Cerber Strategy ETH/BTC Cerber Strategy: High-Precision Crypto Trend Follower
The Cerber Strategy is a low-frequency, high-conviction trend following system designed to capture massive quarterly crypto moves while
filtering out 90% of consolidation noise. It combines a momentum-based "Sniper Entry" (entering only on verified breakouts) with a
"Trend Confirmation" filter (Weekly DEMA) to ensure capital is only deployed during macro bull runs.
Usage:
* Timeframe: Daily (1D) mandatory.
* Assets: Optimized for BTC and ETH, works on high-volatility alts.
* Style: Position Trading (holding for weeks/months).
* Risk: Extremely high efficiency (high Profit Factor), very low drawdown compared to Buy & Hold. Perfect for a "Set and Forget"
portfolio allocation.
波動率
CODEX OB + BBMA V1CODEX OB + BBMA is a multi-purpose Smart Money Concepts (SMC) indicator that automatically detects and visualizes key institutional trading elements such as Order Blocks, Fair Value Gaps, Rejection Blocks, Break of Structure, Pivots, High Volume Bars, and several qualitative SMC signals.
In addition to SMC tools, this indicator also incorporates multi-timeframe BBMA logic, allowing traders to view higher-timeframe momentum, trend direction, and volatility envelopes directly from the current chart. This makes it easier to align SMC setups—like OB, FVG, and BOS—with BBMA structure such as MA touches, re-entry zones, extreme candles, and volatility expansions.
This combination helps traders identify institutional footprints, multi-timeframe confluence, and displacement-based setups with high clarity.
Bollinger Bands Forecast [QuantAlgo]🟢 Overview
Bollinger Bands are widely recognized for mapping volatility boundaries around price action, but they inherently lag behind market movement since they calculate based on completed bars. The Bollinger Bands Forecast addresses this limitation by adding a predictive layer that attempts to project where the upper band, lower band, and basis line might position in the future. The indicator provides three unique analytical models for generating these projections: one examines swing structure and breakout patterns, another integrates volume flow and accumulation metrics, while the third applies statistical trend fitting. Traders can select whichever methodology aligns with their market view or trading style to gain visibility into potential future volatility zones that could inform position planning, risk management, and timing decisions across various asset classes and timeframes.
🟢 How It Works
The core calculation begins with traditional Bollinger Bands: a moving average basis line (configurable as SMA, EMA, SMMA/RMA, WMA, or VWMA) with upper and lower bands positioned at a specified number of standard deviations away. The forecasting extension works by first generating predicted price values for upcoming bars using the selected method. These projected prices then feed into a rolling calculation that simulates how the basis line would update bar by bar, respecting the mathematical properties of the chosen moving average type. As each new forecasted price enters the calculation window, the oldest historical price drops out, mimicking the natural progression of the moving average. The system recalculates standard deviation across this evolving price window and applies the multiplier to determine where upper and lower bands would theoretically sit. This process repeats for each of the forecasted bars, creating a connected chain of potential future band positions that render as dashed lines on the chart.
🟢 Key Features
1. Market Structure Model
This forecasting approach interprets price through the lens of swing analysis and structural patterns. The algorithm identifies pivot highs and lows across a definable lookback window, then tracks whether price is forming higher highs and higher lows (bullish structure) or lower highs and lower lows (bearish structure). The system looks for break of structure (BOS) when price pushes beyond a previous swing point in the trending direction, or change of character (CHoCH) when price starts creating opposing swing patterns.
When projecting future prices, the model considers current distance from recent swing levels and the strength of the established trend (measured by counting higher highs versus lower lows). If bullish structure dominates and price sits near a swing low, the forecast biases upward. Conversely, bearish structure near a swing high produces downward bias. ATR scaling ensures the projection magnitude relates to actual market volatility.
Practical Implications for Traders:
Useful when you trade based on swing points and structural breaks
The Structure Influence slider (0 to 1) lets you dial in how much weight structure analysis carries versus pure trend
Helps visualize where bands could form around key structural levels you're watching
Works better in trending conditions where structure patterns are clearer
Might be less effective in choppy, sideways markets without defined swings
2. Volume-Weighted Model
This method attempts to incorporate volume flow into the price forecast. It combines three volume-based metrics: On-Balance Volume (OBV) to track cumulative buying/selling pressure, the Accumulation/Distribution Line to measure money flow, and volume-weighted price changes to emphasize moves that occur on high volume. The algorithm calculates the slope of these indicators to determine if volume is confirming price direction or diverging from it.
Volume spikes above a configurable threshold are flagged as potentially significant, with the direction of the spike (whether it occurred on an up bar or down bar) influencing the forecast. When OBV, A/D Line, and volume momentum all align in the same direction, the model projects stronger moves. When they conflict or show weak volume support, the forecast becomes more conservative.
Practical Implications for Traders:
Relevant if you use volume analysis to confirm price moves
More meaningful in markets with reliable volume data
The Volume Influence parameter (0 to 1) controls how much volume factors into the projection
Volume Spike Threshold adjusts sensitivity to what constitutes unusual volume
Helps spot scenarios where volume doesn't support a move, suggesting possible consolidation
Might be less effective in low-liquidity instruments or markets where volume reporting is unreliable
3. Linear Regression Model
The simplest of the three methods, linear regression fits a straight line through recent price data using least-squares mathematics and extends that line forward. This creates a clean trend projection without conditional logic or interpretation of market characteristics. The forecast simply asks: if the recent trend continues at its current rate of change, where would price be in 10 or 20 bars?
Practical Implications for traders:
Provides a neutral, mathematical baseline for comparison
Works well when trends are steady and consistent
Can be useful for backtesting since results are deterministic
Requires minimal configuration beyond lookback period
Might not adapt to changing market conditions as dynamically as the other methods
Best suited for trending markets rather than ranging or volatile conditions
🟢 Universal Applications Across All Models
Regardless of which forecasting method you select, the indicator projects future Bollinger Band positions that may help with:
▶ Pre-planning entries and exits: See where potential support (lower band) or resistance (upper band) might develop before price gets there
▶ Volatility context: Observe whether forecasted bands are widening (suggesting potential volatility expansion) or narrowing (possible compression or squeeze setup)
▶ Target setting: Reference projected band levels when determining profit targets or stop placement
▶ Mean reversion scenarios: Visualize potential paths back toward the basis line when price extends to a band extreme
▶ Breakout anticipation: Consider where upper or lower bands might sit if price begins a strong directional move
▶ Strategy development: Build trading rules around forecasted band interactions, such as entering when price is projected to return to the basis or exit when forecasts show band expansion
▶ Method comparison: Switch between the three forecasting models to see if they agree or diverge, potentially using consensus as a confidence filter
It's critical to understand that these forecasts are projections based on recent market behavior. Markets are complex systems influenced by countless factors that cannot be captured in a technical calculation or predicted perfectly. The forecasted bands represent one possible scenario of how volatility might unfold, so actual price action may still diverge from these projections. Past performance and historical patterns provide no assurance of future results. Use these forecasts as one input within a broader trading framework that includes proper risk management, position sizing, and multiple forms of analysis. The value lies not in prediction accuracy but in helping you think probabilistically about potential market states and plan accordingly.
The Abramelin Protocol [MPL]"Any sufficiently advanced technology is indistinguishable from magic." — Arthur C. Clarke
🌑 SYSTEM OVERVIEW
The Abramelin Protocol is not a standard technical indicator; it is a "Technomantic" trading algorithm engineered to bridge the gap between 15th-century esoteric mathematics and modern high-frequency markets.
This script is the flagship implementation of the MPL (Magic Programming Language) project—an open-source experimental framework designed to compile metaphysical intent into executable Python and Pine Script algorithms.
Unlike traditional indicators that rely on arbitrary constants (like the 14-period RSI or 200 SMA), this protocol calculates its parameters using "Dynamic Entity Gematria." We utilize a custom Python backend to analyze the ASCII vibrational frequencies of specific metaphysical archetypes, reducing them via Tesla's 3-6-9 harmonic principles to derive market-responsive periods.
🧬 WHAT IS ?
MPL (Magic Programming Language) is a domain-specific language and research initiative created to explore Technomancy—the art of treating code as a spellbook and the market as a chaotic entity to be tamed.
By integrating the logic of ancient Grimoires (such as The Book of Abramelin) with modern Data Science, MPL aims to discover hidden correlations in price action that standard tools overlook.
🔗 CONNECT WITH THE PROJECT:
If you are a developer, a trader, or a seeker of hidden knowledge, examine the source code and join the order:
• 📂 Official Project Site: hakanovski.github.io
• 🐍 MPL Source Code (GitHub): github.com
• 👨💻 Developer Profile (LinkedIn): www.linkedin.com
🔢 THE ALGORITHM: 452 - 204 - 50
The inputs for this script are mathematically derived signatures of the intelligence governing the system:
1. THE PAIMON TREND (Gravity)
• Origin: Derived from the ASCII summation of the archetype PAIMON (King of Secret Knowledge).
• Function: This 452-period Baseline acts as the market's "Event Horizon." It represents the deep, structural direction of the asset.
• Price > Line: Bullish Domain.
• Price < Line: Bearish Void.
2. THE ASTAROTH SIGNAL (Trigger)
• Origin: Derived from the ASCII summation of ASTAROTH (Knower of Past & Future), reduced by Tesla’s 3rd Harmonic.
• Function: This is the active trigger line. It replaces standard moving averages with a precise, gematria-aligned trajectory.
3. THE VOLATILITY MATRIX (Scalp)
• Origin: Based on the 9th Harmonic reduction.
• Function: Creates a "Cloud" around the signal line to visualize market noise.
🛡️ THE MILON GATE (Matrix Filter)
Unique to this script is the "MILON Gate" toggle found in the settings.
• ☑️ Active (Default): The algorithm applies the logic of the MILON Magic Square. Signals are ONLY generated if Volume and Volatility align with the geometric structure of the move. This filters out ~80% of false signals (noise).
• ⬜ Inactive: The algorithm operates in "Raw Mode," showing every mathematical crossover without the volume filter.
⚠️ OPERATIONAL USAGE
• Timeframe: Optimized for 4H (The Builder) and Daily (The Architect) charts.
• Strategy: Use the Black/Grey Line (452) as your directional bias. Take entries only when the "EXECUTE" (Long) or "PURGE" (Short) sigils appear.
Use this tool wisely. Risk responsibly. Let the harmonics guide your entries.
— Hakan Yorganci
Technomancer & Full Stack Developer
Volume Crisis Created by Alphaomega18
🎯 What is the Crisis Detector Pro?
The Crisis Detector Pro is an advanced multi-component indicator that detects market crisis situations by simultaneously analyzing:
Volume: Anomalies and volume spikes
VIX: Volatility Index (S&P 500)
ATR: True volatility (all assets)
Open Interest: Estimated open interest (futures contracts)
The indicator calculates a Composite Crisis Score (0-100) that combines these elements to alert you to critical market moments.
📊 Indicator Components
1️⃣ Volume Analysis
Anomaly detection: Compares current volume to its moving average
Classification:
🟡 Moderate: 1.5x - 2x average
🟠 High: 2x - 3x average
🔴 Extreme: > 3x average
Bollinger Bands: Detects volume breakouts
Clusters: Identifies 3+ consecutive days of anomalies
2️⃣ VIX (Fear Index)
S&P 500 only
Default thresholds:
🟡 Moderate: VIX > 20
🟠 High: VIX > 30
🔴 Extreme: VIX > 40
3️⃣ ATR (Average True Range)
Measures true volatility
Compatible with all assets (stocks, futures, forex, crypto)
Compares current ATR to its average
4️⃣ Open Interest (OI)
Estimation based on Volume / 2
Detects changes > 25%
Inverted colors:
🔴 Red: OI increase (new positions)
🟢 Green: OI decrease (position closing)
⚙️ Main Parameters
Calculations:
Moving Average Period: 20 (default)
Standard Deviation Period: 20
ATR Period: 14
Volume Thresholds:
Moderate: 1.5x
High: 2.0x
Extreme: 3.0x
Composite Score (Weights):
Volume: 35%
VIX: 25%
ATR: 20%
Open Interest: 20%
📈 Visual Signals
Top of Chart:
🟡 Yellow triangle: Moderate alert (Score 50-70)
🟠 Orange triangle: High alert (Score 70-85)
🔴 Red triangle: EXTREME CRISIS (Score 85-100)
⚠️ Purple cross: Reinforced signal (Volume + Volatility simultaneous)
Bottom of Chart:
💎 Purple diamond: 50-day volume record
⬛ Fuchsia square: Cluster (3+ abnormal days)
Volume Bars:
Gray: Normal volume
🟡 Yellow: Moderate volume
🟠 Orange: High volume
🔴 Red: Extreme volume
Open Interest Curve:
🔵 Blue: Normal variation
🔴 Red: Increase > 25%
🟢 Green: Decrease > 25%
🎯 How to Use the Indicator
1. Initial Setup
For S&P 500 / US Indices:
Enable VIX ✅
Enable ATR ✅
Enable OI ✅
Composite Score ✅
For Other Assets (Forex, Crypto, Stocks):
Disable VIX ❌
Enable ATR ✅
Enable OI (optional)
Composite Score ✅
2. Crisis Score Interpretation
ScoreLevelMeaningAction0-50Normal ✅Calm marketNormal trading50-70Vigilance 🟡Volatility risingIncreased monitoring70-85Danger 🟠Critical situationReduce exposure85-100Crisis 🔴MAXIMUM ALERTCapital protection
3. Trading Strategies
Directional Trading:
Reinforced signal ⚠️ = Powerful move in progress
Enter in direction of movement with confirmation
Tight stops, quick targets
Risk Management:
Score > 70 → Reduce position size by 50%
Score > 85 → Stop trading or ultra-short positions
Cluster detected → Avoid new trades
Scalping/Day Trading:
Extreme volume 🔴 = Scalping opportunities
Wait for confirmation before entering
Exit quickly on spikes
Swing Trading:
Avoid opening swings during crises
Protect existing positions (trailing stops)
Wait for return to normal (Score < 50)
4. Open Interest (Futures):
OI Increase (🔴 Red):
New positions opened
Strong market conviction
Movement may intensify
OI Decrease (🟢 Green):
Position closing
Profit-taking or stop losses
Possible reversal
🔔 Configurable Alerts
The indicator includes 8 types of alerts:
🟡 Moderate Crisis Alert: Score 50-70
🟠 HIGH Crisis ALERT: Score 70-85
🔴 MAJOR CRISIS: Score 85-100
⚠️ REINFORCED SIGNAL: Extreme Volume + Volatility simultaneous
💎 RECORD Volume: Highest volume over 50 days
📊 Cluster DETECTED: 3+ consecutive abnormal days
📈 OI SPIKE >25%: Sharp Open Interest increase
📉 OI DECLINE >25%: Sharp Open Interest decrease
Setup: Right-click on chart → "Add Alert" → Select alert
💡 Optimization Tips
Scalping (1-5min):
MA Period: 10-15
Moderate Threshold: 1.3x
High Threshold: 1.8x
Volume Weight: 50%
Day Trading (15min-1H):
MA Period: 20 (default)
Thresholds: Default
Composite Score: Enabled
Swing Trading (4H-Daily):
MA Period: 30-50
StdDev Multiplier: 2.5
ATR Period: 20
Volatile Markets (Crypto):
Moderate Threshold: 1.8x
High Threshold: 2.5x
Extreme Threshold: 4.0x
ATR Weight: 30%
📊 Statistics Table
The real-time table displays:
Crisis Score: 0-100 with color coding
Current volume: Value and ratio
Volume Score: Contribution to total score
Open Interest: Estimated value and % change
VIX: Current value (if enabled)
ATR: Ratio to average
Global STATUS: Normal ✅ / Vigilance 🟡 / Danger 🟠 / Crisis 🔴
⚠️ Warnings and Limitations
❌ Limitations:
Open Interest is estimated (Volume / 2), not real value
VIX only works for S&P 500
False signals possible in very volatile markets
✅ Best Practices:
Always combine with classic technical analysis
Never trade solely on alerts
Adapt thresholds to your asset and timeframe
Backtest before using live
Respect your risk management plan
🎓 Real Use Cases
Example 1: Flash Crash
Extreme volume 🔴 + Extreme ATR 🔴 + Reinforced signal ⚠️
Composite score > 90
Action: No new trades, protect existing positions
Example 2: Fed Announcement
VIX > 35 + Moderate volume 🟡 + OI rising 🔴
Composite score: 65
Action: Reduce position size, widen stops
Example 3: Volatility Squeeze
Cluster detected + Volume record 💎 + OI declining 🟢
Action: Scalping opportunity in breakout direction
📈 Performance
Real-time detection (0 lag)
Compatible all markets and timeframes
Low resource consumption
Complete history preserved
VSA Visual RenkoWith this script you will be able to identify absorption, exhaustion, and a possible end of movement.
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RSI Median DeviationRSI Median Deviation – Adaptive Statistical RSI for High-Probability Extremes
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder in 1978 to measure the magnitude of recent price changes and identify potential overbought or oversold conditions. It calculates the ratio of upward to downward price movements over a specified period, scaled to 0-100. However, standard RSI often relies on fixed thresholds like 70/30, which can produce unreliable signals in varying market regimes due to their lack of adaptability to the actual distribution of RSI values.
This indicator was developed because I needed a reliable tool for spotting intermediate high-probability bottoms and tops. Instead of arbitrary horizontal lines, it uses the RSI’s own historical median as a dynamic centerline and measures how far the current RSI deviates from that median over a chosen lookback period. The main signals are triggered only at 2 standard deviation (2σ) extremes — statistically rare events that occur roughly 5 % of the time under a normal distribution. I selected 2σ because it is extreme enough to be meaningful yet frequent enough for practical trading. For oversold signals I further require RSI to be below 42, a filter that significantly improved results in my mean-reversion tests (enter on oversold, exit on the first bar the condition is no longer true).
The combination of percentile median + standard deviation bands is deliberate: the median is far more robust to outliers than a simple average, while the SD bands automatically adjust to the current volatility of the RSI itself, producing adaptive envelopes that work equally well in ranging and trending markets.
Underlying Concepts and Calculations
Base RSI: RSI = 100 − (100 / (1 + RS)), RS = average gain / average loss (default length 10).
Percentile Median: 50th percentile of the last "N" RSI values (default 28 = 4 weeks)
→ dynamic, outlier-resistant centerline.
Standard Deviation Bands: rolling stdev of RSI (default length 27 = = 4 weeks (almost))
→ bands = median ± 1σ / 2σ.
Optional Dynamic MA Envelopes: user-selectable moving average (TEMA, WMA, etc., default WMA length 37) for additional momentum context.
Trend Bias Coloring
Independent of the statistical extremes, the RSI line itself is colored green when above the user-defined Long Threshold (default 60) and red when below the Short Threshold (default 47). This provides an instant bullish/bearish bias overlay similar to classic RSI usage, without interfering with the main 2σ extreme signals.
Extremes are highlighted with background color (green for oversold 2σ + RSI<42, magenta for overbought 2σ) and small diamond markers for ultra-extremes (RSI <25 or >85).
Originality and Development Rationale
The indicator was built and refined through extensive testing on dozens of assets including major cryptocurrencies:
(BTC, ETH, SOL, SUI, BNB, XRP, TRX, DOGE, LINK, PAXG, CVX, HYPE, VIRTUAL and many more),
the Magnificent 7 stocks,, QQQ, SPX, and gold.
Default parameters were chosen to deliver consistent profitability in simple mean-reversion setups while maximizing Sortino ratio and minimizing maximum drawdown across this broad universe — ensuring the settings are robust and not overfitted to any single instrument or timeframe.
How to Use It
Ideal for swing / position trading on the 1h to daily charts (the same defaults work).
Oversold (high-probability long): RSI crosses below lower 2σ band AND RSI < 42
→ green background
→ enter long, exit the first bar the condition disappears.
Overbought (high-probability short): RSI crosses above upper 2σ band
→ magenta background
→ enter short, exit on opposite signal or at median. (Shorts were not tested, it's only an idea)
Use the green/red RSI line coloring for quick trend context and to avoid fighting strong momentum.
Always confirm with price action and manage risk appropriately.
This indicator is not a standalone trading system.
Disclaimer: This is not financial advice. Backtests are based on past results and are not indicative of future performance.
Standard Deviation Levels with Settlement Price and VolatilityStandard Deviation Levels with Settlement Price and Volatility.
This indicator plots the standard deviation levels based on the settlement price and the implied volatility. It works for all Equity Stocks and Futures.
For Futures
Symbol Volatility Symbol (Implied Volatility)
NQ VXN
ES VIX
YM VXD
RTY RVX
CL OVX
GC GVZ
BTC DVOL
The plot gives you an ideas that the price has what probability staying in the range of 1SD,2SD,3SD ( In normal distribution method)
Please provide the feedback or comments if you find any improvements
ATR R-LevelsATR-R Levels is built for clarity of risk management.
The script takes your account size, chosen risk %, and the market’s volatility, then turns all of that into exact stop-loss, take-profit, and position size so there’s no guessing.
It’s inspired by key principles from NNFX, especially ATR-based stop placement and fixed-risk position sizing, but redesigned for fast intraday crypto trading. You get the same consistency and discipline NNFX is known for, adapted to a much shorter timeframe.
ATR-R Levels gives you:
A volatility-based stop using ATR
A clean 2R (or custom R-multiple) target
Automatic position sizing based on your risk rules
A simple HUD showing ATR, entry, stop, TP, size, and risk
Optional net profit estimates after fees
Let me know what you think or if you use it!
Volatility Trend FollowerThe script combines several classic technical analysis techniques:
SuperTrend / Adaptive Band - The main idea comes from the SuperTrend indicator, which uses ATR (Average True Range) to create a trailing band that adapts to volatility
ATR (Average True Range) - A volatility measure developed by J. Welles Wilder Jr.
EMA (Exponential Moving Average) - Used as a global trend filter
Heikin Ashi - An option to smooth prices and reduce noise
Trend Following $BTC - Multi-Timeframe Structure + ReversTREND FOLLOWING STRATEGY - MULTI-TIMEFRAME STRUCTURE BREAKOUT SYSTEM
Strategy Overview
This is an enhanced Turtle Trading system designed for cryptocurrency spot trading. It combines Donchian Channel breakouts with multi-timeframe structure filtering and ATR-based dynamic risk management. The strategy trades both long and short positions using reverse signal exits to maximize trend capture.
Core Features
Multi-Timeframe Structure Filtering
The strategy uses Swing High/Low analysis to identify market structure trends. You can customize the structure timeframe (default: 3 minutes) to match your trading style. Only enters trades aligned with the identified trend direction, avoiding counter-trend positions that often lead to losses.
Reverse Signal Exit System
Instead of using fixed stop-losses or time-based exits, this strategy exits positions only when a reverse entry signal triggers. This approach maximizes trend profits and reduces premature exits during normal market retracements.
ATR Dynamic Pyramiding
Automatically adds positions when price moves 0.5 ATR in your favor. Supports up to 2 units maximum (adjustable). This pyramid scaling enhances profitability during strong trends while maintaining disciplined risk management.
Complete Risk Management
Fixed position sizing at 5000 USD per unit. Includes realistic commission fees of 0.06% (Binance spot rate). Initial capital set at 10,000 USD. All backtest parameters reflect real-world trading conditions.
Trading Logic
Entry Conditions
Long Entry: Close price breaks above the 20-period high AND structure trend is bullish (price breaks above Swing High)
Short Entry: Close price breaks below the 20-period low AND structure trend is bearish (price breaks below Swing Low)
Position Scaling
Long positions: Add when price rises 0.5 ATR or more
Short positions: Add when price falls 0.5 ATR or more
Maximum 2 units including initial entry
Exit Conditions
Long Exit: Triggers when short entry signal appears (price breaks 20-period low + structure turns bearish)
Short Exit: Triggers when long entry signal appears (price breaks 20-period high + structure turns bullish)
Default Parameters
Channel Settings
Entry Channel Period: 20 (Donchian Channel breakout period)
Exit Channel Period: 10 (reserved parameter)
ATR Settings
ATR Period: 20
Stop Loss ATR Multiplier: 2.0
Add Position ATR Multiplier: 0.5
Structure Filter
Swing Length: 300 (Swing High/Low calculation period)
Structure Timeframe: 3 minutes
Adjust these based on your trading timeframe and asset volatility
Position Management
Maximum Units: 2 (including initial entry)
Capital Per Unit: 5000 USD
Visualization Features
Background Colors
Light Green: Bullish market structure
Light Red: Bearish market structure
Dark Green: Long position entry
Dark Red: Short position entry
Optional Display Elements (Default: OFF)
Entry and exit channel lines
Structure high/low reference lines
ATR stop-loss indicator
Next position add level
Entry/exit labels
Alert Message Format
The strategy sends notifications with the following format:
Entry: "5m Long EP:90450.50"
Add Position: "15m Add Long 2/2 EP:91000.25"
Exit: "5m Close Long Reverse Signal"
Where the first part shows your current chart timeframe and EP indicates Entry Price
Backtest Settings
Capital Allocation
Initial Capital: 10,000 USD
Per Entry: 5,000 USD (split into 2 potential entries)
Leverage: 0x (spot trading only)
Trading Costs
Commission: 0.06% (Binance spot VIP0 rate)
Slippage: 0 (adjust based on your experience)
Best Use Cases
Ideal Scenarios
Trending markets with clear directional movement
Moderate to high volatility assets
Timeframes from 1-minute to 4-hour charts
Best suited for major cryptocurrencies with good liquidity
Not Recommended For
Highly volatile choppy/ranging markets
Low liquidity small-cap coins
Extreme market conditions or black swan events
Usage Recommendations
Timeframe Guidelines
1-5 minute charts: Use for scalping, consider Swing Length 100-160
15-30 minute charts: Good for short-term trading, Swing Length 50-100
1-4 hour charts: Suitable for swing trading, Swing Length 20-50
Optimization Tips
Always backtest on historical data before live trading
Adjust swing length based on asset volatility and your timeframe
Different cryptocurrencies may require different parameter settings
Enable visualization options initially to understand entry/exit points
Monitor win rate and drawdown during backtesting
Technical Details
Built on Pine Script v6
No repainting - uses proper bar referencing with offset
Prevents lookahead bias with lookahead=off parameter
Strategy mode with accurate commission and slippage modeling
Multi-timeframe security function for structure analysis
Proper position state tracking to avoid duplicate signals
Risk Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Backtesting results may differ from live trading due to slippage, execution delays, and changing market conditions. The strategy performs best in trending markets and may experience drawdowns during ranging conditions. Always practice proper risk management and never risk more than you can afford to lose. It is recommended to paper trade first and start with small position sizes when going live.
How to Use
Add the strategy to your TradingView chart
Select your desired timeframe (1m to 4h recommended)
Adjust parameters based on your risk tolerance and trading style
Review backtest results in the Strategy Tester tab
Set up alerts for automated notifications
Consider paper trading before risking real capital
Tags
Trend Following, Turtle Trading, Donchian Channel, Structure Breakout, ATR, Cryptocurrency, Spot Trading, Risk Management, Pyramiding, Multi-Timeframe Analysis
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Strategy Name: Trend Following BTC
Version: v1.0
Pine Script Version: v6
Last Updated: December 2025
FF calculation Saptarshi ChatterjeeForward factor (in options contexts) measures implied volatility (IV) for a future period between two expirations, like from 30 DTE (days to expiry) front-month to 60 DTE back-month options.
This indicator calculates the FORWARD FACTOR(FF) using 2 IVs of 2 DTEs.
+ve value means front DTE is rich in premium and back expiry is cheap.
-ve value means front DTE IV is cheap and 2nd DTE is expensive
we can use this term structure disbalance to trade calendar spreads with edge.
Trend Following $ZEC - Multi-Timeframe Structure Filter + Revers# Trend Following CRYPTOCAP:ZEC - Strategy Guide
## 📊 Strategy Overview
Trend Following CRYPTOCAP:ZEC is an enhanced Turtle Trading system designed for cryptocurrency spot trading, combining Donchian Channel breakouts, multi-timeframe structure filtering, and ATR-based dynamic risk management for both long and short positions.
---
## 🎯 Core Features
1. Multi-Timeframe Structure Filtering
- Uses Swing High/Low to identify market structure
- Customizable structure timeframe (default: 1 minute)
- Only enters trades in the direction of the trend, avoiding counter-trend positions
2. Reverse Signal Exit
- No fixed stop-loss or fixed-period exits
- Exits only when a reverse entry signal triggers
- Maximizes trend profits, reduces premature exits
3. ATR Dynamic Pyramiding
- Adds positions when price moves 0.5 ATR in favorable direction
- Supports up to 2 units maximum (adjustable)
- Pyramid scaling to enhance profitability
4. Complete Risk Management
- Fixed position size (5000 USD per unit)
- Commission fee 0.06% (Binance spot rate)
- Initial capital 10,000 USD
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## 📈 Trading Logic
Entry Conditions
✅ Long Entry:
- Close price breaks above 20-period high
- Structure trend is bullish (price breaks above Swing High)
✅ Short Entry:
- Close price breaks below 20-period low
- Structure trend is bearish (price breaks below Swing Low)
Add Position Conditions
- Long: Price rises ≥ 0.5 ATR
- Short: Price falls ≥ 0.5 ATR
- Maximum 2 units including initial entry
Exit Conditions
- Long Exit: When short entry signal triggers (price breaks 20-period low + structure turns bearish)
- Short Exit: When long entry signal triggers (price breaks 20-period high + structure turns bullish)
---
## ⚙️ Parameter Settings
Channel Settings
- Entry Channel Period: 20 (Donchian Channel breakout period)
- Exit Channel Period: 10 (reserved parameter, actually uses reverse signal exit)
ATR Settings
- ATR Period: 20
- Stop Loss ATR Multiplier: 2.0 (reserved parameter)
- Add Position ATR Multiplier: 0.5
Structure Filter
- Swing Length: 160 (Swing High/Low calculation period)
- Structure Timeframe: 1 minute (can change to 5/15/60, etc.)
Position Management
- Maximum Units: 2 (including initial entry)
- Capital Per Unit: 5000 USD
---
## 🎨 Visualization Features
Background Colors
- Light Green: Bullish structure
- Light Red: Bearish structure
- Dark Green: Long entry
- Dark Red: Short entry
Optional Display (Default: OFF)
- Entry/exit channel lines
- Structure high/low lines
- ATR stop-loss line
- Next add position indicator
- Entry/exit labels
---
## 📱 Alert Message Format
Strategy sends notifications on entry/exit with the following format:
- Entry: `1m Long EP:428.26`
- Add Position: `15m Add Long 2/2 EP:429.50`
- Exit: `1m Close Long Reverse Signal`
Where:
- `1m`/`15m` = Current chart timeframe
- `EP` = Entry Price
---
## 💰 Backtest Settings
Capital Allocation
- Initial Capital: 10,000 USD
- Per Entry: 5,000 USD (split into 2 entries)
- Leverage: 0x (spot trading)
Trading Costs
- Commission: 0.06% (Binance spot VIP0)
- Slippage: 0
---
## 🎯 Use Cases
✅ Best Scenarios
- Trending markets
- Moderate volatility assets
- 1-minute to 4-hour timeframes
⚠️ Not Suitable For
- Highly volatile choppy markets
- Low liquidity small-cap coins
- Extreme market conditions (black swan events)
---
## 📊 Usage Recommendations
Timeframe Suggestions
| Timeframe | Trading Style | Suggested Parameter Adjustment |
|-----------|--------------|-------------------------------|
| 1-5 min | Scalping | Swing Length 100-160 |
| 15-30 min | Short-term | Swing Length 50-100 |
| 1-4 hour | Swing Trading | Swing Length 20-50 |
Optimization Tips
1. Adjust swing length based on backtest results
2. Different coins may require different parameters
3. Recommend backtesting on 1-minute chart first before live trading
4. Enable labels to observe entry/exit points
---
## ⚠️ Risk Disclaimer
1. Past Performance Does Not Guarantee Future Results
- Backtest data is for reference only
- Live trading may be affected by slippage, delays, etc.
2. Market Condition Changes
- Strategy performs better in trending markets
- May experience frequent stops in ranging markets
3. Capital Management
- Do not invest more than you can afford to lose
- Recommend setting total capital stop-loss threshold
4. Commission Impact
- Frequent trading accumulates commission fees
- Recommend using exchange discounts (BNB fee reduction, etc.)
---
## 🔧 Troubleshooting
Q: No entry signals?
A: Check if structure filter is too strict, adjust swing length or timeframe
Q: Too many labels displayed?
A: Turn off "Show Labels" option in settings
Q: Poor backtest performance?
A:
1. Check if the coin is suitable for trend-following strategies
2. Adjust parameters (swing length, channel period)
3. Try different timeframes
Q: How to set alerts?
A:
1. Click "Alert" in top-right corner of chart
2. Condition: Select "Strategy - Trend Following CRYPTOCAP:ZEC "
3. Choose "Order filled"
4. Set notification method (Webhook/Email/App)
---
## 📞 Contact Information
Strategy Name: Trend Following CRYPTOCAP:ZEC
Version: v1.0
Pine Script Version: v6
Last Updated: December 2025
---
## 📄 Copyright Notice
This strategy is for educational and research purposes only.
All risks of using this strategy for live trading are borne by the user.
Commercial use without authorization is prohibited.
---
## 🎓 Learning Resources
To understand the strategy principles in depth, recommended reading:
- "The Complete TurtleTrader" - Curtis Faith
- "Trend Following" - Michael Covel
- TradingView Pine Script Official Documentation
---
Happy Trading! Remember to manage your risk 📈
StrategyScript77 Is a rule-based strategy built on top of an Ichimoku based engine.
Ichimoku concepts are used as the backbone for trend and momentum filtering, so the strategy tends to stay on the side of the dominant move instead of fighting it.
The name “Super77” comes from the behavior I consistently observed in testing because the win rate tends to hover around the 70–80% range, often clustering around ~77% when used as intended.
It’s not a promise or guarantee, but it reflects the core design philosophy: frequent, relatively small but steady wins, with controlled and manageable losses.
Trading Style – Built for Conservative Traders
Super77 is intentionally designed for traders who prefer a conservative and calm approach:
Entries only at bar close
The strategy waits for bar close confirmation before entering a position. No intrabar guessing, no chasing half-formed signals. If the signal is still valid at close, only then will it enter.
Exits automated on bar close
Exits are also managed on bar close, which makes the logic transparent, easy to review on the chart, and more robust in backtesting compared to tick-based or intrabar hacks.
Semi-auto friendly
If you like to keep some discretion, you can treat it as semi-automatic:
Let the strategy generate entry signals
Manually cancel or skip certain trades if market context changes (news, extreme volatility, etc.)
This combination makes Super77 suitable for traders who don’t want to stare at the screen all day but still want structure and automation.
How to Use
Works best with bar-close execution (avoid trying to simulate intrabar fills if you want consistent behavior).
Designed for conservative, trend-aligned trading, not for hyper-scalping or news gambling.
Can be used as:
Fully automated (let all entries/exits trigger on bar close), or
Semi-automated (use alerts/signals but manually cancel some entries).
Step-by-Step: Automation with Cornix (Webhook Setup)
You can automate Super77 using Cornix by connecting TradingView alerts to your Cornix group via webhook.
Note: Exact button names may differ slightly depending on Cornix / TradingView updates, but the flow is always the same:
Cornix group → get webhook URL & mapping → TradingView alerts → signals sent to Cornix.
(Optional) Map specific pairs / directions
If you use UUID / signal mapping per symbol and per side (long/short), set them up in Cornix according to your own template.
Super77 can be used either:
On a single pair (simple setup), or
On multiple pairs if your alert / webhook structure supports that. So you can pick many pairs with 1 script.
Final Notes & Disclaimer
Super77 is an educational and experimental trading tool, not financial advice.
Past performance in back tests does not guarantee future results.
Always:
Test on demo or paper first
Adjust risk to match your own profile
Accept that losses and drawdowns are a natural part of any strategy
If you’re looking for a strategy that reflects a conservative, confirmation-based trading style with a focus on steady win rate and smoother equity behavior, Super77 was built exactly with that mindset in mind.
Volatility Value BandsThis indicator is a modern adaptation of Mark Helweg's original Value Charts concept, focused on visually displaying volatility zones and "extreme value" areas directly on the price chart. It does not replicate the original work but draws inspiration from the logic of normalizing price by volatility to highlight statistically stretched regions.
1. Introduction
This study displays three lines directly on the chart:
- a central reference line (base),
- an upper overvaluation band,
- and a lower undervaluation band.
The bands are calculated from the relationship between price, moving average, and volatility (via true range/ATR), following Mark Helweg's Value Charts concept but with a custom implementation and adjustable parameters for different assets and timeframes. This allows objectively visualizing when price is in a statistically extended region relative to its recent behavior.
2. Key Features
- Volatility-normalized base
The indicator converts price deviation into "value units" using a combination of moving average and smoothed volatility (true range/ATR), making levels comparable across different assets and time horizons.
- Auto-adjusting limits (optional)
An automatic mode can calculate upper and lower limits from recent value unit extremes, using a configurable sampling window and percentile, allowing bands to adapt to the current volatility regime without manual recalibration.
- Direct plot on price chart
The three lines (central, upper, and lower) are drawn directly on the main asset chart (`overlay`), making it easy to read context: it's clear when price "touches" or breaks the volatility bands without switching to a separate pane.
- Flexible parameters
Users can control:
- base moving average period (length)
- volatility factor (manual or automatic)
- independent windows for volatility and limits calculation
- limits mode (auto or manual) and percentile used
This allows adapting behavior to different markets (stocks, indices, forex, crypto).
3. How to Use
- Basic interpretation
- When price approaches or exceeds the upper band, it indicates a statistically overvalued zone where the asset is stretched upward relative to recent volatility.
- When price approaches or exceeds the lower band, it indicates a statistically undervalued zone.
- The central line serves as a reference for recent "average value," derived from the base moving average.
- Recommended initial setup
- Choose the Value Chart period (e.g., 144 bars) for the base.
- Enable automatic limits mode for coherent bands matching the asset's volatility.
- Adjust the limits window and percentile for tighter bands (more signals) or wider bands (fewer but more extreme).
- Best practices
- Use bands as context filters, not standalone buy/sell signals. Combine with trend, market structure, or other confirmation indicators.
- Avoid decisions solely because price touched a band; in strong trends, price can "walk the edge" for extended periods.
- Always follow TradingView community rules when publishing: clearly state in the description that the study is "inspired by Mark Helweg's Value Charts concept," without claiming official status, reproducing proprietary code, or violating copyrights.
IV vs Realised Volatility (VIX/HV Comparator)VIX / HV Comparator – Implied vs Realised Volatility
This indicator compares Implied Volatility (IV) from a volatility index (VIX, India VIX, etc.) with the Realised / Historical Volatility (HV) of the current chart symbol.
It helps you see whether options are pricing volatility as rich or cheap relative to what the underlying is actually doing.
What it does
Pulls IV from any user-selected vol index symbol (e.g. CBOE:VIX for SPX, NSEINDIA:INDIAVIX for Nifty).
Calculates realised volatility from the chart’s price data using returns over a user-defined lookback.
Annualises HV so IV and HV are displayed on the same percentage scale, on any timeframe (intraday or higher).
Optionally shows an IV/HV ratio in a separate pane to highlight when options are rich or cheap relative to realised volatility.
How to read it
Main panel:
Orange line – Implied Volatility (IV) from your chosen vol index.
Aqua line – Realised / Historical Volatility (HV) of the current chart symbol.
Fill between lines:
Green shading -> IV > HV -> options are priced richer than what the underlying is currently realising.
Red shading -> HV > IV -> realised vol is higher than the options market is implying.
Sub-panel (optional):
IV / HV ratio
- Above 1 -> IV > HV (vol rich).
- Below 1 -> IV < HV (vol cheap).
- Horizontal guides (for example 1.2 / 0.8) help frame “significantly rich/cheap” zones.
A small label on the latest bar displays the current IV, HV and their difference in vol points.
Inputs (key ones)
IV Index Symbol – choose the volatility index that corresponds to your underlying (VIX, India VIX, etc.).
Realised Vol Lookback – number of bars used to compute HV (for example 20).
Trading Days per Year and Active Hours per Day – used for annualising HV so it stays consistent across timeframes.
IV Scale Factor – adjust if your IV index is quoted in decimals (0.15) instead of points (15).
Practical uses
Context for options trades – Quickly see if current IV is high or low relative to realised volatility when deciding on strategies (premium selling vs buying, spreads, hedges).
Vol regime analysis – Track shifts where HV starts to rise above IV (real stress building) or IV spikes far above HV (fear premium / insurance bid).
Cross-timeframe checks – Use on intraday charts for short-term trading context, or on daily/weekly charts for bigger picture vol regimes.
This tool is not a stand-alone signal generator. It is meant to be a volatility dashboard you combine with your usual price action, trend, and options strategy rules to understand how the options market is pricing risk vs what the underlying is actually delivering.
Institutional Equity DashboardAn overlay indicator with everything you need:
Trend Ribbon - 8/21/50/200 EMA cloud with bullish/bearish fill
VWAP + Bands - The institutional benchmark with deviation bands
Auto S/R Detection - Pivot-based support/resistance levels
ATR-Based Stops - Dynamic stop-loss levels that adjust to volatility
Confluence Signals - Multi-factor buy/sell signals (regular + strong)
Real-Time Dashboard showing:
Market regime (Strong Uptrend → Strong Downtrend)
Trend score (0-100)
RSI, MACD, Stochastic status
Volume ratio and VWAP position
Risk metrics (ATR%, Historical Vol, Risk Level)
Relative strength vs. benchmark
Elliott Wave Full Fractal System v2.0Elliott Wave Full Fractal System v2.0 – Q.C. FINAL (Guaranteed R/R)
Elliott Wave Full Fractal System is a multi-timeframe wave engine that automatically labels Elliott impulses and ABC corrections, then builds a rule-based, ATR-driven risk/reward framework around the “W3–W4–W5” leg.
“Guaranteed R/R” here means every order is placed with a predefined stop-loss and take-profit that respect a minimum Reward:Risk ratio – it does not mean guaranteed profits.
Core Idea
This strategy turns a full fractal Elliott Wave labelling engine into a systematic trading model.
It scans fractal pivots on three wave degrees (Primary, Intermediate, Minor) to detect 5-wave impulses and ABC corrections.
A separate “Trading Degree” pivot stream, filtered by a 200-EMA trend filter and ATR-based dynamic pivots, is then used to find W4 pullback entries with a minimum, user-defined Reward:Risk ratio.
Default Properties & Risk Assumptions
The backtest uses realistic but conservative defaults:
// Default properties used for backtesting
strategy(
"Elliott Wave Full Fractal System - Q.C. FINAL (Guaranteed R/R)",
overlay = true,
initial_capital = 10000, // realistic account size
default_qty_type = strategy.percent_of_equity,
default_qty_value = 1, // 1% risk per trade
commission_type = strategy.commission.cash_per_contract,
commission_value = 0.005, // example stock commission
slippage = 0 // see notes below
)
Account size: 10,000 (can be changed to match your own account).
Position sizing: 1% of equity per trade to keep risk per idea sustainable and aligned with TradingView’s recommendations.
Commission: 0.005 cash per contract/share as a realistic example for stock trading.
Slippage: set to 0 in code for clarity of “pure logic” backtesting. Real-life trading will experience slippage, so users should adjust this according to their market and broker.
Always re-run the backtest after changing any of these values, and avoid using high risk fractions (5–10%+) as that is rarely sustainable.
1. Full Fractal Wave Engine
The script builds and maintains four pivot streams using ATR-adaptive fractals:
Primary Degree (Macro Trend):
Captures the large swings that define the major trend. Labels ①–⑤ and ⒶⒷⒸ using blue “Circle” labels and thicker lines.
Intermediate Degree (Trading Degree):
Captures the medium swings (swing-trading horizon). Uses teal labels ( (1)…(5), (A)(B)(C) ).
Minor Degree (Micro Structure):
Tracks short-term swings inside the larger waves. Uses red roman numerals (i…v, a b c).
ABC Corrections (Optional):
When enabled, the engine tries to detect standard A–B–C corrective structures that follow a completed 5-wave impulse and plots them with dashed lines.
Each degree uses a dynamic pivot lookback that expands when ATR is above its EMA, so the system naturally requires “stronger” pivots in volatile environments and reacts faster in quiet conditions.
2. Theory Rules & Strict Mode
Normal Mode: More permissive detection. Designed to show more wave structures for educational / exploratory use.
Strict Mode: Enforces key Elliott constraints:
Wave 3 not shorter than waves 1 and 5.
No invalid W4 overlap with W1 (for standard impulses).
ABC Logic: After a confirmed bullish impulse, the script expects a down-up-down corrective pattern (A,B,C). After a bearish impulse, it looks for up-down-up.
3. Trend Filter & Pivots
EMA Trend Filter: A configurable EMA (default 200) is used as a non-wave trend filter.
Price above EMA → Only long setups are considered.
Price below EMA → Only short setups are considered.
ATR-Adaptive Pivots: The pivot engine scales its left/right bars based on current ATR vs ATR EMA, making waves and trading pivots more robust in volatile regimes.
4. Dynamic Risk Management (Guaranteed R/R Engine)
The trading engine is designed around risk, not just pattern recognition:
ATR-Based Stop:
Stop-loss is placed at:
Entry ± ATR × Multiplier (user-configurable, default 2.0).
This anchors risk to current volatility.
Minimum Reward:Risk Ratio:
For each setup, the script:
Computes the distance from entry to stop (risk).
Projects a take-profit target at risk × min_rr_ratio away from entry.
Only accepts the setup if risk is positive and the required R:R ratio is achievable.
Result: Every order is created with both TP and SL at a predefined distance, so each trade starts with a known, minimum Reward:Risk profile by design.
“Guaranteed R/R” refers exclusively to this order placement logic (TP/SL geometry), not to win-rate or profitability.
5. Trading Logic – W3–W4–W5 Pattern
The Trading pivot stream (separate from visual wave degrees) looks for a simple but powerful pattern:
Bullish structure:
Sequence of pivots forms a higher-high / higher-low pattern.
Price is above the EMA trend filter.
A strong “W3” leg is confirmed with structure rules (optionally stricter in Strict mode).
Entry (Long – W4 Pullback):
The “height” of W3 is measured.
Entry is placed at a configurable Fibonacci pullback (default 50%) inside that leg.
ATR-based stop is placed below entry.
Take-profit is projected to satisfy min Reward:Risk.
Bearish structure:
Mirrored logic (lower highs/lows, price below EMA, W3 down, W4 retrace up, W5 continuation down).
Once a valid setup is found, the script draws a colored box around the entry zone and a label describing the type of signal (“LONG SETUP” or “SHORT SETUP”) with the suggested limit price.
6. Orders & Execution
Entry Orders: The strategy uses limit orders at the computed W4 level (“Sniper Long” or “Sniper Short”).
Exits: A single strategy.exit() is attached to each entry with:
Take-profit at the projected minimum R:R target.
Stop-loss at ATR-based level.
One Trade at a Time: New setups are only used when there is no open position (strategy.opentrades == 0) to keep the logic clear and risk contained.
7. Visual Guide on the Chart
Wave Labels:
Primary: ①,②,③,④,⑤, ⒶⒷⒸ
Intermediate: (1)…(5), (A)(B)(C)
Minor: i…v, a b c
Trend EMA: Single blue EMA showing the dominant trend.
Setup Boxes:
Green transparent box → long entry zone.
Red transparent box → short entry zone.
Labels: “LONG SETUP / SHORT SETUP” labels mark the proposed limit entry with price.
8. How to Use This Strategy
Attach the strategy to your chart
Choose your market (stocks, indices, FX, crypto, futures, etc.) and timeframe (for example 1h, 4h, or Daily). Then add the strategy to the chart from your Scripts list.
Start with the default settings
Leave all inputs on their defaults first. This lets you see the “intended” behaviour and the exact properties used for the published backtest (account size, 1% risk, commission, etc.).
Study the wave map
Zoom in and out and look at the three wave degrees:
Blue circles → Primary degree (big picture trend).
Teal (1)…(5) → Intermediate degree (swing structure).
Red i…v → Minor degree (micro waves).
Use this to understand how the engine is interpreting the Elliott structure on your symbol.
Watch for valid setups
Look for the coloured boxes and labels:
Green box + “LONG SETUP” label → potential W4 pullback long in an uptrend.
Red box + “SHORT SETUP” label → potential W4 pullback short in a downtrend.
Only trades in the direction of the EMA trend filter are allowed by the strategy.
Check the Reward:Risk of each idea
For each setup, inspect:
Limit entry price.
ATR-based stop level.
Projected take-profit level.
Make sure the minimum Reward:Risk ratio matches your own rules before you consider trading it.
Backtest and evaluate
Open the Strategy Tester:
Verify you have a decent sample size (ideally 100+ trades).
Check drawdowns, average trade, win-rate and R:R distribution.
Change markets and timeframes to see where the logic behaves best.
Adapt to your own risk profile
If you plan to use it live:
Set Initial Capital to your real account size.
Adjust default_qty_value to a risk level you are comfortable with (often 0.5–2% per trade).
Set commission and slippage to realistic broker values.
Re-run the backtest after every major change.
Use as a framework, not a signal machine
Treat this as a structured Elliott/R:R framework:
Filter signals by higher-timeframe trend, major S/R, volume, or fundamentals.
Optionally hide some wave degrees or ABC labels if you want a cleaner chart.
Combine the system’s structure with your own trade management and discretion.
Best Practices & Limitations
This is an approximate Elliott Wave engine based on fractal pivots. It does not replace a full discretionary Elliott analysis.
All wave counts are algorithmic and can differ from a manual analyst’s interpretation.
Like any backtest, results depend heavily on:
Symbol and timeframe.
Sample size (more trades are better).
Realistic commission/slippage settings.
The 0-slippage default is chosen only to show the “raw logic”. In real markets, slippage can significantly impact performance.
No strategy wins all the time. Losing streaks and drawdowns will still occur even with a strict R:R framework.
Disclaimer
This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance, whether real or simulated, is not indicative of future results. Always test on multiple symbols/timeframes, use conservative risk, and consult your financial advisor before trading live capital.
VCAI MACD LiteVCAI MACD Lite is a clean, modern version of the classic MACD oscillator, rebuilt with selectable EMA/SMA types and a 2-tone histogram using VCAI’s visual style.
It keeps the indicator lightweight and easy to read while giving clearer momentum shifts through rising/falling histogram colour changes.
What it does
Calculates MACD using your choice of EMA or SMA
Plots signal line and histogram with 2-tone VCAI colours
Highlights changes in momentum strength as histogram bars rise or fade
Works on any market and timeframe
How to use it
Expanding yellow bars reflect strengthening upside momentum; dim yellow shows fading strength.
Darker and lighter VCAI purple tones show momentum behaviour below zero, helping you see when bearish pressure is increasing or weakening.
Part of the VCAI Lite Series — clean, minimal tools.
