adaptive overbought/oversold zones
DIVERGENCE DETECTION:
Pivot confirmation: 10 left bars + 10 right bars (default)
RSI evaluation: Locked at rsi (historical bar, never current)
Bullish divergence: price lower low + RSI higher low
Bearish divergence: price higher high + RSI lower high
Rendering: Lines drawn between last two confirmed pivots with labels
SHARK FIN EXHAUSTION FILTER:
Depth buffer: 1.5 RSI points (penetration threshold beyond band)
Min band stdev: 1.0 (volatility qualification)
Cooldown: 25 bars minimum between Shark Fin confirmations
Slope validation: Requires ta.change(rsi) > 0 (bullish) or < 0 (bearish)
State tracking: Boolean flags prevent premature confirmations
VISUAL CUSTOMIZATION:
Beauty Mode: Six-layer gradient fill anchored at 50-line
• Purple regime (above 50) with configurable opacity
• Green regime (below 50) with configurable opacity
• Gradient layers: 33%, 66%, 100% intensity
Divergence lines: Glow effect (6px) + core line (3px), both configurable
Shark Fin rendering: 20% fill between RSI and violated band (ephemeral)
Labels: Compact "Bull"/"Bear" markers with dot indicators
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ALERT SYSTEM
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Four distinct alert conditions (configure once, fires on all intervals):
"RSI Shark Fin — Bullish"
Triggers when: RSI re-enters lower band from below with slope + stdev + cooldown confirmation
Use case: Momentum exhaustion at oversold extreme
Reliability: No repaint (confirmation locked at re-entry bar)
"RSI Shark Fin — Bearish"
Triggers when: RSI re-enters upper band from above with slope + stdev + cooldown confirmation
Use case: Momentum exhaustion at overbought extreme
Reliability: No repaint (confirmation locked at re-entry bar)
"Bullish Divergence (Panel)"
Triggers when: Pivot-confirmed bullish divergence completes (price LL + RSI HL)
Timing: Fires AFTER Pivot Right bars complete (delayed but stable)
Reliability: Never repaints (divergence locked at rsi )
"Bearish Divergence (Panel)"
Triggers when: Pivot-confirmed bearish divergence completes (price HH + RSI LH)
Timing: Fires AFTER Pivot Right bars complete (delayed but stable)
Reliability: Never repaints (divergence locked at rsi )
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TRADING IMPLEMENTATION
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CONFLUENCE FRAMEWORK:
Highest-probability setups occur when three conditions align:
Bullish Setup:
Shark Fin confirms below lower band (exhaustion)
Bullish divergence prints at pivot (structure)
RSI reclaims 50 line (regime shift to bullish)
→ Entry consideration at next price structure (support, swing low)
Bearish Setup:
Shark Fin confirms above upper band (exhaustion)
Bearish divergence prints at pivot (structure)
RSI loses 50 line (regime shift to bearish)
→ Entry consideration at next price structure (resistance, swing high)
TREND CONTEXT:
Strong uptrends: Prioritize bullish divergence + lower band Shark Fins (buy dips)
Strong downtrends: Prioritize bearish divergence + upper band Shark Fins (sell rallies)
Range-bound markets: Use 50-line crossovers as additional confirmation filter
RISK MANAGEMENT:
Smart Divergence Engine provides CONTEXT, not entries:
Wait for price confirmation (engulfing candle, rejection wick, structure break)
Place stops below/above pivot structure that triggered divergence
Size positions based on distance to invalidation level
Divergence + Shark Fin = elevated probability, not certainty
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CONFIGURATION PARAMETERS
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RSI SETTINGS:
RSI Length: 14 (default, standard momentum window)
Price Source: close (configurable to any price source)
Note: 2-period RMA smoothing is hardcoded (reduces noise)
VOLATILITY BAND SETTINGS:
Band Length: 34 (SMA period for RSI basis)
Band Multiplier: 1.618 (golden ratio, adjustable)
Show Bands: Toggle visibility (true/false)
DIVERGENCE SETTINGS:
Pivot Left: 10 bars (left-side swing confirmation)
Pivot Right: 10 bars (right-side swing confirmation)
Overbought Level: 68 (reference line, does not affect logic)
Oversold Level: 32 (reference line, does not affect logic)
SHARK FIN SETTINGS:
Fin Depth Buffer: 1.5 RSI points (penetration threshold)
Min Band Stdev: 1.0 (volatility qualification gate)
Min Bars Between Fins: 25 (cooldown period)
VISUAL SETTINGS (Beauty Mode):
Enable Beauty Mode: true/false (gradient rendering)
Divergence Glow: true/false (glow effect on lines)
Glow Width: 3-10 px (glow layer thickness)
Main Line Width: 1-6 px (divergence core line)
Top Color: Purple (configurable, above-50 regime)
Bottom Color: Green (configurable, below-50 regime)
Top Opacity: 0-100% (gradient base transparency)
Bottom Opacity: 0-100% (gradient base transparency)
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PERFORMANCE & LIMITATIONS
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RESOURCE ALLOCATION:
max_lines_count: 500 (divergence + Shark Fin lines)
max_labels_count: 500 (divergence markers)
max_bars_back: 500 (historical pivot lookback)
Suitable for most timeframes; reduce limits if performance degrades on low-end devices
SIGNAL TIMING:
Divergences print AFTER Pivot Right bars complete. This is intentional:
Delayed signals are more reliable than real-time signals
Structure confirmation requires waiting for swing completion
Users demanding instant signals should use free real-time divergence indicators
Users demanding reliable signals that never disappear should use this
PANEL VS OVERLAY:
This is the panel version (overlay=false):
Renders in separate pane below price chart
RSI, bands, divergence lines, and Shark Fin fills appear in this pane
For price-chart annotations, use the companion overlay version (same logic, different rendering)
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This script implements proprietary methodology not available in regular community scripts:
REPAINTING-PROOF ARCHITECTURE
The pivot-locked detection system (rsi evaluation) is a non-trivial implementation that requires:
State management across bars using var variables
Historical RSI value storage at pivot confirmation
Divergence comparison between stored values (not current bar)
This architecture eliminates the #1 complaint with free divergence indicators: disappearing signals.
SHARK FIN EXHAUSTION LOGIC
The multi-condition state machine that validates momentum exhaustion is not found in free scripts:
Penetration threshold (buffer beyond band)
Directional slope confirmation on re-entry
Volatility gate (minimum standard deviation)
Cooldown enforcement (prevents clustering)
This filter layer was developed through extensive backtesting to reduce false divergences during choppy conditions.
ADAPTIVE VOLATILITY FRAMEWORK
The dynamic band system (34-SMA + 1.618σ) provides context-aware overbought/oversold detection:
Bands expand in volatile markets → signals adapt to conditions
Bands contract in ranging markets → tighter detection thresholds
50-line regime framework → directional bias context
This approach outperforms fixed-level systems (30/70) that ignore market context.
CONFLUENCE METHODOLOGY
The three-layer confirmation system (structure + exhaustion + volatility) was engineered to answer: "When is a divergence actually tradeable?" Free scripts detect divergence and stop there. Smart Divergence Engine asks: "Did RSI show exhaustion? Is volatility sufficient? Did structure confirm?"
This level of methodological depth—combined with repainting-proof architecture and professional-grade visual implementation—justifies closed-source protection and paid access.
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Smart Divergence Engine is engineered for traders who demand institutional-grade divergence detection without the noise, repainting, and false positives that plague free alternatives.
Access is restricted to maintain signal quality as methodology evolves.
Smart Divergence Engine Overlay [ChartNation]SMART DIVERGENCE ENGINE OVERLAY — CANDLE-ANCHORED RSI DIVERGENCE VISUALIZATION
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TECHNICAL OVERVIEW
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Smart Divergence Engine Overlay renders pivot-confirmed RSI divergences directly on the price chart with candle-anchored lines and labels. This companion overlay shares the identical detection logic as the panel version but visualizes signals at their exact price levels rather than in oscillator space.
The overlay implements repainting-proof divergence detection through pivot-locked RSI evaluation at historical bars (rsi ), ensuring all lines and labels remain stable as new bars form. Visual elements anchor to xloc.bar_index coordinates, maintaining precise positioning across zoom levels and timeframe changes.
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CORE ARCHITECTURE
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PIVOT-LOCKED DETECTION SYSTEM
The overlay evaluates RSI at confirmed pivot bars, not at the current bar:
Technical implementation:
Price pivots detected via ta.pivotlow() / ta.pivothigh() with configurable Left/Right parameters
RSI value captured at the pivot bar: rsi (historical bar offset)
Divergence comparison performed between stored pivot values (lowRsiPrev vs lowRsiCurr)
State management via var floats prevents recalculation across bars
Result: Once a divergence line prints, it never moves or disappears. Historical stability is guaranteed because RSI evaluation occurs at a locked bar index (bar_index - pivotR), not at the moving present.
Bullish divergence logic:
if not na(lowPricePrev) and lowPriceCurr < lowPricePrev and lowRsiCurr > lowRsiPrev
→ Price made lower low, RSI made higher low
→ Divergence confirmed at lowIdxCurr (pivot bar index)
Bearish divergence logic:
if not na(highPricePrev) and highPriceCurr > highPricePrev and highRsiCurr < highRsiPrev
→ Price made higher high, RSI made lower high
→ Divergence confirmed at highIdxCurr (pivot bar index)
RSI ENGINE
The overlay uses the same RSI calculation as the panel version to ensure signal synchronization:
Base calculation: ta.rsi(src, 14) — standard RSI momentum window
Smoothing layer: ta.rma(rsiRaw, 2) — reduces high-frequency noise
Volatility bands: 34-period SMA basis with 1.618 standard deviation multiplier
Purpose: Bands define adaptive overbought/oversold context (not plotted on overlay)
The volatility framework exists in the calculation layer to maintain logic parity with the panel version, ensuring divergences trigger at identical bars across both implementations.
CANDLE-ANCHORED RENDERING
All visual elements use xloc.bar_index positioning:
Line rendering:
line.new(x1=lowIdxPrev, y1=lowPricePrev, x2=lowIdxCurr, y2=lowPriceCurr,
xloc=xloc.bar_index, color=bullCol, width=lineW)
This anchors lines to specific bar indices and price levels, not to time coordinates. Result: Lines maintain exact positioning when zooming, panning, or switching timeframes.
Label rendering:
label.new(x=lowIdxCurr, y=lowPriceCurr, text="BUY",
xloc=xloc.bar_index, style=label.style_label_up)
Labels attach to the second pivot's bar index and price level, scaling naturally with chart transformations.
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VISUAL IMPLEMENTATION
═══════════════════════════════════════════
DIVERGENCE LINES
Bullish divergence: Connects two price swing lows with upward-sloping line
Color: Configurable (default lime green)
Width: 1-6 pixels (configurable)
Endpoint 1: Previous swing low (lowPricePrev at lowIdxPrev)
Endpoint 2: Current swing low (lowPriceCurr at lowIdxCurr)
Requirement: Current price lower than previous, current RSI higher than previous
Bearish divergence: Connects two price swing highs with downward-sloping line
Color: Configurable (default red)
Width: 1-6 pixels (configurable)
Endpoint 1: Previous swing high (highPricePrev at highIdxPrev)
Endpoint 2: Current swing high (highPriceCurr at highIdxCurr)
Requirement: Current price higher than previous, current RSI lower than previous
Lines extend between pivot bars only (extend.none), never projecting into future.
DIVERGENCE LABELS
Optional BUY/SELL markers render at the second pivot:
BUY label (bullish divergence):
Position: Below current swing low (label.style_label_up)
Text: "BUY"
Color: Matches bullish line color
Size: Normal (size.normal)
SELL label (bearish divergence):
Position: Above current swing high (label.style_label_down)
Text: "SELL"
Color: Matches bearish line color
Size: Normal (size.normal)
Labels can be toggled independently of lines via showLabels input.
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CONFIGURATION PARAMETERS
═══════════════════════════════════════════
RSI CALCULATION SETTINGS:
Price Source: close (configurable to any price field)
RSI Length: 14 (standard momentum window)
Volatility Band Length: 34 (SMA period for RSI basis)
Band Multiplier: 1.618 (standard deviation expansion)
Note: Bands calculate internally but don't plot (logic parity with panel)
DIVERGENCE DETECTION SETTINGS:
Pivot Left: 10 bars (left-side swing confirmation)
Pivot Right: 10 bars (right-side swing confirmation)
Overbought Level: 68 (reference, does not affect logic)
Oversold Level: 32 (reference, does not affect logic)
Pivot parameters control strictness:
Higher values = fewer, more significant divergences (requires wider swings)
Lower values = more frequent divergences (detects smaller swings)
VISUAL SETTINGS:
Show Divergence Lines: true/false toggle
Show BUY/SELL Labels: true/false toggle (independent of lines)
Line Width: 1-6 pixels
Bull Color: Configurable (default lime green)
Bear Color: Configurable (default red)
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ALERT SYSTEM
═══════════════════════════════════════════
Two alert conditions trigger at identical timing as visual signals:
"Bullish Divergence (Overlay)"
Triggers when: Bullish divergence confirms at second pivot
Timing: Fires AFTER Pivot Right bars complete (delayed but stable)
Message: "TDI: Bullish divergence"
Reliability: Never repaints (confirmation locked at rsi )
"Bearish Divergence (Overlay)"
Triggers when: Bearish divergence confirms at second pivot
Timing: Fires AFTER Pivot Right bars complete (delayed but stable)
Message: "TDI: Bearish divergence"
Reliability: Never repaints (confirmation locked at rsi )
Alert configuration:
Set once on any chart/timeframe
Fires only when divergence condition evaluates true
Synchronized with visual rendering (alert = line + label appear)
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TRADING IMPLEMENTATION
═══════════════════════════════════════════
VISUAL ANALYSIS WORKFLOW
The overlay provides direct price-level context for divergence signals:
Bullish divergence interpretation:
Identify two connected swing lows with upward-sloping line
Lower price low indicates selling pressure weakening
Higher RSI low indicates momentum refusing to confirm price weakness
BUY label marks the second swing low (divergence confirmation point)
Bearish divergence interpretation:
Identify two connected swing highs with downward-sloping line
Higher price high indicates buying pressure weakening
Lower RSI high indicates momentum refusing to confirm price strength
SELL label marks the second swing high (divergence confirmation point)
CONFLUENCE WITH PRICE STRUCTURE
Overlay enables direct correlation with chart elements:
Support/Resistance alignment:
Bullish divergence at major support level = higher probability reversal
Bearish divergence at major resistance level = higher probability reversal
Divergence in middle of range = lower conviction signal
Volume confirmation:
Divergence with decreasing volume = confirms momentum exhaustion
Divergence with increasing volume = mixed signal, proceed with caution
Multi-timeframe context:
Higher timeframe trend alignment increases signal reliability
Counter-trend divergences (against HTF trend) require additional confirmation
ENTRY/EXIT FRAMEWORK
The overlay marks divergence confirmation points, not entry triggers:
Entry consideration process:
Divergence line appears → structure-confirmed momentum divergence detected
Wait for price confirmation (engulfing candle, break of structure, rejection wick)
Validate with additional confluence (volume, support/resistance, HTF trend)
Enter with predefined stop below/above divergence pivot
Size position according to distance to invalidation level
Exit planning:
Initial target: Previous swing high (bullish) / swing low (bearish)
Trail stop: Move to breakeven after initial profit target
Invalidation: Close below divergence low (bullish) / above divergence high (bearish)
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PANEL VS OVERLAY USAGE
═══════════════════════════════════════════
IDENTICAL DETECTION LOGIC
Both versions implement the same pivot-locked RSI evaluation:
Same RSI calculation (14-length with 2-period RMA smoothing)
Same volatility band framework (34-SMA + 1.618σ)
Same pivot confirmation (10 Left + 10 Right)
Same divergence comparison (rsi at locked bar indices)
Result: Divergences trigger at identical bars across both implementations.
RENDERING DIFFERENCES
Panel version (overlay=false):
Renders in separate pane below price chart
Displays RSI line, volatility bands, 50-line midline
Divergence lines drawn in oscillator space (RSI value coordinates)
Optional Shark Fin exhaustion visualization
Labels positioned relative to RSI levels
Overlay version (overlay=true):
Renders directly on price chart
No RSI line or bands visible (calculate internally for logic only)
Divergence lines drawn in price space (actual price coordinates)
No Shark Fin visualization (price chart remains clean)
Labels positioned at actual swing high/low prices
COMPLEMENTARY WORKFLOW
Recommended usage pattern:
Panel version: Monitor RSI regime (above/below 50), band interactions, Shark Fin exhaustion
Overlay version: Identify exact divergence price levels, correlate with support/resistance
Combined analysis: Use panel for momentum context, overlay for entry/exit precision
Alternative workflow (overlay only):
If RSI analysis not required, overlay version provides clean divergence detection
Pair with external RSI indicator if separate momentum visualization needed
Focuses chart space on price action and divergence markers only
═══════════════════════════════════════════
TECHNICAL SPECIFICATIONS
═══════════════════════════════════════════
RESOURCE ALLOCATION:
max_lines_count: 500 (divergence connector lines)
max_labels_count: 500 (BUY/SELL markers)
Suitable for most chart configurations and timeframes
RENDERING STABILITY:
xloc.bar_index positioning ensures visual stability across zoom/pan operations
Historical divergences never move once printed
Lines and labels scale proportionally with chart transformations
TIMEFRAME COMPATIBILITY:
Functions on any timeframe (1m to 1M)
Pivot detection adapts to bar spacing automatically
Lower timeframes generate more frequent signals (smaller swings)
Higher timeframes generate fewer signals (larger swings)
SYMBOL COMPATIBILITY:
Works on all asset classes (stocks, forex, crypto, futures, indices)
No symbol-specific logic or calculations
Universal RSI-based divergence detection
PERFORMANCE CHARACTERISTICS:
Lightweight calculation overhead (RSI + pivot detection + state management)
Visual rendering occurs only on divergence confirmation (not every bar)
No continuous repainting or historical recalculation
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USE CASE SCENARIOS
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SCENARIO 1: Support/Resistance Divergence
Setup: Price tests major support level twice, second test makes lower low
Signal: Bullish divergence line appears, RSI makes higher low at support
Interpretation: Momentum refusing to confirm price weakness at critical level
Action: Consider long entry on next bullish candle above divergence low
SCENARIO 2: Trend Exhaustion
Setup: Strong uptrend, price makes new high but momentum slowing
Signal: Bearish divergence line appears, RSI makes lower high
Interpretation: Buying pressure weakening despite higher price high
Action: Consider profit-taking on longs, watch for reversal confirmation
SCENARIO 3: Range-Bound Reversal
Setup: Price oscillating in horizontal range, tests lower boundary
Signal: Bullish divergence at range support
Interpretation: Oversold bounce opportunity within defined range
Action: Long entry targeting range midpoint or upper boundary
SCENARIO 4: Failed Breakout
Setup: Price breaks resistance but momentum doesn't confirm
Signal: Bearish divergence forms immediately after breakout
Interpretation: Breakout lacks momentum conviction, likely false breakout
Action: Consider fade setup (short) with stop above divergence high
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LIMITATIONS & CONSIDERATIONS
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SIGNAL TIMING:
Divergences print AFTER Pivot Right bars complete. This delay is intentional:
Ensures structure confirmation (full swing formation)
Prevents real-time repaint issues
Trades confirmation reliability for signal speed
Users requiring instant signals should use real-time divergence detectors (with repaint risk).
Users requiring reliable, stable signals should accept the confirmation delay.
LINE CLUTTER:
On lower timeframes with sensitive pivot settings:
High signal frequency may create visual clutter
Solution: Increase Pivot Left/Right values to filter smaller swings
Alternative: Use panel version for primary analysis, overlay for key divergences only
FALSE SIGNALS:
Divergences indicate momentum divergence, not guaranteed reversals:
Strong trends can maintain divergent conditions for extended periods
Divergence in isolation is a warning sign, not a trade trigger
Requires confluence with price action, volume, structure for high-probability setups
VOLATILITY BAND CONTEXT:
Bands calculate internally but don't visualize on overlay:
Users lose visual context of RSI overbought/oversold zones
Solution: Use panel version alongside overlay for complete RSI regime awareness
Alternative: Add separate RSI indicator to chart for band visualization
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Smart Divergence Engine Overlay provides candle-anchored, repainting-proof RSI divergence visualization directly on price charts. Lines and labels render at exact pivot price levels using xloc.bar_index positioning, maintaining stability across all chart transformations. Divergence detection uses pivot-locked RSI evaluation (rsi ) to ensure historical signals never move or disappear.
The overlay shares identical detection logic with the panel version but renders in price space rather than oscillator space, enabling direct correlation with support/resistance levels and price structure. All visual elements trigger only after full pivot confirmation (Pivot Left + Pivot Right bars), trading signal speed for absolute reliability.
Bästa Bob Multi-RSI 😎👊✅ RSI 7 → Fast impulse indicator
• Shows micro-movements
• Reacts instantly to liquidity sweeps
• Perfect for entry timing
✅ RSI 14 → Macro momentum indicator
• Captures the real trend
• Filters out noise
• Confirms larger market movements
When both are in sync → you get true market direction plus perfect timing.
👉 How to Use RSI 7 + RSI 14
1️⃣ Entry Signals (the best method)
BUY when:
• RSI 7 turns up from oversold
• RSI 14 is also sloping upward or gets crossed by RSI 7 from below
→ Extremely accurate right after a liquidity sweep.
SELL when:
• RSI 7 turns down from overbought
• RSI 14 is sloping downward or gets crossed by RSI 7 from above
→ Works insanely well for fakeouts and FVG entries.
2️⃣ Trend Filter
• When RSI 14 stays above 50 → market is bullish
• When RSI 14 stays below 50 → bearish
RSI 7 is then used only for timing entries.
3️⃣ A++ Setups (your favorite ones 😉🔥)
The best signals appear when:
✔ RSI 7 crosses RSI 14 at the same time as:
• a liquidity sweep happens
• price taps into an FVG or Order Block
• volume reacts
• your trend filter (EMA, HTF) supports the move
This combo is criminally effective when scalping BTC, NAS100, and XAUUSD.
Dark Pool Pulse – LiteDark Pool Pulse Lite
This indicator provides an observational proxy for dealer gamma exposure using only price and volume data. It helps users visualize whether market makers may be leaning long gamma (potential stabilizing flows) or short gamma (potential destabilizing flows). For educational and informational purposes only.
Key Features
0–100 oscillator representing an estimated dealer-gamma proxy.
Bullish zone (above 60): dealers may be long gamma → potentially absorbing volatility.
Bearish zone (below 40): dealers may be short gamma → potentially amplifying volatility.
Background tint for quick visual context.
Optional summary table showing current value and interpretation.
Alert conditions for crosses of the 60 and 40 thresholds.
How It Works
The indicator measures volume-weighted directional pressure and normalizes it over a rolling lookback window. The value is smoothed and mapped into a 0–100 oscillator:
Above 60 → potential positive gamma conditions.
Below 40 → potential negative gamma conditions.
40–60 → neutral or balanced zone.
All calculations are performed internally using only price and volume.
Settings
Lookback Length (default 20): Number of bars used for normalization.
Smoothing Length (default 10): EMA smoothing applied to the proxy.
Show Summary Table: Toggles the optional value/interpretation panel.
How to Use
Add the indicator to any chart or timeframe.
Observe the oscillator levels:
A move above 60 may reflect a more stabilizing dealer environment.
A move below 40 may reflect a more destabilizing environment.
Use the background tint for quick contextual bias.
Enable alerts for threshold crossings if desired.
Adjust settings to match your preferred responsiveness.
Notes
For educational and informational purposes only.
Not financial, trading, or investment advice.
No signals or recommendations are provided.
Source code protected to maintain proprietary calculation methods.
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
Trend & Pullback Cycle How to use.
Trend Identification:
Green Columns: The cycle is above 50. Look for Longs.
Red Columns: The cycle is below 50. Look for Shorts.
Pullback Detection:
I added a Colour Change feature. If the Green bars turn Dark Green, it means momentum is fading (a pullback is happening). This is your signal to get ready to enter or add to a position once it turns Bright Green again.
The Yellow Line:
This is your trigger. In the screenshot, you see the bars cross the yellow line.
Entry Signal: When the Histogram crosses above the Yellow line (while generally green) or crosses below it (while generally red).
Trade volume indicator @mybullandbearThe indicator consolidates Trend (MA), Momentum (RSI), Breakout (ORB), and Volume (CVD) into a single dashboard, giving you an objective "Green" or "Red" bias.
Mybullandbear View (CVD): This specific component tracks whether buying or selling volume is dominant for the day. It helps you avoid false breakouts—if price goes up but CVD is Red (Bearish), it's likely a trap.
How to Benefit: Wait for Confluence. Do not take a trade unless the Dashboard shows a clear consensus (e.g., Green Trend + Bullish CVD + Price above ORB High). This filters out low-quality trades and keeps you on the right side of the market.
Mean Reversion Framework [LTS]LHAMA Trading Suite's Mean Reversion Framework is a VWAP-centric mean reversion and exhaustion tool that combines volatility regimes, volume-weighted extension zones, and multi-oscillator divergence detection into a single framework. It is designed to help traders quickly answer three questions on any chart:
How far is price stretched away from VWAP in standard deviations?
Is the current environment favorable or hostile to mean reversion?
Are there momentum divergences supporting a reversal or trend continuation idea?
Core components
1. Adaptive VWAP with standard deviation bands
The framework builds around a dynamically anchored VWAP with statistical bands:
VWAP line plotted from a rolling anchor point.
Standard deviation bands : ±1σ, ±2σ, ±2.5σ, and ±3σ around VWAP.
Extension zones : the area between ±2.5σ and ±3σ is highlighted as an “extension zone,” where price is statistically stretched from its mean.
Anchoring is automatic and timeframe-aware. When you change your charts timeframe, this will automatically adjust what VWAP you are looking at to make sure you're always using the anchoring research has shown to be most appropriate and relevant for that timeframe.
2. Reversion candle coloring
To highlight potentially climactic moves:
The script tracks a configurable volume average and multiplier.
When price touches the ±2.5σ extension zone and a candle meets one of these conditions, candles can be recolored:
Has above average volume, but below average candle body size.
Has lower volume than the previous candle.
An optional alert can be triggered when these extension touches occur.
The ideal reversion setup is a quick extension into the marked zone, which includes a high volume, small body candle at its peak, surrounded by lower volume candles in opposite directions. This shows an energetic push in one direction, followed by exhaustion and a fade back toward the mean.
3. Volatility regime detection
The script classifies the current volatility regime using ATR:
Calculates ATR over a user-defined lookback.
Computes the percentile rank of current ATR relative to its recent history.
Labels the environment as:
HIGH volatility (ATR percentile at or above the high threshold).
LOW volatility (at or below the low threshold).
MODERATE otherwise.
The current regime and ATR percentile are displayed on the dashboard and can be used as context for whether mean-reversion setups may be more or less favorable. Alerts can fire when volatility crosses into high or low regimes so users can adjust expectations or strategies if desired.
4. RSI & Stochastic divergence framework
The indicator includes a combined divergence engine using RSI and Stochastic:
User-configurable RSI length.
User-configurable Stochastic K/D parameters.
Pivot-based detection with left/right lookbacks and a max lookback window.
Two main categories:
Regular divergences – potential reversal context.
Hidden divergences – potential trend continuation context.
For both RSI and Stochastic, the script looks for:
Bullish regular : price lower low vs. oscillator higher low.
Bearish regular : price higher high vs. oscillator lower high.
Hidden bullish : price higher low vs. oscillator lower low.
Hidden bearish : price lower high vs. oscillator higher high.
When conditions are met, the script will:
Plot labels on the price chart:
🔃 icons for regular (reversal) divergences.
⏩ icons for hidden (continuation) divergences.
Combine RSI and Stochastic confirmation into a single label when both agree, with tooltips explaining:
Price structure (HH/HL/LL/LH).
Which oscillator(s) confirmed the divergence.
Whether the pattern suggests potential reversal or continuation.
Optionally trigger alerts for each divergence type when alerts are enabled.
Divergence labels are based on confirmed pivots, so they appear with a delay relative to the pivot bar. They are not predictive and should be treated as contextual information rather than standalone trade signals.
5. Dashboard overlay
An on-chart dashboard summarizes the most important state variables in a compact table:
VWAP Anchor – shows the effective anchor logic currently in use (“Session/Week/Month”, “5-Day Rolling” or “Yearly (Jan 1)”).
Alert Status – ACTIVE, COOLDOWN, or DISABLED.
Volatility Regime – HIGH / MODERATE / LOW with the current ATR percentile.
VWAP Value – current VWAP price.
Price vs VWAP – distance of price from VWAP in standard deviations (σ).
ATR – current ATR value for the selected length.
The dashboard can be toggled on or off and moved to any corner of the chart (top/bottom, left/right).
6. Alert system & cooldown
The script defines multiple alert conditions so users can build their own rules around mean reversion and volatility changes:
Extension zone alerts :
Price enters upper extension (≥ +2.5σ).
Price enters lower extension (≤ −2.5σ).
Price enters any extension zone.
High-volume candle touching an extension zone.
Divergence alerts :
Regular bullish / bearish divergence.
Hidden bullish / bearish divergence.
Volatility regime alerts :
ATR percentile crosses into HIGH volatility.
ATR percentile crosses into LOW volatility.
To reduce alert noise around VWAP resets, there is an optional alert cooldown :
At the start of a new VWAP period (session/5-day/yearly, depending on timeframe), the script can enter a cooldown phase.
During cooldown, extension-related alerts are temporarily suppressed for a user-defined number of minutes.
Volatility regime alerts remain active, as they reflect broader structural changes rather than short-term VWAP resets.
Users can disable the cooldown by setting its duration to 0.
Sen Channel LiteSen Channel Lite
Sen Channel Lite calculates a robust, median-based regression channel using the Theil–Sen slope method. This visual tool helps traders identify trend direction and potential breakout zones in real time.
Key Features
Dynamic Trend Line: The median-based regression line adapts to price movement, providing a central reference for trend direction.
Upper and Lower Bands: Automatically updated bands highlight potential breakout or reversal areas.
Breakout Markers: Optional triangles indicate when price crosses above the upper band or below the lower band.
Midline (EMA/SMA): Toggleable trend line for additional context on price direction.
VWAP Anchor: Optional VWAP plot to visualize volume-weighted average price levels.
Customizable Inputs:
Lookback Period for slope calculation
Band Multiplier to adjust sensitivity
Option to use Standard Deviation or ATR for band width
Midline type, length, and color
VWAP visibility and color
Channel cloud transparency
How to Read Signals (Educational Use Only):
Trend Context: The midline provides a reference for general trend direction. Price above the midline suggests bullish bias; below indicates bearish bias.
Breakouts:
Triangle up → price crossed above the upper band; potential strong move upward.
Triangle down → price crossed below the lower band; potential strong move downward.
Channel Interpretation:
Price near the upper band → market may be overextended.
Price near the lower band → market may be oversold.
Price moving within the channel → trend is balanced; use additional analysis for direction.
VWAP Context: Compare price to VWAP for intraday support/resistance insights.
Usage Notes:
Fully visual tool; no trading or financial advice.
All calculations are protected to preserve intellectual property.
Results reflect real-time calculations; no repainting.
Suitable for intraday to daily timeframes.
Important: This script is published as protected/closed-source to safeguard GammaBulldog intellectual property.
Hemanth's Pure Z-Score IndicatorThe Pure Z-Score Indicator is a statistical tool that measures how far the current price is from its recent average in terms of standard deviations. It helps traders identify overbought, oversold, and mean-reverting conditions in the market. This indicator is fully customizable, lightweight, and easy to use.
Key Features:
Displays the Z-Score of the price with optional smoothing.
Highlights overbought and oversold zones based on standard deviation thresholds.
Highlights mean (0) level for tracking price reversion.
Optional SMA or EMA smoothing to reduce noise.
Background highlights visually indicate extreme zones for easier analysis.
Inputs:
Length – Number of bars used to calculate the Z-Score.
Higher values smooth the indicator but react slower.
Lower values make it more sensitive but may produce more noise.
Overbought Level – Upper threshold for the Z-Score.
Default: 2.0 (2 standard deviations above the mean).
Crossing above this level signals a statistically overbought condition.
Oversold Level – Lower threshold for the Z-Score.
Default: -2.0 (2 standard deviations below the mean).
Crossing below this level signals a statistically oversold condition.
Use EMA instead of SMA – Determines whether the basis for Z-Score calculation is an Exponential Moving Average (EMA) or a Simple Moving Average (SMA).
EMA reacts faster to recent price changes.
SMA gives a smoother, slower-reacting average.
Smooth Z-Score (0 = no smoothing) – Apply additional smoothing to the Z-Score using a moving average.
Reduces noise and false spikes for cleaner visualization.
How to Use:
Overbought/Oversold: Watch for the Z-Score crossing the upper or lower levels to identify potential reversal zones.
Mean Reversion: Z-Score crossing the mean (0) can indicate short-term trend shifts.
Smoothing Options: Adjust the smoothing length and type to suit your trading style and timeframe.
Recommended Timeframes:
Works on any timeframe; suitable for day trading, swing trading, or longer-term analysis.
Best used in combination with price action or other indicators for confirmation.
Note:
This is a pure statistical indicator based on standard deviations. It does not provide buy/sell signals by itself, but helps traders identify areas of extreme price movement and potential reversals.
XAU Micro ScalperThis indicator is designed for short-term price rotation detection on XAUUSD, especially on the 1-minute timeframe.
It combines three momentum components—Stochastic, RSI, and OBV slope—to highlight potential reversal points and short-term scalping opportunities.
Core Logic
The script generates a signal only when multiple conditions align:
1. Stochastic Reversal (Timing Component)
A basic long/short trigger occurs when the Stochastic oscillator exits oversold (long) or overbought (short).
This represents a potential shift in short-term momentum.
2. RSI “Smart Rotation” Filter (Context Component)
Instead of using fixed oversold/overbought thresholds, the indicator checks whether RSI is turning:
Long: RSI is below a contextual ceiling (default 50) and rising
Short: RSI is above a contextual floor (default 55) and falling
This avoids premature entries during strong trending phases and confirms that momentum is actually rotating.
3. OBV Slope Filter (Volume Confirmation)
The On-Balance Volume trend is compared to its previous value:
Long: OBV slope improving
Short: OBV slope deteriorating
This helps confirm whether volume pressure is shifting in favor of the trade direction.
Both RSI and OBV filters can be enabled or disabled independently via the indicator settings.
Signals
Small circles mark raw Stochastic reversal points (unfiltered).
Green / red triangles represent validated long/short signals where all active filters agree.
Optional candle coloring highlights confirmed entry signals on the chart.
Use Cases
Intraday and scalping strategies on XAUUSD
Identifying short-term momentum reversals
Filtering noisy signals during high-volatility sessions
Studying how volume and momentum align around turning points
Customization
Users can adjust:
RSI contextual thresholds
Lookback periods
OBV slope sensitivity
Stochastic parameters
Activation of RSI and OBV filters
This flexibility allows the indicator to adapt to different market conditions and timeframes.
Disclaimer
This indicator does not provide financial advice or guarantee performance.
Always test any strategy on historical data and use proper risk management.
KSL-Fullsystem V2.0Trend Following & Reversal Trading System. It combines **Price Action (Market Structure)** with multiple technical indicators to generate high-quality Buy and Sell signals.
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1. How Signals are Generated (The Core Logic)
The script uses **"Internal Shifts"** (Market Structure Breaks) to find entry points.
* BUY Signal: The price breaks above a previous bearish structure (Higher High) + All enabled filters are Green.
* SELL Signal: The price breaks below a previous bullish structure (Lower Low) + All enabled filters are Red.
When a signal occurs, the script automatically calculates:
* Stop Loss (SL): Based on the recent Swing High/Low.
* Take Profit (TP): Three levels (TP1, TP2, TP3) based on risk-reward ratios (1.5x, 2.0x, 3.0x).
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2. The Filters (Your Confirmation Checklist)
You can turn these On/Off in the settings. **Note:** If you turn *all* of them on, you might get very few signals because the conditions become too strict.
**A. Bollinger Bands (BB) Filters (Primary Feature)**
This is the main filter for this version.
* Squeeze Filter: Prevents trading when the bands are too narrow (low volatility). If the background turns **Yellow**, it means the market is "Squeezing" – **Do Not Trade.**
* Touch Entry: Looks for price bouncing off the Lower Band (Buy) or Upper Band (Sell).
* Breakout Entry: Looks for price blasting through the bands.
* Mean Reversion: Checks if price is reverting to the middle line (Basis).
**B. Moving Average Filters (Trend)**
The script includes three types of Moving Averages. You can choose which style suits you:
* EMA (Exponential): Fast-reacting. Good for scalping.
* SMA (Simple): Standard trend lines. Good for position trading.
* LWMA (Linear Weighted): Focuses heavily on recent data.
* Configuration: You can select specific setups like "Scalping" (9/21/50 EMA) or "Trend" (50/200 EMA).
**C. Momentum Filters**
* MACD: Checks momentum. You can choose settings for Scalping, Day Trading, or Swing Trading.
* AO (Awesome Oscillator) & AC: Helps confirm if the momentum is strong enough to support the trend.
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**3. Visual Guide: What You See on the Chart**
* Green Box: A Buy Zone (Demand).
* Red Box: A Sell Zone (Supply).
* Labels (Text): Shows "BUY" or "SELL" with exact prices for TP1, TP2, TP3, and SL.
* Blue Lines: The Bollinger Bands (Upper and Lower).
* Orange Line: The Bollinger Band Basis (Middle).
* Small Triangles:
* Green Triangle (Below Bar): Price touched the Lower Bollinger Band.
* Red Triangle (Above Bar): Price touched the Upper Bollinger Band.
* Yellow Background: **WARNING.** The market has low volume/volatility (BB Squeeze). Wait for a breakout.
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4. How to Use This Script
1. Select Your Style: Go to the Settings (Inputs).
* If you are a **Scalper**, turn on "Scalping EMA" or "Scalping MACD".
* If you are a **Swing Trader**, turn on "Swing SMA" or "Trend EMA".
2. Configure Bollinger Bands: Keep `Use Bollinger Bands Filter` checked. Decide if you want to trade "Squeezes" (usually safer to avoid them).
3. Wait for the Label: Do not enter blindly. Wait for the script to print a **BUY** or **SELL** label with the TP/SL targets.
4. Check the Background: If the background is **Yellow**, ignore the signal or wait until the color clears.
5. Manage Risk: Place your Stop Loss at the price shown on the label ("SL").
VAPO OsilatorThe Real Map of Buying and Selling Pressure.
VAPO Advanced is fundamentally different from conventional oscillators that only measure momentum based on price. By integrating Volume and price movement (Pressure), it quantitatively maps the true buying and selling pressure in the market.
How It Works and What Are Its Advantages?
1. Core Pressure Measurement
Logic: The oscillator interprets high-volume price increases as strong buying pressure (+P) and high-volume price decreases as strong selling pressure (-P). Low-volume moves weaken the signal strength.
Benefit: This effectively filters out misleading signals caused by "fake" price movements (manipulation or low-volume spikes). It only displays momentum shifts that are supported by volume.
2. Dynamic Signal Line and Histogram
Signal Line: Provides a dynamic signal line smoothed by your choice of Moving Average type (EMA, SMA, WMA).
Histogram: Shows the difference between the VAPO line and the Signal line. A zero-line crossover of the histogram is the clearest signal that pressure is shifting direction. As the Green histogram grows, Buying Pressure accelerates; as the Red histogram grows, Selling Pressure accelerates.
3. Reliable Confirmation Tool
VAPO serves as an excellent confirmation tool when used alongside your primary trend indicators. For instance, when a trend indicator gives a BUY signal, VAPO crossing above the zero line (positive pressure) significantly increases the reliability of that signal.
⚠️ DISCLAIMER: THIS IS NOT FINANCIAL ADVICE. ALL INFORMATION PROVIDED IS FOR EDUCATIONAL AND ANALYTICAL PURPOSES ONLY.
YASAL UYARI: BU BİR YATIRIM TAVSİYESİ DEĞİLDİR. SUNULAN TÜM BİLGİLER YALNIZCA EĞİTİM VE ANALİZ AMAÇLIDIR.
DSS Bressert (Double Smoothed Stochastic) Mid point (H+L)/2Changed source to midpoint (High+Low)/2 instead of Close for a cleaner average.
Fundamental Analysis DashboardFundamental Analysis Dashboard
Valuation | P/E, P/B, P/S, EV/EBITDA, PEG, FCF Yield
Profitability | ROE, ROA, ROIC, Net Margin, Gross Margin, Operating Margin
Growth | EPS Growth YoY, Revenue Growth YoY, EPS TTM
Financial Health | Debt/Equity, Current Ratio, Quick Ratio, Net Cash, FCF
Dividends | Dividend Yield, Payout Ratio, DPS
Technical Context | Price vs EMA50/200, RSI, 52-Week Position
The dashboard calculates a Fundamental Score (0-100) based on weighted criteria across all sections:
80-100: Excellent
65-79: Good
50-64: Fair
35-49: Weak
0-34: Poor
SBMS RSIThis is everyones favourite RSI with small modification as it has 60 as breaout level and 40 as breakdown level, 80 as Overbrought zone and 20 as oversold zone. An EMA helps to stay in the trend.
RSI + Psy + ADX P2RSI + Psy + ADX
This indicator combines multi-length RSI analysis with the Psychological Line (PSY) and ADX trend strength to highlight reversal zones, emotional extremes, and trend conditions in a single unified panel.
🔹 Features
1️⃣ Triple RSI with Dynamic Colors
Displays Short / Mid / Long RSI values (9 / 26 / 52 by default)
Line color changes based on RSI levels:
🔴 Overbought (above 68)
🟢 Oversold (below 32)
⚪ Neutral market conditions
Fixed zone levels at 70 / 50 / 30 for simple visual analysis
2️⃣ Psychological Line (PSY) Extreme Signal
Measures the percentage of bearish candles in the selected period
Only highlights emotional extremes (overbought & oversold conditions)
Red/Green histogram makes market sentiment easy to read
3️⃣ ADX Trend Strength Detector
Confirms trend momentum using ADX
Color-coded levels:
🔵 Weak trend
🟡 Moderate trend
🔴 Strong trend (possible trend continuation)
Helps avoid counter-trend trades during strong momentum
4️⃣ RSI Background Highlight (Mid-term RSI Only)
Background turns RED in overbought area
Background turns GREEN in oversold area
Provides fast and clean recognition of reversal zones
🎯 Best Uses
Identifying low-risk reversal entry zones
Avoiding entries against strong trends
Confirming momentum and sentiment alignment
Useful for scalping, day-trading, and swing-trading strategies
💡 Tip
For higher precision, combine this indicator with:
🔹 Support/Resistance Levels
🔹 Candlestick Reversal Patterns
🔹 Volume Spikes or Breakout Tools
3 Lines RCI + Psy Signal + RSI Background📌 3 Lines RCI + Psy Signal + RSI Background
This indicator combines three RCI lines, Psychological Line signals, RSI-based background highlights, and ADX strength detection to visualize market momentum, trend strength, and potential reversal zones.
🔍 Main Features
📌 1. Triple RCI (Rank Correlation Index)
Displays Short / Mid / Long RCI
Detects momentum shifts and trend reversals
Highlight zones:
Overbought: +80 ~ +100 (Red Zone)
Oversold: -80 ~ -100 (Green Zone)
📌 2. Psychological Line Signal
Column bars appear only in extreme conditions:
Overbought → Red Bars
Oversold → Green Bars
Helps detect short-term sentiment extremes
📌 3. RSI Background Highlight
Red Background: RSI > Overbought threshold
Green Background: RSI < Oversold threshold
Provides a visual cue of underlying market pressure.
📌 4. ADX Trend Strength
ADX line color shows strength level:
Blue: Weak trend
Yellow: Moderate trend
Red: Strong trend
Useful to identify whether signals occur in a trend or range state.
🎯 Trading Usage Tips
RCI + RSI + Psy confluence can identify strong reversal timing.
Use signals only when ADX is weak or moderate to avoid counter-trading a strong trend.
Combine short/mid RCI crossovers with extreme zones for potential entry timing.
⚙️ Suitable For
Scalping, day trading, swing trading
Stocks, Forex, Crypto, Indices, Commodities
Momentum Marks - Buy and Sell IndicatorsIndicator Overview
This tool is a multi‑factor entry signal system designed to highlight potential BUY and SHORT opportunities directly on the chart with hard‑anchored labels. It combines trend, momentum, volatility, and volume conditions to reduce noise and provide more reliable trade signals.
Core Components
- EMA Trend Filter
- Uses a fast EMA (9) and a slow EMA (21) to determine short‑term vs. medium‑term trend direction.
- Signals only trigger when price aligns with the EMA relationship (e.g., fast above slow for shorts, fast below slow for buys).
- RSI Extremes
- RSI thresholds (default 65/35) ensure signals occur only when momentum is stretched into overbought or oversold zones.
- Helps avoid false triggers during neutral conditions.
- Linear Regression Channel
- A regression line with ±2 standard deviation bands defines dynamic support and resistance.
- Signals require price to be near the top (for shorts) or bottom (for buys) of the channel, adding a structural filter.
- TTM Squeeze Histogram
- Measures momentum shifts by comparing price to its EMA.
- Signals require histogram confirmation: weakening momentum for shorts, strengthening momentum for buys.
- Volume Confirmation
- Volume must fade for shorts or surge for buys relative to a 20‑period average.
- Ensures signals align with participation strength.
Visual Output
- Red “SHORT” label above bars when all short conditions align.
- Green “BUY” label below bars when all buy conditions align.
- Optional plotshape arrows (triangles) as backup markers.
- Linear regression channel shaded between upper and lower bands.
- EMA lines plotted for trend context.
Key Features
- Hard‑anchored labels: Signals are locked to confirmed bars, preventing repainting or shifting.
- Multi‑layer confirmation: Requires trend, momentum, volume, and structure to align before firing.
- Customizable inputs: Users can adjust EMA lengths, RSI thresholds, regression length, and squeeze parameters.
