VWolf - Quantum DriftOVERVIEW
The Quantum Drift strategy is a sophisticated, highly customizable trading approach designed to identify market entries and exits by leveraging multiple technical indicators. The strategy uniquely combines the Dynamic Exponential Moving Average (DEMA), QQE indicators, Volume Oscillator, and Hull Moving Average (HULL), enabling precise detection of trend direction, momentum shifts, and volatility adjustments. It stands out due to its adaptability across different market conditions by allowing significant user customization through various input parameters.
RECOMMENDED USE
Markets: Ideal for Forex and Stocks due to the strategy's volatility-sensitive and trend-following nature.
Timeframes: Best suited for medium to higher timeframes (15m, 1H, 4H), where clearer trend signals and less noise occur, enhancing strategy reliability.
CONCLUSION
The Quantum Drift strategy is tailored for intermediate to advanced traders seeking a versatile and adaptive system. Its strength lies in combining momentum, volatility, and trend-following components, providing robust entry and exit signals. However, its effectiveness relies significantly on accurate parameter tuning by traders familiar with the underlying indicators and market behavior.
FOR MORE INFORMATION VISIT vwolftrading.com
Wskaźniki i strategie
VWolf – Pivot VumanSkewOVERVIEW
This strategy blends a lightweight trend scaffold (EMA/DEMA) with a skew-of-volatility filter and VuManchu/WaveTrend momentum signals. It’s designed to participate only when trending structure, momentum alignment, and volatility asymmetry converge, while delegating execution management to either a standard SuperTrend or a Pivot-based SuperTrend. Position sizing is risk‑based, with optional two‑step profit taking and automatic stop movement once price confirms in favor.
RECOMMENDED USE
Markets: Designed for Forex and equities, and readily adaptable to indices or liquid futures.
Timeframes: Performs best from 15m to 4h where momentum and trend layers both matter; daily can be used for confirmation/context.
Conditions: Trending or range‑expansion phases with clear volatility asymmetry. Avoid extremely compressed sessions unless thresholds are relaxed.
Strengths
Multi‑layer confluence (trend + skew + momentum) reduces random signals.
Dual SuperTrend modes provide flexible trailing and regime control.
Built‑in hygiene (ADX/DMI, lockout after loss, ATR gap) curbs over‑trading.
Risk‑% sizing and two‑step exits support consistent, plan‑driven execution.
Precautions
Over‑tight thresholds can lead to missed opportunities; start from defaults and tune gradually.
High sensitivity in momentum settings may overfit to a single instrument/timeframe.
In very low volatility, ATR‑gap or skew filters may block entries—consider adaptive thresholds.
CONCLUSION
VWolf – Pivot VumanSkew is a disciplined trend‑participation strategy that waits for directional structure, volatility asymmetry, and synchronized momentum before acting. Its execution layer—selectable between Normal and Pivot SuperTrend—keeps management pragmatic: scale out early when appropriate, trail intelligently, and defend capital with volatility‑aware stops. For users building a diversified playbook, Pivot VumanSkew serves as a trend‑continuation workhorse that can be tightened for precision or relaxed for higher participation depending on the market’s rhythm.
VWolf – Momentum TwinOVERVIEW
VWolf – Momentum Twin is designed to identify high-probability momentum reversals emerging from overbought or oversold market conditions. It employs a double confirmation from the Stochastic RSI oscillator, optionally filtered by trend and directional movement conditions, before executing trades.
The strategy emphasizes consistent risk management by scaling stop-loss and take-profit targets according to market volatility (ATR), and it provides advanced position management features such as partial profit-taking and automated stop-loss adjustments.
RECOMMENDED USE
Markets: Major FX pairs, index futures, large-cap stocks, and top-volume cryptocurrencies.
Timeframes: Best suited for M15–H4; adaptable for swing trading on daily charts.
Trader Profile: Traders who value structured, volatility-adjusted momentum reversal setups.
Strengths:
Double confirmation filters out many false signals.
Multiple filter options allow strategic flexibility.
ATR scaling maintains consistent risk across assets.
Trade management tools improve adaptability in dynamic markets.
Precautions:
May produce fewer trades in strong one-direction trends.
Over-filtering can reduce trade frequency.
Requires validation across instruments and timeframes before deployment.
CONCLUSION
The VWolf – Momentum Twin offers a disciplined framework for capturing momentum reversals while preserving flexibility through its customizable filters and risk controls. Its double confirmation logic filters out a significant portion of false reversals, while ATR-based scaling ensures consistency across varying market conditions. The optional trade management features, including partial profit-taking and automatic stop adjustments, allow the strategy to adapt to both trending and ranging environments. This makes it a versatile tool for traders who value structured entries, robust risk control, and adaptable management in a variety of markets and timeframes.
VWolf – Hull VectorOVERVIEW
VWolf – Hull Vector is a momentum-driven trend strategy centered on the Hull Moving Average (HMA) angle. It layers optional confirmations from EMA/DEMA alignment, DMI/ADX strength, and Supertrend triggers to filter lower-quality entries and improve trade quality.
Risk is controlled through capital-based position sizing, ATR-anchored stops and targets, and dynamic trade management (partial exits and stop movement). The strategy supports Backtest and Forwardtest modes with configurable date ranges, and a market profile toggle (Forex vs. Stocks) to adjust internal scaling for price behavior.
RECOMMENDED USE
Markets: Major Forex pairs, index CFDs/futures, and liquid stocks with clean trend legs.
Styles: Intraday and swing applications where momentum continuation is common.
Volatility Regimes: Performs best in trending or expanding-volatility environments; consider tightening thresholds in choppy phases.
Workflow Tips:Start with HMA angle + ST trigger only; then layer DEMA and DMI/ADX if you need more selectivity.
Use Forwardtest dates to simulate out-of-sample performance after tuning Backtest parameters.
Re-evaluate angle thresholds when switching between Forex and Stocks modes.
Strengths
Clear momentum core (HMA angle) with optional, orthogonal filters (trend alignment, strength, trigger).
Robust risk tooling: ATR/ST stops, two-step profits, and capital-based sizing.
Testing discipline: Native Backtest/Forwardtest scoping supports walk-forward validation.
Broad portability: Works across instruments thanks to market-aware scaling.
Precautions
Over-filtering risk: Enabling all gates simultaneously may under-trade; calibrate selectivity to your timeframe.
Sideways markets: Expect more whipsaws when slope hovers near zero; raise angle threshold or rely more on ADX gating.
Overfitting hazard: Tune on one regime, then verify with Forwardtest windows and alternative markets/timeframes.
VWolf – Hulk StrikeOVERVIEW
VWolf – Hullk Strike is a dynamic trend-following strategy designed to capture pullbacks within established moves. It combines a configurable Moving Average (HULL, EMA, SMA, or DEMA) trend filter with DMI/ADX confirmation and a Stochastic RSI timing trigger. Risk is managed through ATR- or Supertrend-based stops, optional partial profit-taking, and automatic stop adjustments. The strategy aims to rejoin momentum after controlled retracements while maintaining consistent, quantified risk
RECOMMENDED USE
Markets: Liquid indices, major FX pairs, large-cap equities, high-liquidity crypto pairs.
Timeframes: M15 to D1 (stricter filters for lower timeframes, looser for higher).
Profiles: Traders seeking structured trend participation with systematic timing.
Strengths
Highly flexible trend engine adaptable to multiple markets.
Dual confirmation reduces false signals during pullbacks.
Risk-first design with multiple stop models and partial exits.
Precautions
Over-filtering may reduce trade frequency and miss fast continuations.
Under-filtering may increase whipsaw risk in choppy markets.
Backtest vs forward-test differences if date/session filters are inconsistent.
CONCLUSION
VWolf – Hullk Strike is designed to capture the “second leg” of a trend after a controlled retracement. With configurable MA strictness, DMI/ADX strength filters, and precise Stoch RSI timing, it enhances selectivity while keeping responsiveness. Its stop/target framework—anchored stops, proportional targets, partial exits, and dynamic stop moves—offers disciplined risk control and upside preservation.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf – EquinoxOVERVIEW
The VWolf – Equinox strategy integrates multiple technical filters, skew deviation logic, and advanced momentum indicators to identify high-probability trend continuation and reversal setups. Built upon the Vumanchu framework, this strategy applies filters such as EMA, DEMA, Supertrend, QQE, ADX/DMI, and customized skew thresholds. It combines these with divergence detection, volatility conditions, and risk-managed trade execution for dynamic adaptability across market conditions.
Its architecture is designed to provide flexibility for both backtesting and forward testing periods, while allowing traders to fine-tune entry confirmations and risk management tools based on their preferred market or timeframe.
RECOMMENDED USE
Markets: Forex, equities, and potentially crypto markets due to skew/volatility adaptability.
Timeframes: Works best on intraday (15m–1H) and swing-trading (4H–1D) horizons.
Trader Profile: Suited for intermediate to advanced traders who value multiple confirmation layers and dynamic risk management.
Strengths:
Robust filter system reduces false signals.
Flexible exit strategies with dynamic profit-taking.
Adaptability across different assets and timeframes.
Precautions:
Complexity may overwhelm beginners; careful parameter tuning is recommended.
Too many active filters can reduce signal frequency, potentially missing opportunities.
Divergence and skew thresholds require calibration to each market’s volatility regime.
CONCLUSION
The VWolf – Equinox stands out as one of the most comprehensive strategies in the VWolf library, combining skew deviation with a wide array of technical filters. Its layered confirmation system reduces noise and improves reliability across volatile markets. While powerful, its effectiveness depends on thoughtful parameter selection and disciplined risk management. This makes it a strong candidate for experienced traders seeking depth, adaptability, and dynamic trade control.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Basic EdgeOVERVIEW
VWolf - Basic Edge is a clean and accessible crossover strategy built on the core principle of moving average convergence. Designed for simplicity and ease of use, it allows traders to select from multiple types of moving averages—including EMA, SMA, HULL, and DEMA—and defines entry points strictly based on the crossover of two user-defined MAs.
This strategy is ideal for traders seeking a minimal, no-frills trend-following system with flexible exit conditions. Upon crossover in the selected direction (e.g., fast MA crossing above slow MA for a long entry), the strategy opens a trade and then manages the exit based on the user’s chosen method:
Signal-Based Exit:Trades are closed on the opposite crossover signal (e.g., long is exited when the fast MA crosses below the slow MA).
Fixed SL/TP Exit:The trade is closed based on fixed Stop Loss and Take Profit levels.Both SL and TP values are customizable via the strategy’s input settings.Once either the TP or SL is reached, the position is exited.
Additional filters such as date ranges and session times are available for backtesting control, but no extra indicators are used—staying true to the “basic edge” philosophy. This strategy works well as a starting framework for beginners or as a reliable, lightweight system for experienced traders wanting clean, rule-based entries and exits.
RECOMMENDED FOR
- Beginner to intermediate traders who want a transparent and easy-to-follow system.
- Traders looking to understand or build upon classic moving average crossover logic.
- Users who want a customizable but uncluttered strategy framework.
🌍 Markets & Instruments:
Well-suited for liquid and trending markets, including:Major forex pairs
Stock indices
Commodities (e.g., gold, oil)
Cryptocurrencies with stable trends (e.g., BTC, ETH)
⏱ Recommended Timeframes:
Performs best on higher intraday or swing trading timeframes, such as:15m, 1h, 4h, and 1D
Avoid low-timeframe noise (e.g., 1m, 3m) unless paired with strict filters or volatility controls.
FOR MORE INFORMATION VISIT vwolftrading.com
ATR ZigZag BreakoutATR ZigZag Breakout
This strategy uses my ATR ZigZag indicator (powered by the ZigZagCore library) to scalp breakouts at volatility-filtered highs and lows.
Everyone knows stops cluster around clear swing highs and lows. Breakout traders often pile in there, too. These levels are predictable areas where aggressive orders hit the tape. The idea here is simple:
→ Let ATR ZigZag define clean, volatility-filtered pivots
→ Arm a stop market order at those pivots
→ Join the breakout when the crowd hits the level
The key to greater success in this simple strategy lies in the ZigZag. Because the pivots are filtered by ATR instead of fixed bar counts or fractals, the levels tend to be more meaningful and less noisy.
This approach is especially suited for intraday trading on volatile instruments (e.g., NQ, GC, liquid crypto pairs).
How It Works
1. Pivot detection
The ATR ZigZag uses an ATR-based threshold to confirm swing highs and lows. Only when price has moved far enough in the opposite direction does a pivot become “official.”
2. Candidate breakout level
When a new swing direction is detected and the most recent high/low has not yet been broken in the current leg, the strategy arms a stop market order at that pivot.
• Long candidate → most recent swing high
• Short candidate → most recent swing low
These “candidate trades” are shown as dotted lines.
3. Entry, SL, and TP
If price breaks through the level, the stop order is filled and a bracket is placed:
• Stop loss = ATR × SL multiplier
• Take profit = SL distance × RR multiplier
Once a level has traded, it is not reused in the same swing leg.
4. Cancel & rotate
If the market reverses and forms a new swing in the opposite direction before the level is hit, the pending order is cancelled and a new candidate is considered in the new direction.
Additional Features
• Optional session filter for backtesting specific trading hours
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Damians UJ Strategy20 Pip Candle Strategy (No Engulfing)
Trades taken at 6pm direcrtly after candle close
Inputs allow you to reorganize retracement pips, SL, TP, 5PM candle amount.
S&D Light+ Enhanced# S&D Light+ Enhanced - Supply & Demand Zone Trading Strategy
## 📊 Overview
**S&D Light+ Enhanced** is an advanced Supply and Demand zone identification and trading strategy that combines institutional order flow concepts with smart money techniques. This strategy automatically identifies high-probability reversal zones based on Break of Structure (BOS), momentum analysis, and first retest principles.
## 🎯 Key Features
### Smart Zone Detection
- **Automatic Supply & Demand Zone Identification** - Detects institutional zones where price is likely to react
- **Multi-Candle Momentum Analysis** - Validates zones with configurable momentum requirements
- **Break of Structure (BOS) Confirmation** - Ensures zones are created only after significant structure breaks
- **Quality Filters** - Minimum zone size and ATR-based filtering to eliminate weak zones
### Advanced Zone Management
- **Customizable Zone Display** - Choose between Geometric or Volume-Weighted midlines
- **First Retest Logic** - Option to trade only the first touch of each zone for higher probability setups
- **Zone Capacity Control** - Maintains a clean chart by limiting stored zones per type
- **Visual Zone Status** - Automatically marks consumed zones with faded midlines
### Risk Management
- **Dynamic Stop Loss** - Positioned beyond zone boundaries with adjustable buffer
- **Risk-Reward Ratio Control** - Customizable R:R for consistent risk management
- **Entry Spacing** - Minimum bars between signals prevents overtrading
- **Position Sizing** - Built-in percentage of equity allocation
## 🔧 How It Works
### Zone Creation Logic
**Supply Zones (Selling Pressure):**
1. Strong momentum downward movement (configurable body-to-range ratio)
2. Identified bullish base candle (where institutions accumulated shorts)
3. Break of Structure downward (price breaks below recent swing low)
4. Zone created at the base candle's high/low range
**Demand Zones (Buying Pressure):**
1. Strong momentum upward movement
2. Identified bearish base candle (where institutions accumulated longs)
3. Break of Structure upward (price breaks above recent swing high)
4. Zone created at the base candle's high/low range
### Entry Conditions
**Long Entry:**
- Price retests a demand zone (touches top of zone)
- Rejection confirmed (close above zone)
- Zone hasn't been used (if "first retest only" enabled)
- Minimum bars since last entry respected
**Short Entry:**
- Price retests a supply zone (touches bottom of zone)
- Rejection confirmed (close below zone)
- Zone hasn't been used (if "first retest only" enabled)
- Minimum bars since last entry respected
## ⚙️ Customizable Parameters
### Display Settings
- **Show Zones** - Toggle zone visualization on/off
- **Max Stored Zones** - Control number of active zones (1-50 per type)
- **Color Customization** - Adjust supply/demand colors and transparency
### Zone Quality Filters
- **Momentum Body Fraction** - Minimum body size for momentum candles (0.1-0.9)
- **Min Momentum Candles** - Number of consecutive momentum candles required (1-5)
- **Big Candle Body Fraction** - Alternative single-candle momentum threshold (0.5-0.95)
- **Min Zone Size %** - Minimum zone height as percentage of price (0.01-5.0%)
### BOS Configuration
- **Swing Length** - Lookback period for structure identification (3-20)
- **ATR Length** - Period for volatility measurement (1-50)
- **BOS Required Break** - ATR multiplier for valid structure break (0.1-3.0)
### Midline Options
- **None** - No midline displayed
- **Geometric** - Simple average of zone top/bottom
- **CenterVolume** - Volume-weighted center based on highest volume bar in window
### Risk Management
- **SL Buffer %** - Additional space beyond zone boundary (0-5%)
- **Take Profit RR** - Risk-reward ratio for target placement (0.5-10x)
### Entry Rules
- **Only 1st Retest per Zone** - Trade zones only once for higher quality
- **Min Bars Between Entries** - Prevent overtrading (1-20 bars)
## 📈 Recommended Settings
### Conservative (Lower Frequency, Higher Quality)
```
Momentum Body Fraction: 0.30
Min Momentum Candles: 2-3
BOS Required Break: 0.8-1.0
Min Zone Size: 0.15-0.20%
Only 1st Retest: Enabled
```
### Balanced (Default)
```
Momentum Body Fraction: 0.28
Min Momentum Candles: 2
BOS Required Break: 0.7
Min Zone Size: 0.12%
Only 1st Retest: Enabled
```
### Aggressive (Higher Frequency, More Signals)
```
Momentum Body Fraction: 0.20-0.25
Min Momentum Candles: 1-2
BOS Required Break: 0.4-0.5
Min Zone Size: 0.08-0.10%
Only 1st Retest: Disabled
```
## 🎨 Visual Elements
- **Red Boxes** - Supply zones (potential selling areas)
- **Green Boxes** - Demand zones (potential buying areas)
- **Dotted Midlines** - Center of each zone (fades when zone is used)
- **Debug Triangles** - Shows when zone creation conditions are met
- Red triangle down = Supply zone created
- Green triangle up = Demand zone created
## 📊 Best Practices
1. **Use on Higher Timeframes** - 1H, 4H, and Daily charts work best for institutional zones
2. **Combine with Trend** - Trade zones in direction of overall market structure
3. **Wait for Confirmation** - Don't enter immediately at zone touch; wait for rejection
4. **Adjust for Market Volatility** - Increase BOS multiplier in choppy markets
5. **Monitor Zone Quality** - Fresh zones typically have higher success rates
6. **Backtest Your Settings** - Optimize parameters for your specific market and timeframe
## ⚠️ Risk Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Always:
- Use proper position sizing
- Set appropriate stop losses
- Test thoroughly before live trading
- Consider market conditions and overall trend
- Never risk more than you can afford to lose
## 🔍 Data Window Information
The strategy provides real-time metrics visible in the data window:
- Supply Zones Count
- Demand Zones Count
- ATR Value
- Momentum Signals (Up/Down)
- BOS Signals (Up/Down)
## 📝 Version History
**v1.0 - Enhanced Edition**
- Improved BOS detection logic
- Extended base candle search range
- Added comprehensive input validation
- Enhanced visual feedback system
- Robust array bounds checking
- Debug signals for troubleshooting
## 💡 Tips for Optimization
- **Trending Markets**: Lower momentum requirements, tighter BOS filters
- **Ranging Markets**: Increase zone size minimum, enable first retest only
- **Volatile Assets**: Increase ATR multiplier and SL buffer
- **Lower Timeframes**: Reduce swing length, increase min bars between entries
- **Higher Timeframes**: Increase swing length, relax momentum requirements
---
**Created with focus on institutional order flow, smart money concepts, and practical risk management.**
*Happy Trading! 📈*
AI ALGO [Ganesh]Core Strategy Components\
1. EMA (Exponential Moving Average) SystemThe strategy uses three EMAs to identify trend direction:
EMA 48 (longer-term trend)
EMA 2 (short-term momentum)
EMA 21 (medium-term trend)
How it works:
Bullish trend: When price is above EMA 21 (green cloud)
Bearish trend: When price is below EMA 21 (red cloud)
EMA Cloud: The area between EMA 2 and EMA 48/21 provides visual trend confirmation
Optional higher timeframe (HTF) analysis for multi-timeframe confirmation
2. DEMA ATR (Double EMA + Average True Range)
This is a dynamic support/resistance indicator that adapts to volatility:Components:
DEMA (Double Exponential Moving Average): Smooths price action with less lag
ATR Bands: Creates upper and lower bands based on volatility (ATR × 1.7 factor)
Signal Generation:
Green line: Uptrend (DEMA ATR rising)
Red line: Downtrend (DEMA ATR falling)
Acts as a trailing stop-loss level that adjusts with market volatility
3. Smart Trail System (Fibonacci-Based)
An advanced trailing stop system using modified true range calculations:Key Features:
Calculates true range using Wilder's smoothing method
Creates Fibonacci retracement levels (61.8%, 78.6%, 88.6%) from the trail line
Adaptive stop-loss: Adjusts based on ATR factor (4.2) and smoothing (4)
Trend Detection:
Bullish: Price > Trailing line (blue zones)
Bearish: Price < Trailing line (red zones)
The Fibonacci zones show potential support/resistance areas
4. ZigZag Indicator Identifies significant swing highs and lows:
Length parameter: 13 (sensitivity control)
Labels: Higher Highs (HH), Lower Lows (LL), etc.
Helps identify trend reversals and key pivot points
5. Support & Resistance Levels
Strength-based S/R: Identifies horizontal support/resistance zones
Zone width: Adjustable percentage-based zones
High/Low zones: Marks significant price levels
Trading LogicEntry Conditions (Implied)The strategy likely enters trades when:Long Entry:
Price crosses above DEMA ATR (green)
Price is above EMA 21 (bullish EMA cloud)
Smart Trail confirms uptrend
Price bounces from Fibonacci support levels
Short Entry:
Price crosses below DEMA ATR (red)
Price is below EMA 21 (bearish EMA cloud)
Smart Trail confirms downtrend
Price rejects from Fibonacci resistance levels
Exit/Stop-Loss Strategy
Trailing stops: Using Smart Trail Fibonacci levels
Dynamic stops: DEMA ATR line acts as a moving stop-loss
Risk management: Position sizing at 50% of equity per trade
Dashboard Features1. Weekly Performance Table
Tracks trades per day of the week
Shows win/loss statistics
Calculates win rate percentage
2. Monthly Performance Table
Monthly P&L breakdown
Yearly performance summary
Color-coded returns (green = profit, red = loss)
Strategy Parameters
Initial Capital: $5,000
Commission: 0.02% per trade
Position Size: 50% of equity
Pyramiding: Disabled (no adding to positions)
Calculation: On bar close (not tick-by-tick)
Visual Elements
EMA clouds: Green (bullish) / Red (bearish)
DEMA ATR line: Dynamic support/resistance
Smart Trail zones: Fibonacci-based colored bands
ZigZag lines: Swing high/low connections
S/R zones: Horizontal support/resistance areas
Strategy Philosophy
This is a trend-following strategy with dynamic risk management that:
Uses multiple timeframes for confirmation
Adapts to volatility through ATR-based indicators
Provides clear visual cues for trend direction
Includes comprehensive performance tracking
Combines momentum (EMAs) with volatility (ATR) for robust signals
The strategy works best in trending markets and uses the Fibonacci trail system to maximize profits while protecting against reversals with adaptive stop-losses.
🔥 Ribas Waves Strategy PRO++📝 Strategy Description: Ribas Waves Strategy PRO++
The Ribas Waves Strategy PRO++ is a powerful trading system based on the identification of Wolfe Waves patterns, designed to capture high-probability reversal points with precise entries and smart risk management.
This advanced version is fully customizable, allowing traders to adapt entry confirmations, trend filters, and risk/reward ratios to their preferred trading style and market conditions.
⚙️ Key Features:
✅ Automatic detection of both Bullish and Bearish Wolfe Wave patterns
✅ Entry confirmation options:
No confirmation (pure Wolfe pattern)
Directional candle (bullish or bearish close)
Engulfing candle (bullish/bearish)
Inside bar + breakout
✅ Optional EMA trend filter
✅ Configurable take profit via:
Risk multiple (R-multiple: e.g., 3x risk)
Percentage of risk (e.g., 300% of stop-loss distance)
✅ Toggle to show or hide wave labels and structure on chart
✅ Entry cooldown to prevent overlapping trades
✅ Visual display of current strategy position: 📈 Long / 📉 Short / ⛔️ Flat
📌 How to Use:
Set pivot sensitivity based on the asset's volatility (default: 7)
Choose your preferred entry confirmation method
Enable or disable the EMA trend filter
Adjust your take profit logic (R-multiple or % of risk)
Run a backtest or use live alerts for execution
💡 Author Recommendations:
Best suited for volatile markets such as crypto, indices, and forex.
For more trades, disable confirmation filters or use “Directional Candle” mode.
Use higher timeframes or combine with volume/context filters for increased accuracy.
Regularly backtest different settings to optimize your edge on specific assets.
MACD Zero-Line Strategy (Long Only)Strategy to Open order when Mac-D Signal Cross up 0, Sell when it cross down 0
Vegas Pro_邀請版Vegas Pro
Access Requirements To access this script, please follow these steps:
Register on MEXC using the link below.
Deposit at least 200 USDT.
Provide your email address to receive access.
Sign up link: www.mexc.com
Katik EMA BUY SELLThis strategy uses EMA 9, EMA 20, and EMA 200 to generate Buy and Sell signals.
BUY Conditions
EMA 9 crosses above EMA 20
Stoploss: Recent Swing Low
Target: EMA 9 touches or crosses EMA 200
SELL Conditions
EMA 9 crosses below EMA 20
Stoploss: Recent Swing High
Target: EMA 9 touches or crosses EMA 200
Features
Automatic Long & Short entries
Dynamic swing-based stoploss
Clear EMA plots with line width 3
Works on all timeframes
Profitable Pair Correlation Divergence Scanner v6This strategy identifies divergence opportunities between two correlated assets using a combination of Z-Score spread analysis, trend confirmation, RSI & MACD momentum checks, correlation filters, and ATR-based stop-loss/take-profit management. It’s optimized for positive P&L and realistic trade execution.
Key Features:
Pair Divergence Detection:
Measures deviation between returns of two assets and identifies overbought/oversold spread conditions using Z-Score.
Trend Alignment:
Trades only in the direction of the primary asset’s trend using a fast EMA vs slow EMA filter.
Momentum Confirmation:
Confirms trades with RSI and MACD to reduce false signals.
Correlation Filter:
Ensures the pair is strongly correlated before taking trades, avoiding noisy signals.
Risk Management:
Dynamic ATR-based stop-loss and take-profit ensures proper reward-to-risk ratio.
Exit Conditions:
Automatically closes positions when Z-Score normalizes, or ATR-based exits are hit.
How It Works:
Calculate Returns:
Computes returns for both assets over the selected timeframe.
Z-Score Spread:
Calculates the spread between returns and normalizes it using moving average and standard deviation.
Trend Filter:
Only takes long trades if the fast EMA is above the slow EMA, and short trades if the fast EMA is below the slow EMA.
Momentum Confirmation:
Confirms trade direction with RSI (>50 for longs, <50 for shorts) and MACD alignment.
Correlation Check:
Ensures the pair’s recent correlation is strong enough to validate divergence signals.
Trade Execution:
Opens positions when Z-Score crosses thresholds and all conditions align. Positions close when Z-Score normalizes or ATR-based SL/TP is hit.
Plot Explanation:
Z-Score: Blue line shows divergence magnitude.
Entry Levels: Red/Green lines mark long/short thresholds.
Exit Zone: Gray lines show normalization zone.
EMA Trend Lines: Purple (fast), Orange (slow) for trend alignment.
Correlation: Teal overlay shows current correlation strength.
Usage Tips:
Use highly correlated pairs for best results (e.g., EURUSD/GBPUSD).
Run on higher timeframe charts (1h or 4h) to reduce noise.
Adjust ATR multiplier based on volatility to avoid premature stops.
Combine with alerts for automated notifications or webhook execution.
Conclusion:
The Profitable Pair Correlation Divergence Scanner v6 is designed for traders who want systematic, low-risk, positive P&L trading opportunities with minimal manual monitoring. By combining trend alignment, momentum confirmation, correlation filters, and dynamic exits, it reduces false signals and improves execution reliability.
Run it on TradingView and watch how it captures divergence opportunities while maintaining positive P&L across trades.
specific breakout FiFTOStrategy Description: 10:14 Breakout Only
Overview This is a time-based intraday trading strategy designed to capture momentum bursts that occur specifically after the 10:14 AM candle closes. It operates on the logic that if price breaks the high of this specific candle within a short window, a trend continuation is likely.
Core Logic & Rules
The Setup Candle (10:14 AM)
The strategy waits specifically for the minute candle at 10:14 to complete.
Once this candle closes, the strategy records its High price.
Defining the Entry Level
It calculates a trigger price by taking the 10:14 High and adding a user-defined Buffer (e.g., +1 point).
Formula: Entry Level = 10:14 High + Buffer
The "Active Window" (Expiry)
The trade setup does not remain open all day. It has a strict time limit.
By default, the setup is valid from 10:15 to 10:20.
If the price does not break the Entry Level by the expiry time (default 10:20), the setup is cancelled and no trade is taken for the day.
Entry Trigger
If a candle closes above the Entry Level while the window is open, a Long (Buy) position is opened immediately.
Exits (Risk Management)
Stop Loss: A fixed number of points below the entry price.
Target: A fixed number of points above the entry price.
Visual & Automation Features
Visual Boxes: Upon entry, the strategy draws a "Long Position" style visual on the chart. A green box highlights the profit zone, and a red box highlights the loss zone. These boxes extend automatically until the trade closes.
JSON Alerts: The strategy is pre-configured to send data-rich alerts for automation (e.g., Telegram bots).
Entry Alert: Includes Symbol, Entry Price, SL, and TP.
Exit Alerts: Specific messages for "Target Hit" or "SL Hit".
Summary of User Inputs
Entry Buffer: Extra points added to the high to filter false breaks.
Fixed Stop Loss: Risk per trade in points.
Fixed Target: Reward per trade in points.
Expiry Minute: The minute (10:xx) at which the setup becomes invalid if not triggered.
BTC Dynamic Volatility Trend Backtested from 2017 to present, this strategy has delivered a staggering 7100%+ cumulative return. It doesn't just track the market; it dominates it. By capturing major trends and strictly limiting drawdowns, it has significantly outperformed the standard 'Buy & Hold' BTC strategy, proving its ability to generate massive alpha across multiple bull and bear cycles.
自 2017 年至今，本策略实现了惊人的 7100%+ 累计收益率。它不仅仅是跟随市场，更是超越了市场。通过精准捕捉主升浪并严格控制回撤，该策略在穿越多轮牛熊周期后，大幅度跑赢了比特币‘买入持有’（Buy & Hold）的基准收益，展现了极致的阿尔法（Alpha）捕捉能力。"
Introduction ：Simplicity is the ultimate sophistication. This strategy is designed specifically for Bitcoin (BTC), capturing its unique characteristics: high volatility, frequent fakeouts, and massive trend persistence. It abandons complex indicators in favor of a robust logic: "Follow the Trend, Filter the Noise, Let Profits Run."
Core Logic
Trend Filter (Fibonacci EMA 144): We use the 144-period Exponential Moving Average as the baseline. Longs are only taken above this line, and shorts only below. This keeps you on the right side of the major trend.
Volatility Breakout (Donchian Channel 20): Entries are triggered only when price breaks the 20-day high (for longs) or low (for shorts). This confirms momentum and avoids trading in chop.
Dynamic Risk Management (ATR Chandelier Exit):
Instead of fixed % stops, we use Average True Range (ATR) to calculate stop losses.
The Ratchet Mechanism: The stop loss moves up with the price but never moves down (for longs). This locks in profits automatically as the trend develops and exits immediately when volatility turns against you.
Why Use This Strategy?
Zero Repainting: All signals are confirmed.
No Curve Fitting: Uses classic parameters (144, 20) that have worked for decades.
Mental Peace: The strategy handles the exit. You don't need to guess where to sell. It holds through minor corrections and exits only when the trend truly reverses.
Settings
Leverage %: Adjust your position size based on equity (default 100% = 1x).
Timeframe: Recommended for 4H charts.
中文版 (Chinese Version)
简介 ：大道至简。本策略专为 比特币 (BTC) 设计，针对其高波动、假突破多但趋势爆发力强的特点，摒弃了复杂的过度拟合指标，回归交易本质：“顺大势，滤噪音，截断亏损，让利润奔跑”。
核心逻辑
趋势过滤器 (斐波那契 EMA 144)： 使用 144 周期指数移动平均线作为多空分水岭。价格在均线之上只做多，之下只做空。这能有效过滤掉大部分震荡市的噪音。
波动率突破 (唐奇安通道 20)： 只有当价格突破过去 20 根 K 线的最高价（做多）或最低价（做空）时才进场。这确保了我们只在趋势确立的瞬间入场。
动态风控 (ATR 吊灯止损)：
拒绝固定点数止损，使用 ATR（平均真实波幅）根据市场热度动态计算安全距离。
棘轮机制： 止损线会跟随价格上涨而上移，但绝不会下移（做多时）。这实现了自动化的“利润锁定”，既能扛住正常的波动回调，又能在大势反转时果断离场。
策略优势
绝不重绘： 所有信号均为收盘确认或实时触价。
拒绝拟合： 使用经过数十年市场验证的经典参数组合。
心态管理： 策略全自动管理出场。你不需要纠结何时止盈，它会帮你吃到完整的鱼身，直到趋势结束。
使用建议
资金管理： 可通过参数调整仓位占比（默认 100% = 1倍杠杆）。
推荐周期： 建议在4小时 图表上运行效果最佳。
Gold Seasonal Long-Term StrategyBased on the rigid cycle of physical gold demand.
It capitalizes on the strong buying momentum driven by India's Diwali in November, the Western holiday season in December, and the Chinese New Year in January/February to execute a long-term hold.
KNNstrategyKNN is an advanced gold-trading strategy built on a set of refined, confidential patterns extracted from thousands of recurring price behaviors. It identifies hidden reversal and breakout zones using a unique candle-movement signature optimized for fast timeframes. The strategy filters market noise and reveals high-precision entry points overlooked by traditional methods. KNN delivers a powerful edge in the highly volatile gold market through unmatched pattern accuracy and smart validation logic.
US Market Long Horizon Momentum Summary in one paragraph
US Market Long Horizon Momentum is a trend following strategy for US index ETFs and futures built around a single eighteen month time series momentum measure. It helps you stay long during persistent bull regimes and step aside or flip short when long term momentum turns negative.
Scope and intent
• Markets. Large cap US equity indices, liquid US index ETFs, index futures
• Timeframes. 4h/ Daily charts
• Default demo used in the publication. SPY on 4h timeframe chart
• Purpose. Provide a minimal long bias index timing model that can reduce deep drawdowns and capture major cycles without parameter mining
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. One unscaled multiple month log return of an external benchmark symbol drives all entries and exits, with optional volatility targeting as a single risk control switch.
• Failure mode addressed. Fully passive buy and hold ignores the sign of long horizon momentum and can sit through multi year drawdowns. This script offers a way to step down risk in prolonged negative momentum without chasing short term noise.
• Testability. All parameters are visible in Inputs and the momentum series is plotted so users can verify every regime change in the Tester and on price history.
• Portable yardstick. The log return over a fixed window is a unit that can be applied to any liquid symbol with daily data.
Method overview in plain language
The method looks at how far the benchmark symbol has moved in log return terms over an eighteen month window in our example. If that long horizon return is positive the strategy allows a long stance on the traded symbol. If it is negative and shorts are enabled the strategy can flip short, otherwise it goes flat. There is an optional realised volatility estimate on the traded symbol that can scale position size toward a target annual volatility, but in the default configuration the model uses unit leverage and only the sign of momentum matters.
Base measures
Return basis. The core yardstick is the natural log of close divided by the close eighteen months ago on the benchmark symbol. Daily log returns of the traded symbol feed the realised volatility estimate when volatility targeting is enabled.
Components
• Component one Momentum eighteen months. Log of benchmark close divided by its close mom_lookback bars ago. Its sign defines the trend regime. No extra smoothing is applied beyond the long window itself.
• Component two Realised volatility optional. Standard deviation of daily log returns on the traded symbol over sixty three days. Annualised by the square root of 252. Used only when volatility targeting is enabled.
• Optional component Volatility targeting. Converts target annual volatility and realised volatility into a leverage factor clipped by a maximum leverage setting.
Fusion rule
The model uses a simple gate. First compute the sign of eighteen month log momentum on the benchmark symbol. Optionally compute leverage from volatility. The sign decides whether the strategy wants to be long, short, or flat. Leverage only rescales position size when enabled and does not change direction.
Signal rule
• Long suggestion. When eighteen month log momentum on the benchmark symbol is greater than zero, the strategy wants to be long.
• Short suggestion. When that log momentum is less than zero and shorts are allowed, the strategy wants to be short. If shorts are disabled it stays flat instead.
• Wait state. When the log momentum is exactly zero or history is not long enough the strategy stays flat.
• In position. In practice the strategy sits IN LONG while the sign stays positive and flips to IN SHORT or flat only when the sign changes.
Inputs with guidance
Setup
• Momentum Lookback (months). Controls the horizon of the log return on the benchmark symbol. Typical range 6 to 24 months. Raising it makes the model slower and more selective. Lowering it makes it more reactive and sensitive to medium term noise.
• Symbol. External symbol used for the momentum calculation, SPY by default. Changing it lets you time other indices or run signals from a benchmark while trading a correlated instrument.
Logic
• Allow Shorts. When true the strategy will open short positions during negative momentum regimes. When false it will stay flat whenever momentum is negative. Practical setting is tied to whether you use a margin account or an ETF that supports shorting.
Internal risk parameters (not exposed as inputs in this version) are:
• Target Vol (annual). Target annual volatility for volatility targeting, default 0.2.
• Vol Lookback (days). Window for realised volatility, default 63 trading days.
• Max Leverage. Cap on leverage when volatility targeting is enabled, default 2.
Usage recipes
Swing continuation
• Signal timeframe. Use the daily chart.
• Benchmark symbol. Leave at SPY for US equity index exposure.
• Momentum lookback. Eighteen months as a default, with twelve months as an alternative preset for a faster swing bias.
Properties visible in this publication
• Initial capital. 100000
• Base currency. USD
• Default order size method. 5% of the total capital in this example
• Pyramiding. 0
• Commission. 0.03 percent
• Slippage. 3 ticks
• Process orders on close. On
• Bar magnifier. Off
• Recalculate after order is filled. Off
• Calc on every tick. Off
• All request.security calls use lookahead = barmerge.lookahead_off
Realism and responsible publication
The strategy is for education and research only. It does not claim any guaranteed edge or future performance. All results in Strategy Tester are hypothetical and depend on the data vendor, costs, and slippage assumptions. Intrabar motion is not modeled inside daily bars so extreme moves and gaps can lead to fills that differ from live trading. The logic is built for standard candles and should not be used on synthetic chart types for execution decisions.
Performance is sensitive to regime structure in the US equity market, which may change over time. The strategy does not protect against single day crash risk inside bars and does not model gap risk explicitly. Past behavior of SPY and the momentum effect does not guarantee future persistence.
Honest limitations and failure modes
• Long sideways regimes with small net change over eighteen months can lead to whipsaw around the zero line.
• Very sharp V shaped reversals after deep declines will often be missed because the model waits for momentum to turn positive again.
• The sample size in a full SPY history is small because regime changes are infrequent, so any test must be interpreted as indicative rather than statistically precise.
• The model is highly dependent on the chosen lookback. Users should test nearby values and validate that behavior is qualitatively stable.
Legal
Education and research only. Not investment advice. You are responsible for your own decisions. Always test on historical data and in simulation with realistic costs before any live use.
