Rocket Scalper 1.0 Bullish onlyThis is a premium, invite-only strategy designed for high-frequency, bullish micro-scalping. It is engineered to identify and exploit fast continuation moves during peak market activity, prioritizing high win-rate results over high individual R:R targets.
🛡️ The Strategy's Proprietary Edge
The Rocket Scalper 1.0 operates based on three independent, proprietary logic blocks that must align before a trade is considered:
Adaptive Trend Filter: Uses a unique dual-period moving average system to ensure entries are only generated in alignment with the prevailing short-term trend direction.
Market Momentum Validator: A proprietary momentum reading that confirms institutional interest and sufficient price velocity, filtering out slow, choppy movements.
Volume Confirmation Engine: Requires a validated surge in trading volume to confirm the strength and sustainability of the breakout, significantly reducing false signals.
Trade Execution Window: To maximize efficiency and signal quality, trading is strictly limited to the most liquid hours: US Session (8:00 AM - 4:00 PM ET / 12:00 - 20:00 UTC).
💰 Risk Management & Performance Focus
This strategy is built for capital preservation and compounding:
Dynamic Loss Control: Employs an Adaptive ATR Stop Loss that automatically adjusts to current market volatility, ensuring tight, controlled losses. You can fine-tune its tightness using the Vol. SL Multiplier setting.
Dual-Phase Profit System: Positions are split, with the first half securing a 1:1 R target quickly, and the second half utilizing a custom Trailing Stop system to capture extended runs.
Breakeven Security: An optional feature automatically moves the stop to a minimum profit level after a small favorable move, effectively making the trade risk-free.
⚙️ Key Customization Parameters
The strategy includes key adjustable settings for optimization without revealing the core logic: Trend Sensitivity, Vol. SL Multiplier, Trail Multiplier, and Confirmation Threshold.
🔒 Access & Membership Information (Crucial for Stan Store)
This is a premium, invite-only script. Access is granted only upon successful membership application.
To begin the access process and for all membership details, please review the information located in the Author's Signature directly below this description.
Access permissions are granted manually to your TradingView account after verification of your membership.
⚠️ Mandatory Risk Disclaimer
RISK DISCLOSURE: This strategy is provided for educational and informational use only. It does not constitute financial or trading advice, and is not a recommendation to trade any financial instrument. Trading carries a high risk of loss. Consult a professional financial advisor. Past performance is not an indicator of future results. By using this script, you accept full responsibility for all trading decisions.
การวิเคราะห์แนวโน้ม
MAC's V6 finalBreakout retest strategy
Works best on a NQ 1 hour chart
Also works on other futures charts
Adjust the initial capital to 100000
and the margin requirement percent to 0
Rebound Sigma Pro - StrategyOverview
Rebound Sigma Pro is a mean-reversion indicator that detects statistically oversold conditions in trending markets.
It helps traders identify potential short-term rebounds based on momentum exhaustion and volatility-adjusted entry zones.
Concept
The indicator combines two quantitative components:
Short-term momentum to detect short-term exhaustion
Trend filter to ensure setups align with the long-term direction
When a stock in an uptrend becomes temporarily oversold, a limit-entry signal is plotted.
The trade is then tracked until short-term conditions normalize or a time-based exit occurs.
Visual Signals
Green Triangle: Suggests placing a limit order for the next session
Green Circle: Confirms entry was filled
Red Triangle: Signals an exit for the next session’s open
Orange Background: Pending order
Green Background: Position active
Red Background: Exit phase
Yellow Line: Entry reference price
User Inputs
Limit Entry (% below previous close) – Default 1 %
Use Limit Entry – Switch between limit or market entries
Enable Time Exit – Optional holding-period constraint
Maximum Holding Days
All other internal parameters (momentum length, filters) are pre-configured.
Alerts
Limit Order Signal: New setup detected
Entry Confirmed: Order filled
Exit Signal: Exit expected next day
Usage
Designed for liquid equities and ETFs
Works best in confirmed uptrends
Backtesting encouraged to adapt parameters per symbol and timeframe
Notes
Not an automated strategy; manual order execution required
Past behavior does not imply future performance
Always apply sound position sizing and risk management
Disclaimer
This indicator is provided for educational and analytical purposes only.
It does not constitute financial advice or performance assurance.
Traders Club RSI, EMA Strategy 🔻 Arun Gold 3H Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Arun R5.41🔻 Arun Gold 3H Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
Adaptive Chikou Strategy - Level 1This strategy is based on the Ichimoku cloud system and the power of delaying the signal. I changed how the averages are calculated to better detect the range areas.
The strategy uses this concept to determine the market regime, whether the price is below or above its delayed signal, and acts accordingly:
Bull (green) – when the price is above the average of the highs, delayed, the strategy favors long entries.
Bear (red) – when the price is below the average of the lows delayed, the strategy favors short entries.
Range (brown) – when the percent rank is in between those 2 conditions, we detect range, and no trades are initiated.
The transition between these regimes depends mainly on 4 key parameters.
The first parameter controls the lookback period for the highest and lowest functions.
The second controls how much we delay the signal of these 2 functions.
The third adjusts how much range is detected in bull conditions; it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The fourth parameter is similar to the third, but for bear conditions. The bigger it is, the less bear and the more range conditions are detected.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when the price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Percent Rank Strategy - Level 1This strategy is based on the Percent Rank math, a statistical measure that evaluates how the current price compares to its historical prices over a specified lookback period.
In simple terms, Percent Rank tells you the percentile position of the current price within a recent window, for example, a value of 80% means the price is higher than 80% of the previous prices in that period, while 20% means it’s lower than 80% of them.
The strategy uses this concept to determine the market regime, whether price is high, low, or neutral relative to its recent range, and acts accordingly:
Bull (green) – when the price percent rank is usually above 50% the price is normally high, and the strategy favors long entries.
Bear (red) – when the price percent rank is usually below 50% the price is normally low, and the strategy favors short entries.
Range (brown) – when the percent rank is in between those 2 conditions, we detect range, and no trades are initiated.
The transition between these regimes depends mainly on 3 key parameters.
The first parameter controls the maximum lookback period for the percent rank array and so the maximum cycle length.
The second controls how much range is detected in bull conditions; it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The third parameter is similar to the second, but for bear conditions. The smaller it is, the less bear and the more range conditions are detected.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when the price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Correlation Cycle Strategy - Level 1This strategy is based on John Ehlers idea of the correlation cycle, and that markets often oscillate. They move up and down in cycles, though not perfectly sinusoidal, they can be approximated by a sinusoidal wave. This script measures the strength of the correlation between price and a range of ideal sine wave components of different periods. By doing this, we estimate which cycle length the market is most currently following and from that, we find the phase to learn in which part of the cycle we are in.
Bull (green) – when price is at the bottom of the sinusoidal going to the top (positive phases), the strategy favors long entries.
Bear (red) – when price is at the top of the sinusoidal going down to the bottom (negative phases), the strategy favors short entries.
Range (brown) – when the phase is in the transition zones we detect range conditions and no trades are initiated.
The transition between these regimes depends mainly on 3 key parameters.
The first parameter controls the maximum lookback period for correlation detection and so the maximum cycle length.
The second controls how much range is detected in bull conditions, it changes the transition from bull to range conditions. The bigger it is, the less bull and the more range.
The third parameter is similar to the second, but for bear conditions. The bigger it is, the less bear and the more range conditions are detected
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
When multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Alts Strategy 3.1Alts Strategy 3.1 is a long-term adaptive DCA system designed for spot investment management and portfolio scaling.
It automatically accumulates and averages spot positions during market corrections, using layered Fibonacci supports and adaptive take-profit logic to optimize long-term entry efficiency.
This strategy is built for investors and swing traders who prefer gradual accumulation over frequent trading.
Instead of short-term entries and exits, it focuses on adding to positions at statistically favorable levels and reducing exposure near major resistance zones.
Its adaptive nature allows users to simulate real investment behavior — buying lower, holding through volatility, and exiting strategically once recovery targets are reached.
The core of the strategy is based on dynamic Fibonacci-derived support zones that react to historical price structures.
When price approaches these zones, Alts Strategy 3.1 initiates or averages entries following cooldown rules and bear-cycle filters.
The built-in bear-market filter recognizes historical cycle patterns (based on Bitcoin halving timelines) and temporarily blocks new entries during high-risk macro phases.
Once the market exits a bear regime, the system reactivates, continuing long-term accumulation.
The adaptive take-profit module adjusts target multipliers depending on recovery depth — distinguishing between “normal recovery” and “deep recovery” cycles.
This approach helps maximize profit during sustainable uptrends while keeping long-term exposure moderate.
All logic is handled internally without repainting, allowing accurate and consistent backtesting.
Alts Strategy 3.1 is intended mainly for long-term investors, portfolio rebalancers, and spot market participants who use DCA (Dollar-Cost Averaging) logic to accumulate assets over time.
It can be used to test different investment horizons, cooldown periods, and adaptive TP configurations directly in the Strategy Tester.
Because it operates on real price action without leverage logic, it is ideal for simulating spot accumulation strategies and macro investment cycles.
This tool is provided for educational and analytical purposes only.
It is not financial advice or a trading signal system.
Anthony's trading strategyWait for signal to print and a continuation candle to enter trade. If no continuation candle, disregard signal.
Market Structure Strategy - Level 1This strategy identifies peaks and valleys (local tops and bottoms) in price to construct a dynamic market structure, labeling Higher Highs (HH), Lower Lows (LL), Higher Lows (HL), and Lower Highs (LH). From this evolving structure, the script determines the dominant market regime, which can be:
Bull (green) – when price forms new highs and maintains a bullish structure, the strategy favors long entries.
Bear (red) – when price forms new lows and confirms a bearish structure, the strategy favors short entries.
Range (brown) – when price fluctuates between recent highs and lows, suggesting sideways conditions where no trades are initiated.
The transition between these regimes depends mainly on four key parameters.
The first parameter controls the lookback period into the past to find the top or bottom.
The second controls the period of the looback to the right of the top or bottom.
The “Entry Margin” parameter determines how much ranging behavior the model will detect before switching regimes.
The 4 parameter select the source to construct the top and bottom, the close the wick, etc.
The user can configure the strategy to run long-only, short-only, or both directions, depending on the market or preference. In addition to the core regime logic, the strategy includes several risk and trade management controls that are featured in all my strategies.
Four oscillators are also integrated into the logic to detect short-term overbought and oversold conditions. These help the strategy avoid entering or exiting a trade when price has already extended too far in one direction, improving timing and potentially reducing false entries and exits. When overbought or oversold are detected, a red or green dot appears on the chart.
The script is designed to be flexible across different assets and timeframes. However, to achieve consistent results, it is important to optimize parameters carefully. A recommended workflow is as follows:
Disable the walk-forward option during the optimization phase.
Optimize the first main parameter while keeping others fixed.
Once a satisfactory value is found, move to the second parameter.
Continue the process for subsequent parameters.
Optionally, repeat the full sequence once more to refine the results.
Finally, activate walk-forward analysis and check the out-of-sample results.
This strategy is published as invite-only with hidden source code. Access may be granted upon request for research or evaluation purposes. It is part of a broader collection of technical analysis strategies I have developed, which focus on regime detection and adaptive trading systems.
There are five levels of strategy complexity and performance in my collection. This script represents a Level 1 strategy, designed as a solid foundation and introduction to the framework. More advanced levels progressively add greater complexity, adaptability, and robustness.
Finally, when multiple strategies are combined under this same framework, the results become more robust and stable. In particular, combining my suite of technical analysis strategies with my macro strategies and alternative data strategies, such as onchain for cryptocurrencies. It creates a multi-layered system that adapts across regimes, timeframes, and market conditions.
Tight Entry Trend Engine Strategy═══════════════════════════════════════
TIGHT ENTRY TREND ENGINE
═══════════════════════════════════════
A breakout-based trend-following system designed to capture explosive
moves by entering at precise resistance/support breakouts with minimal
entry risk and massive profit potential.
⚠️ LOW WIN RATE, HIGH REWARD SYSTEM ⚠️
This is NOT a high win-rate strategy. Expect 25-35% winners, but
when it hits, winners are typically 10X+ larger than losers.
═══════════════════════════════════════
🎯 WHAT THIS SYSTEM DOES
═══════════════════════════════════════
The Tight Entry Trend Engine identifies powerful breakout opportunities
by detecting when price breaks through established trendlines with
confirmation from higher timeframe trends:
1. DYNAMIC TRENDLINE DETECTION (3 BANKS)
• Automatically draws support and resistance trendlines
• 3 separate "banks" capture short-term, medium-term, and long-term levels
• Each bank has configurable parameters (required pivot touch count,
angle limits, lengths)
2. BREAKOUT ENTRY TIMING
• Enters LONG when price breaks ABOVE resistance trendlines
• Enters SHORT when price breaks BELOW support trendlines
• Entry Alert occurs at the exact moment of breakout = "tight entry"
• Stop-loss placed just below/above the broken trendline (configurable)
3. HIGHER TIMEFRAME TREND FILTER
• Uses Hull Moving Average (HMA) on higher timeframe for trend following
• Auto-adjusts HTF based on your chart timeframe
• Optional filters prevent entries against major trend
• Optional "overextension" filter avoids buying parabolic moves
4. VOLATILITY-ADAPTIVE RISK MANAGEMENT
• Stop-loss calculated using Average True Range (ATR)
• Tighter stops = better R:R
• Profit targets adjust dynamically with volatility
• Breakeven stop moves automatically when in profit
• Extended profit targets when far from HTF trend
═══════════════════════════════════════
📊 HOW IT WORKS (METHODOLOGY)
═══════════════════════════════════════
STEP 1: TRENDLINE FORMATION
The system continuously scans for pivot highs and pivot lows to
construct trendlines. You control:
BANK 1 (Short-Term):
- Pivot Length: How many bars to look back for swing points
- Min Touches: How many pivots needed to form a line (default: 3)
- Max Length: How far back lines can reach (default: 180 bars)
- Angle Limits: Maximum steepness allowed for valid trendlines
- Tolerance: How close pivots must align to form horizontal lines
BANK 2 (Medium-Term):
- Slightly longer pivot periods for more significant levels
- Captures medium-term trend structure
- Default Max Length: 200 bars
BANK 3 (Long-Term):
- Focuses on major support/resistance zones
- Often uses horizontal levels (angled lines disabled by default)
- Default Max Length: 300 bars
The system draws RESISTANCE lines (red) above price and SUPPORT
lines (green) below price. These adapt in real-time as new pivots form.
STEP 2: BREAKOUT DETECTION
LONG SIGNALS:
- Price closes above a resistance trendline
- Higher timeframe trend is up (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
SHORT SIGNALS:
- Price closes below a support trendline
- Higher timeframe trend is down (optional filter)
- Price not overextended from HTF trend (optional filter)
- No position currently open
The "tight" aspect: Because you're entering right at the trendline
break, your stop-loss can be placed very close (just below the
broken resistance for longs), creating exceptional risk/reward ratios.
STEP 3: POSITION SIZING
Choose between:
- Fixed $ Risk Per Trade: Risk same dollar amount every trade
- % Risk Per Trade: Risk percentage of current equity
Position size automatically calculated based on:
- Your risk amount
- Distance to stop-loss (ATR-based)
- Works with stocks, futures, crypto (auto-adjusts for contract multipliers)
STEP 4: EXIT MANAGEMENT
Multiple exit methods working together:
- PROFIT TARGET: Exits when profit reaches 100x your risk
- EXTENDED PROFIT: Earlier exit (80R) when very far from HTF trend
- STOP LOSS: Fixed ATR-based stop below entry
- HTF TREND EXIT: Exits when price crosses below HTF trend with profit
- BREAKEVEN PULLBACK: Exits if profit drops below 0.6R after reaching breakeven
- PARTIAL PROFITS: Optional - take partial profits at specified R-multiple
═══════════════════════════════════════
🔧 KEY COMPONENTS EXPLAINED
═══════════════════════════════════════
HULL MOVING AVERAGE (HMA)
A smoothed moving average that reduces lag compared to traditional
MAs. The system uses HMA on a higher timeframe to determine the
dominant trend direction. You can choose:
- Auto HTF: System picks appropriate HTF based on your chart timeframe
- Manual HTF: You specify the higher timeframe
AVERAGE TRUE RANGE (ATR)
Measures current market volatility. Used for:
- Stop-loss distance (tighter when volatility low)
- Profit targets (larger when volatility high)
- Position sizing (smaller positions in volatile conditions)
- Breakeven trigger distance
TRENDLINE ANGLE FILTERING
Each trendline bank has angle limits to ensure quality:
- Resistance lines: Max downward/upward slope allowed
- Support lines: Max downward/upward slope allowed
- Angles automatically adjust based on current volatility
- Prevents overly steep/unreliable trendlines
SENSITIVITY CONTROL
One master slider adjusts multiple parameters:
- Trendline detection sensitivity
- HTF MA length
- Exit timing
- Auto-adjusts for daily+ timeframes (60% increase)
═══════════════════════════════════════
⚙️ WHAT YOU SEE ON YOUR CHART
═══════════════════════════════════════
TRENDLINES:
✓ Red resistance lines above price
✓ Green support lines below price
✓ Orange broken lines (past breakouts)
✓ Lines extend to show current levels
HTF TREND:
✓ Thick colored line showing higher timeframe trend
✓ Color gradient: Red (bearish) → Orange → Yellow → Green (bullish)
✓ 250-bar smoothed curve for visual clarity
ENTRY/EXIT SIGNALS:
✓ Small green dot below bar = Long entry
✓ Small red dot above bar = Short entry
✓ Small red dot above = Long exit
✓ Small black dot below = Short exit
OPTIONAL DETAILED LABELS:
✓ Bank number that triggered entry (Bank 1, 2, or 3)
✓ Exit reason (Profit Target, Stop Loss, HTF Exit, etc.)
✓ Partial profit notifications
POSITION TRACKING:
✓ Yellow dashed line at entry price (extends right)
✓ Green/red fill showing current profit/loss zone
✓ Lime arrows at top = Currently in long position
✓ Red arrows at bottom = Currently in short position
✓ Gray background = No position (flat)
STATS TABLE (Top Right):
✓ Current position (LONG/SHORT/FLAT)
✓ Risk per trade ($ or %)
✓ Entry price
✓ Unrealized P/L in dollars
✓ P/L in R-multiples (how many R's profit/loss)
✓ Average winner/loser R ($ mode) OR CAGR (% mode)
═══════════════════════════════════════
📈 OPTIMAL USAGE
═══════════════════════════════════════
BEST ASSETS:
- NASDAQ:QQQ on 1-hour (reg) chart ⭐ (PRIMARY OPTIMIZATION)
- Strong trending stocks: NVDA, AAPL, TSLA, MSFT, GOOGL, AMZN
- High volatility tech stocks
- Crypto: BTC, ETH
- Any liquid asset with clear trends and momentum (GOLD)
AVOID:
- Low volatility stocks
- Ranging/choppy markets
- Penny stocks or illiquid assets
- Assets without clear directional movement
BEST TIMEFRAMES:
- PRIMARY: 1-hour charts (optimal for QQQ)
- ALSO EXCELLENT: 2H, 4H, 8H
- WORKS: 15min, 30min (only momentum leaders, more noise)
- WORKS WITH ADJUSTMENTS: 1D, 2D (decrease trendline pivot lengths)
═══════════════════════════════════════
📊 BACKTEST RESULTS (QQQ 1H (Reg hours), 1999-2024)
═══════════════════════════════════════
The system showed on NASDAQ:QQQ 1-hour timeframe (regular hours):
- Total Return: 1,100,000%+ over 24 years
- Total Trades: 500+
- Win Rate: ~20-24% (LOW - this is by design!)
- Average Winner: 8-15% gain
- Average Loser: 2-4% loss
- Win/Loss Ratio: 10:1 (winners much bigger than losers)
- Profit Factor: 3+
- Max Drawdown: 45-50%
- Risk per trade: 3% of capital
KEY INSIGHT: This is a LOW WIN RATE, HIGH REWARD system. You will
lose more trades than you win, but the few winners are so large
they more than compensate for many small losses.
IMPORTANT: These are backtested results using optimal parameters
on historical data. Real trading results will vary based on:
- Your execution and timing
- Slippage and commissions
- Your emotional discipline
- Market conditions during your trading period
═══════════════════════════════════════
🎓 WHO IS THIS FOR?
═══════════════════════════════════════
IDEAL FOR:
✓ Swing traders comfortable holding winners for longer period
✓ Part-time traders (1H = check 2-3x per day)
✓ Traders seeking exceptional risk/reward ratios
✓ Those comfortable with low win rates if winners are huge
✓ Technical analysis enthusiasts
✓ Breakout traders
✓ Trend followers
═══════════════════════════════════════
🚀 GETTING STARTED - STEP BY STEP
═══════════════════════════════════════
STEP 1: APPLY TO YOUR CHART
- Search "Tight Entry Trend Engine" in indicators
- Click to apply to your chart
- Trendlines and HTF line will appear immediately
STEP 2: CHOOSE YOUR SETTINGS
For BEGINNERS - Use These Settings First:
1. Trade Direction & Filters:
• ENABLE LONGS: ✓ ON
• ENABLE SHORTS: ✗ OFF (start with longs only)
• Sensitivity: 1.0 (default)
• HTF Trend Entry Filter: ✓ ON (safer entries)
• Block Entries When Overextended: ✓ ON (avoid parabolic tops)
2. Position Sizing & Risk:
• Position Sizing: "Per Risk"
• RISK Type: "$ Per Trade"
• Risk Amount: $200 (or 1-3% of your account)
3. Visual Settings:
• Show Support Lines: ✗ OFF (unless trading shorts)
• Show Detailed Entry/Exit Labels: ✓ ON
• Show Stats Table: ✓ ON
• Show Entry Line & P/L Fill: ✓ ON
4. Leave everything else at DEFAULT for now
STEP 3: UNDERSTAND WHAT YOU SEE
When trendlines appear:
- RED lines above = Resistance (watch for price breaking UP through these)
- GREEN lines below = Support (watch for price breaking DOWN)
- When price breaks a red line = Potential LONG entry
- When price breaks a green line = Potential SHORT entry
The HTF trend line (thick colored):
- Green/lime = Strong uptrend (favorable for longs)
- Red = Strong downtrend (favorable for shorts if enabled)
- Orange/yellow = Transitioning
STEP 4: OBSERVE SIGNALS
- Small GREEN dot below bar = System entered LONG
- Small RED dot above bar = System exited LONG
- Check the label to see which "Bank" triggered (Bank 1, 2, or 3)
- Watch the yellow entry line and colored fill show your P/L
STEP 5: PAPER TRADE FIRST
- Use TradingView's paper trading feature
- Watch how signals perform on YOUR chosen asset
- Understand the win rate will be LOW (20-35%)
- Verify that winners are indeed much larger than losers
- Test for at least 20-30 signals before going live
STEP 6: OPTIMIZE FOR YOUR ASSET (OPTIONAL)
If default settings aren't working well:
For FASTER signals (more trades):
- Reduce Pivot Length 1 to 3-4
- Reduce Max Length 1 to 120-150
- Increase Sensitivity to 1.2-1.5
For SLOWER signals (higher quality):
- Increase Pivot Length 1 to 7-10
- Increase Max Length 1 to 250+
- Decrease Sensitivity to 0.7-0.9
For DAILY timeframes:
- Increase all Pivot Lengths by 30-50%
- Increase all Max Lengths significantly
- Sensitivity: 0.6-0.8
═══════════════════════════════════════
⚙️ ADVANCED SETTINGS EXPLAINED
═══════════════════════════════════════
TRENDLINE BANK SETTINGS:
Each bank (1, 2, 3) has these parameters:
- Min Touches: Minimum pivots to form a line
- Lower (2) = More lines, earlier detection
- Higher (4+) = Fewer lines, higher quality
- Pivot Length: Lookback for swing points
- Lower (3-5) = Reacts to recent price action
- Higher (10+) = Only major swing points
- Max Length: How old a trendline can be
- Shorter (100-150) = Only recent lines
- Longer (300+) = Include historical levels
- Tolerance: Alignment strictness for horizontal lines
- Lower (3.0-3.5) = Very strict horizontal
- Higher (4.5+) = More forgiving alignment
- Allow Angled Lines: Enable diagonal trendlines
- ON = Catches sloped support/resistance
- OFF = Only horizontal levels
- Angle Limits: Maximum steepness allowed
- Lower (1-2) = Only gentle slopes
- Higher (4-6) = Accept steeper angles
- Automatically adjusts for volatility
ATR MULTIPLIERS:
- STOP LOSS ATR (0.6): Distance to stop-loss
- Lower (0.4-0.5) = Tighter stops, stopped out more
- Higher (0.8-1.0) = Wider stops, more room
- PROFIT TARGET ATR (100): Main profit target
- This is 100x your risk = 10,000% R:R
- Lower (50-80) = Take profits sooner
- Higher (120+) = Let winners run longer
- BREAKEVEN ATR (40): When to move stop to breakeven
- Lower (20-30) = Protect profits earlier
- Higher (60+) = Give more room before protecting
HIGHER TIMEFRAME:
- Auto HTF: Automatically selects appropriate HTF
- 5min chart → uses 2H
- 15-30min → uses 6H
- 1-4H → uses 2D
- Daily → uses 4D
- HTF MA Length (300): HMA period for trend
- Lower (150-250) = More responsive
- Higher (400-500) = Smoother, less whipsaw
- HTF Trend Following Exit: Exits when crossing HTF
- ON = Additional exit method
- OFF = Rely only on profit targets/stops
- HTF Trend Entry Filter: Only trade with HTF trend
- ON = Safer, fewer signals
- OFF = More aggressive, more signals
- Block Entries When Overextended: Prevents chasing
- ON = Avoids parabolic tops/bottoms
- OFF = Enter all breakouts regardless
═══════════════════════════════════════
💡 TRADING PHILOSOPHY & EXPECTATIONS
═══════════════════════════════════════
This system is built on one core principle:
"ACCEPT SMALL, FREQUENT LOSSES TO CAPTURE RARE, MASSIVE WINS"
What this means:
- You WILL lose 65%-75% of your trades
- Most losses will be small (1-2R)
- Some winners hit 80R+
- Over time, math works in your favour
Ajay R5.41🔻 Ajay Gold 3H Power Indicator 🔻
Precision-Based Smart Sell System for Gold (XAU/USD)
💡 Overview
This indicator is specifically designed for Gold (XAU/USD) and delivers best results on the 3-Hour Timeframe (3H TF).
It is a Smart Money Logic-based Sell Confirmation System, combining institutional structure and candle behavior to generate highly accurate bearish signals.
⚙️ Technical Foundation
The indicator uses multiple advanced confirmations:
📉 EMA Trend Filter → Confirms downtrend
💪 RSI Overbought Rejection → Momentum reversal signal
📊 MACD Bearish Cross → Confirms trend strength
🕯️ Bearish Candle Structure → Price action validation
When all conditions align, a clear 🔻 Sell Signal is plotted on the chart.
💎 Hidden Feature
This indicator includes a hidden feature that activates only when the correct market structure forms.
It helps reduce false signals and increases accuracy without being visible on the chart — fully automated internal logic.
📆 Recommended Settings
Symbol: XAU/USD (Gold)
Timeframe: 3-Hour (3H)
Market: Forex / Commodity
Mode: Sell-Only Confirmation Indicator
Performance: Best precision and consistency on 3H TF
📈 How to Use
Select XAU/USD on chart and set 3H timeframe.
Add the indicator to the chart.
Wait for the 🔻 Sell Signal and confirm the market structure after candle close.
Take entry according to your risk management.
⚠️ Disclaimer
This indicator is for educational and analytical purposes only.
No system is 100% accurate — always backtest and demo trade before using in real trading.
💬 Credits
Developed by Ajay Sahu (India)
Based on Institutional & Smart Money Logic
Best results on 3H TF
Hidden Algorithm for XAU/USD traders
AMF PG Strategy v2.3 The AMF PG Strategy (Praetorian Guard) is an advanced trading system designed to seamlessly adapt to market conditions. Its unique structure balances precise entries with intelligent protection, giving traders confidence in both trending and volatility environments.
Key points include:
Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts for clearer long- and short-term opportunities and generates a robust tracking line.
Praetorian Guard – A built-in protective shield that activates in extreme conditions and helps stabilize performance when markets become turbulent.
Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments.
Clarity – Clear visual signals and color-coded monitoring for instant decision-making.
This strategy is designed for traders who want more than just entries and exits; it offers a command center for disciplined, adaptable, and resilient trading.
Disclaimer:
It should be noted that no strategy is guaranteed. This strategy does not provide buy-sell-hold advice. Responsibility rests with the user.
Version 2.3: Bugs overlooked in Version 2 have been corrected and improvements have been made.
Batman Strategy v1
1. Overview & Core Concept
The "Batman Strategy V1" is a comprehensive trend-following and pyramid-trading framework designed for multiple asset classes. Its core concept is to identify strong, established trends and systematically enter positions in stages (pyramiding) to maximize gains during sustained market movements.
This strategy is built on a proprietary scoring system that synthesizes multiple market dimensions—including stage analysis, relative strength, and volume dynamics—into clear, actionable signals. It is not a simple indicator mashup; it's a complete system with defined entry, exit, and risk management protocols.
2. Key Features
Proprietary Trend Scoring: The strategy grades market conditions from 'A' (strong bull trend) to 'Z' (strong bear trend) using a unique combination of ADX and RSI calculations, providing a nuanced view of trend maturity and strength.
Advanced Relative Strength Analysis: Automatically compares the asset's performance against a relevant market index (e.g., NIFTY for Indian stocks, NDX for US stocks, or a total crypto market cap for crypto) to ensure it is a market leader.
Heikin-Ashi Based Logic: Utilizes Heikin-Ashi candles for its core calculations to filter out market noise and provide smoother trend signals.
Multi-Tranche Pyramiding: The strategy is designed to enter a position with an initial tranche and add up to four subsequent positions if the trend continues favorably, based on a proprietary breakout logic (`ha_close > breakout`).
Dynamic & Multi-Option Exits: Offers three distinct, user-selectable trailing stop mechanisms for exits: SuperTrend, V-Stop, and Chandelier Exit. This allows traders to tailor the exit logic to their risk tolerance and the asset's volatility. The data source for these exits can also be switched between the standard chart and Heikin-Ashi candles.
Integrated Risk Management: Implements a sophisticated stop-loss system that adjusts based on the number of open trades, aiming to move to break-even after the third tranche and protecting capital.
3. How to Use This Strategy
Configuration: In the script settings, first set your desired backtesting date range. Then, configure the "Entry," "Tranching," and "Exit" parameters to suit your trading style. The most important choice is the "Exit Indicator," as this will define how the strategy closes trades.
Interpretation: When applied to a chart, the strategy will plot trend score labels ('A', 'B', 'C' for bullish; 'X', 'Y', 'Z' for bearish), color the background based on relative strength, and color the bars based on volume strength. Backtesting results, including all pyramided trades, will be visible in the "Strategy Tester" panel.
Alerts: The script includes built-in alert conditions for both bullish and bearish trend scores, which can be used to notify you of potential opportunities.
4. Backtesting & Performance
This is a strategy script, and its performance should be thoroughly evaluated in the Strategy Tester. As per TradingView rules, users should use realistic settings for initial capital, commission, and slippage. The default settings are a template; they should be adjusted to reflect the conditions of the market you are testing. Past performance is not indicative of future results.
5. Disclaimer
This strategy is a tool for market analysis and idea validation. It is not financial advice. All trading involves risk, and you should not risk more than you are prepared to lose. This is a closed-source, protected script; its internal calculations are proprietary.
TSI Base BTC 1D /tv! (www.tradingview.com)
# 🧠 TSI Base BTC 1D /tv
## Overview
**TSI Base BTC 1D /tv** is a **trend-following strategy** optimized for **Bitcoin on the 1D timeframe**, though it also performs strongly across other major cryptocurrencies.
It’s designed to identify major directional shifts while filtering out short-term noise, maintaining a balance between **clarity, consistency, and risk control**. The system focuses on staying aligned with large market trends — not chasing every fluctuation — which makes it particularly suited for traders seeking structured, high-integrity signals.
---
## Backtesting & Performance
This strategy has been tested extensively across multiple market cycles. The chosen backtest range — **from 2018 to the present** — is deliberate, as it captures both a full **bear market and bull market phase**, offering a statistically representative view of long-term performance and risk behavior.
We also recommend testing the strategy **from 2023 onward**, covering the ongoing bull run, to evaluate how it adapts to renewed momentum and volatility expansion.
Across both periods, TSI Base BTC 1D /tv demonstrates **consistent profitability**, **contained drawdowns**, and a **disciplined number of trades**, often outperforming a simple buy-and-hold benchmark.
Although primarily designed for **1D charts**, the system can also be applied to shorter timeframes while maintaining its trend-based integrity.
---
## Risk Management Inputs
The strategy includes optional parameters allowing traders to fine-tune risk and reward dynamics while preserving the same core logic:
- **Enable Stop Loss (%)** → activates a protective stop loss. You can freely adjust this percentage; however, using a **6 % Stop Loss** (as shown below) has proven to **increase overall profitability** while keeping the **maximum equity drawdown** close to **11.48 %**, compared to over 12 % without it.
📈 *Example backtest with 6 % Stop Loss enabled (2018 – 2025):*
*(Image below illustrates total P&L, drawdown, and profitable trade ratio.)*
! (<>)
- **Enable Take Profit (%)** → sets a percentage target where profits are automatically secured once reached.
- **Fixed Stop-Loss / Take-Profit Price** → allows absolute price levels (enter “0” to disable).
- **Enable Trailing Stop (%)** → locks in profits by following price movement from the last peak.
> These inputs are optional and should be used experimentally. Each trader can adapt them to their own risk tolerance and market conditions.
---
## Automation
Given its non-repainting design, **automation is highly recommended** for consistent execution.
The strategy can be connected to external automation systems such as **Signum**, which has been tested and confirmed to operate seamlessly.
*(Disclosure: we are not affiliated with Signum or any automation provider. Mentions are purely illustrative and for educational purposes.)*
---
## Trading Philosophy
TSI Base BTC 1D /tv aims to **capture the essence of macro trends** while avoiding emotional over-trading.
It keeps traders positioned during periods of strength and sidelines them during uncertainty, offering a disciplined, data-driven approach to following momentum.
---
## Key Characteristics
- ✅ **No Repainting** — signals confirmed on candle close.
- ✅ **Trend-Based Logic** — trades align with macro directional bias.
- ✅ **Volatility-Adaptive** — dynamic envelopes respond to market expansion and contraction.
- ✅ **Backtest-Proven Stability** — consistent across multiple cycles.
- ✅ **Automation-Ready** — compatible with external trade-execution platforms.
---
⚠️ **Disclaimer:**
This strategy is provided solely for **educational and research purposes**. It does **not constitute financial advice**.
Users are responsible for their own configurations, including Stop Loss, Take Profit, and Trailing Stop settings.
While examples show that enabling a **6 % Stop Loss** can improve historical results and reduce drawdown, performance may vary across assets and timeframes.
Always backtest thoroughly and use demo environments before applying live capital.
Twisted Forex's Doji + Area StrategyTitle
Twisted Forex’s Doji + Area Strategy
Description
What this strategy does
This strategy looks for doji candles forming inside or near supply/demand areas . Areas are built from swing pivots and sized with ATR, then tracked for retests (“confirmations”). When a doji prints close to an area and quality checks pass, the strategy places a trade with the stop beyond the doji and a configurable R:R target.
How areas (zones) are built
• Swings are detected with a user-set pivot length.
• Each swing spawns a horizontal area centered at the pivot price with half-height = zoneHalfATR × ATR .
• Duplicates are de-duplicated by center distance (ATR-scaled).
• Areas fade when broken beyond a buffer or after an optional age (expiry).
• Retests are recorded when price touches and then bounces away from the area; repeated reactions increase the zone’s “strength”.
Signal logic (summary)
Doji detection: strict or loose body criteria with optional minimum wick fractions and ATR-scaled minimum range.
Proximity: price must be inside/near a supply or demand area (proxATR × ATR).
Side resolution: overlap is resolved by (a) which side price penetrates more, (b) fast/slow EMA trend, or (c) nearest distance. Optional “previous candle flip” can bias long after a bearish candle and short after a bullish one.
Optional 1-bar confirmation: the bar after the doji must close away from the area by confirmATR × ATR .
Quality filter (Off/Soft/Strict): four checks—(i) wick rejection past the edge, (ii) doji closes in an edge “band” of the area, (iii) fresh touch (cooldown), (iv) approach impulse over a short lookback. In Strict , thresholds auto-tighten.
Orders & exits
• Long: stop below doji low minus buffer; Short: above doji high plus buffer.
• Target = rrMultiple × risk distance .
• Pyramiding is off by default.
Position sizing
You can size from the script or from Strategy Properties:
• Script-driven (default): set Position sizing = “Risk % of equity” and choose riskPercent (e.g., 1.0%). The script applies safe floors/rounding (FX micro-lots by default) so quantity never rounds to zero.
• Properties-driven : toggle Use TV Properties → Order size ON, then pick “Percent of equity” in Properties (e.g., 1%). The header includes safe defaults so trades still place.
Key inputs to explore
• Zone building : pivotLen, zoneHalfATR, minDepartureATR, expiryBars, breakATR, leftBars, dedupeATR.
• Doji & proximity : strictDoji, dojiBodyFrac, minWickFrac, minRangeATR, proxATR, minBarsBetween.
• Overlap resolution : usePenetration, useTrend (EMA 21/55), “previous candle flip”, needNextBarConf & confirmATR.
• Quality : qualityMode (Off/Soft/Strict), minQualPass/kStrict, wickPenATR, edgeBandFrac, approachLookback, approachMinATR, freshTouchBars.
• Zone strength gating : minStrengthSoft / minStrengthStrict.
• HTF confluence (optional) : useHTFTrend (HTF EMA 34/89) and/or useHTFZoneProx (HTF swing bands).
Tips to make it cleaner / higher quality
• Turn needNextBarConf ON and use confirmATR = 0.10–0.15 .
• Increase approachMinATR (e.g., 0.35–0.45) to require a stronger pre-touch impulse.
• Raise minStrengthSoft/Strict (e.g., 4–6) so only well-reacted zones can signal.
• Use signalsOnlyConfirmed ON if you prefer trades only from zones with retests (the script falls back gracefully when none exist yet).
• Nudge proxATR to 0.5–0.6 to demand tighter proximity to the level.
• Optional: enable useHTFTrend to filter counter-trend setups.
Default settings used in this publication
• Initial capital: 100,000 (illustrative).
• Slippage: 1 tick; Commission: 0% (you can raise commission if you prefer—spread is partly modeled by slippage).
• Sizing: Risk % of equity via inputs; riskPercent = 1.0% ; FX uses micro-lot floors by default.
• Quality: Off by default (Soft/Strict available).
• HTF trend gate: Off by default.
Backtesting notes
For a meaningful sample size, test on liquid symbols/timeframes that yield 100+ trades (e.g., majors on 5–15m over 1–2 years). Backtests are modelled and broker costs/spread vary—validate on your feed and forward-test.
How to read the chart
Shaded bands are supply (above) and demand (below). Brighter bands are the nearest K per side (visual aid). BUY/SELL labels mark entries; colored dots show entry/SL/TP levels. You can hide zones or unconfirmed zones for a cleaner view.
Disclaimer
This is educational material, not financial advice. Trading involves risk. Always test and size responsibly.
OneHolo-TGAPSNRTGAPSNR: Multi time frame - Trend Gap Stop And Reverse strategy/Study PnL. This script outlines a systematic approach to generating buy and sell signals by combining Fair Value Gaps (FVGs), specific market structures, and three different trend direction methods (Swing, Gravity, and FVG Inverse direction). The strategy incorporates multiple entry modes, such as Hyper Mode, Swiper Mode, and a Custom mode, allowing users to tailor signal conditions, alongside extensive logic for trade management, higher time frame analysis, and various visual indicators for plotting trend, pivots, and profit and loss information.
I. Core Trend Direction Consensus (The Three-Pillar System)
The primary method for determining market bias is a three-pillar consensus model, requiring all directional methods to align before the overall Trend Direction is established (up or down). This ensures high conviction for trend signals.
• Pillar 1: Swing Direction: Determines market direction based on classic price action, specifically checking for continuous higher highs and higher lows for an upward bias, or lower lows and lower highs for a downward bias.
• Pillar 2: Gravity Direction (Peak and Valley): This uses specific market structure pivots. Direction is set based on whether the close price successfully crosses the established recent Peak High (indicating upward momentum) or crosses under the recent Valley Low (indicating downward pressure).
• Pillar 3: FVG Inverse Direction: This relies on Fair Value Gaps (FVGs), defined as a gap between the current bar's price and the price two bars prior. Direction shifts occur when the Close price crosses the midpoint of the last relevant FVG. For instance, crossing above the midpoint of the last FVG Down signals a potential inverse long trade.
II. Flexible Signal Generation Modes
The strategy offers several pre-configured and highly detailed entry modes, plus a powerful Custom Mode:
• Session Open Range Break (ORB) Mode: Uses the high/low of the session's first bar to generate initial signals, then defaults to the Three-Pillar Trend Direction after the ORB session concludes.
• Swiper Mode: Designed to identify continuations, combining a confirmed Trend Direction with a Stop and Reverse signal (SnR) while actively avoiding confirmed pivot breaks.
• Hyper/Aggressive Modes: These modes use broad combinations of signals, allowing for earlier entry based on momentum and structural breaks (like PeakCrossLong, SnRtrapLong, or FVG signals).
• Custom Query Mode (The Seven-Slot Logic): This non-redundant system allows the user to define complex, tailored entry conditions by selecting any combination of 14 core patterns across seven distinct slots.
◦ AND/OR Combination: For each of the seven slots, the user determines if the chosen pattern must be met (AND component) or if it can serve as an alternative trigger (OR component).
◦ The final signal requires that all configured AND conditions are true and then integrates the result of the OR conditions, allowing for highly specific "hook queries" (e.g., "Condition A AND Condition B, OR Condition C").
III. Advanced PnL and Mobile App Diagnostics
A key proprietary element is the implementation of a dual PnL system and customized visualization features:
• Dual PnL Display (Strategy PnL vs. Study PnL): Users can choose to view either the native platform's strategy performance data or the script's internal, proprietary Study PnL. The Study PnL calculates profits/losses based strictly on the close price and tracks performance using Pine Script® arrays, providing a transparent, diagnostic view of performance independent of broker/platform simulation biases.
• Lower Panel Visualization: Both PnL types are displayed on the lower panel using detailed bar plots (style=plot.style_columns), which color according to profitability, and include labels that show current open profit and total net profit.
• Detailed Trade Labels: The script generates detailed, customizable labels on both the chart (above/below bars) and the lower PnL panel, providing historical PnL, number of trades, and real-time profit information for each entry or exit.
IV. Higher Time Frame (HTF) Context and Lookahead Prevention
The strategy integrates multi-time frame analysis using strict methodology to prevent lookahead bias:
• HTF Bias Filtering: When enabled, the strategy uses the position calculated on a user-defined higher time frame (HTF) as a mandatory filter. A long signal on the current chart is only executed if the HTF is also in a long position, and vice-versa.
• Lookahead Prevention: To maintain integrity, all HTF data requests use a mandatory lookback index (often ) to ensure the script only accesses confirmed data from the prior completed bar on the higher timeframe.
• HTF Visual Mode: The user can opt to display key structural elements—such as the Gravity Pivots and the Trend Direction blocks—as calculated on the HTF, overlaying this higher-level context onto the current chart for visual analysis.
The TGAPSNR: Multi time frame - Trend Gap Stop And Reverse strategy/Study PnL script, despite its complexity, intentionally excludes realistic considerations such as fees, slippage, and explicit risk management settings (like fixed stop-loss or take-profit rules) from its primary logic.
Here is an explanation of why these elements are omitted in the strategy's current implementation and why they must be applied by the user for real-world application, drawing on the context of the sources:
1. Absence of Realistic Fees, Commissions, and Slippage
The primary function of the TGAPSNR script is to execute intricate signal generation and diagnostic PnL calculation based on its three-pillar trend system and Custom Mode logic.
However, the strategy's backtesting results, particularly those displayed by the internal Study PnL feature, are based purely on price difference (e.g., (close - lse) * syminfo.pointvalue * IUnits).
• Strategy Result Requirements: TradingView explicitly states that strategies published publicly should strive to use realistic commission AND slippage when calculating backtesting results to avoid misleading traders.
• User Responsibility: Since the script currently focuses on signal integrity and uses a fixed contract size (IUnits = 1) without configurable commission/slippage inputs shown in the source, the user must manually configure these fees within the Pine Script® Strategy Tester settings (Properties tab) to ensure the strategy results are reflective of actual trading costs.
2. Omission of Built-in Risk Management (Stop-Loss and Take-Profit)
The TGAPSNR strategy's core focuses on entry signals and trend confirmation. Exits are primarily governed by:
• Reversal signals (BuyStop or SellStop).
• End-of-Day (EOD) session closures (EODStop).
• HTF bias opposition.
What is Missing: The script does not include explicit, hard-coded risk management parameters for traditional stop-loss (SL) or take-profit (TP) levels (e.g., risk percentage or ATR-based exits).
• Viable Risk: TradingView guidelines stipulate that strategies should generally risk sustainable amounts of equity, usually not exceeding 5-10% on a single trade, and trade size must be appropriate.
• User Application: To ensure the strategy operates within realistic risk boundaries, users must apply their own risk management rules. This includes:
◦ Implementing realistic stops and profit targets, which can be added via Pine Script® code or manually managed during live trading.
◦ Sizing trades to only risk sustainable amounts of equity. The current default unit size (IUnits = 1) is unrealistic for risk assessment unless the symbol is micro-sized.
3. Execution Quality (Fills)
The strategy is set to fill_orders_on_standard_ohlc = true and operates on confirmed bar closes (barstate.isconfirmed).
• Fill Assumption: This suggests the strategy primarily uses close price or the HTF close price (EntryPrice = HTFClose) for execution.
• Real-World Limitation: In volatile markets, obtaining a fill price equal to the close of the bar is rare. The user must be aware that the simulated fill price shown in backtesting may differ significantly from actual execution prices due to market action and chosen order type, reinforcing the importance of applying slippage settings.
In summary, while the script provides highly detailed and unique signal generation and internal PnL diagnostics, users must exercise caution and apply their own realistic parameters for fees, slippage, and explicit risk controls to prevent misleading performance results and ensure viable trading
Momentum Pro (Tuned v6) — 8/18 EMA • RVOL • PrevHigh • ADXMomentum strategy with signals (VWAP + 9/20 EMA alignment, MACD hist > 0, RSI 55–70, RVOL filter, ATR stop, 2R target
Golden StrategyTitle: XAUUSD (Gold) Smart Entry Strategy with Dynamic Scaling
Description:
This is a precision-based entry strategy for XAUUSD (Gold), optimized for lower timeframes like the 5-minute and 15-minute charts. It uses a custom logic engine to detect potential reversals and applies dynamic scaling (pyramiding) to build positions strategically based on price behavior.
🔍 Key Features:
✅ Smart entry logic for trend shifts
✅ Configurable position scaling up to 7 level
✅ Built-in capital efficiency for smaller accounts
✅ Backtest window control for historical testing
✅ Compact on-screen table for user guidance
Timeframes Recommended:
🔸 15-minute: Best balance of risk and consistency
🔸 5-minute: More frequent signals, slightly higher risk
⚠️ Important Disclaimer
This script is for educational and informational purposes only. It is not financial advice or a signal service. Trading carries risk, and past performance does not guarantee future results. Use at your own discretion and always manage risk appropriately.
Trend-Following & Breakout — Index Quant Strategy (NASDAQ)📈 Trend-Following & Breakout — Index Quant Strategy (NASDAQ & S&P 500)
Type: Invite-only strategy
Markets: NASDAQ 100 (NAS100 / US100 / NQ), S&P 500 (US500 / SPX), and other major equity indices.
🧠 Concept: Continuous trend model combining EWMAC (trend-following) and Donchian (breakout) signals, scaled by forecast strength and portfolio risk.
⚙️ Execution: Rebalances only on decision-bar closes, using hysteresis and a no-trade band to reduce churn.
📊 Default bias: Long-only — aligned with equity index drift.
🧩 How it works
• EWMAC Trend: Difference between fast and slow EMAs, normalized by an EWMA of absolute returns.
• Donchian Breakout: Distance beyond a 200-bar channel (Strict mode) or relative z-score position within it.
• Forecast combination: Weighted sum of trend and breakout points, clamped to ± capPoints.
• Hysteresis: Prevents quick sign flips near zero forecast.
• Risk scaling: Maps forecast strength to position size using equity × risk budget × ATR-based stop distance.
• Rebalance: Executes only if the required quantity change exceeds the Δqty threshold; can optionally block increases on Sundays (for CFDs).
⚙️ Default parameters
Deployed on NQ / US100 / NAS100 on Daily Timeframe
• Decision timeframe = 360 min (other options from 1 min to 1 week).
• Trend (EWMAC): Fast = 64, Slow = 256, Vol Norm = 32, Weight = 0.8.
• Breakout (Donchian): Length = 200, Mode = Strict, Weight = 0.2.
• Forecast scaling: ptsPerSigma = 1.0, capPoints = 10.
• Risk % per rebalance = 4 % of equity.
• ATR stop: ATR(14) × 1.0.
• No-trade band (Δqty) = 4 units.
• Hysteresis = 2 forecast points.
• Bias = Long-only (Neutral / Long-bias 50 % optional).
• Skip Sunday increases = false (default).
📋 Backtest properties (documented)
• Initial capital = 100 000 USD.
• Commission = 0.20 % per trade.
• Pyramiding = 10.
• Calc on every tick = false.
• Point value = 1 (for NAS100 CFD).
• No financing or slippage modeled.
• If using CFDs, account for overnight funding.
• On futures (NQ / ES), carry is implicit.
📊 Typical behaviour
• Many small scratches, a few large winners.
• Performs best during multi-week / multi-month trends.
• Underperforms in tight or volatile ranges.
• Average hold ≈ 30 – 90 days in historical tests.
💡 Risk and performance guide (illustrative)
Sharpe ≈ 1.25
Sortino ≈ 1.10 – 1.30
Max drawdown ≈ –18 % to –25 %
Annual volatility ≈ 24 – 28 %
CAGR ≈ 50 – 60 % (at 4 % risk)
Edge ratio ≈ 5 (MFE / MAE)
Historical backtests only — past performance does not guarantee future results.
🌍 Intended markets and timeframes
Optimized for NASDAQ 100 and S&P 500; also effective on similar indices (DAX, Dow Jones, FTSE).
Best on Daily or higher timeframes.
Aligns with long-term index drift — suitable for long-bias systematic trend portfolios.
⚠️ Limitations
• Backtests exclude CFD funding costs.
• Trend models will have losing streaks in range-bound markets.
• Designed for experienced traders seeking systematic exposure.
🔑 Requesting access
Send a private TradingView message to with the text:
“Request access to Trend-Following & Breakout — Index Quant Strategy.”
Access is granted only on explicit request.
For further information, see my TradingView Signature.
🆕 Release notes (v1.0)
• Initial release (360 min TF): EWMAC 64/256 + Donchian 200 Strict.
• Risk 4 %, ATR × 1.0, Long-only bias, hysteresis 2 pts, Δqty ≥ 4.
• Developed for NASDAQ 100 and S&P 500 indices.
• Implements continuous risk-scaled positioning and no-trade band logic.
🧾 Originality statement
This strategy is original work built entirely from TradingView built-ins (EMA, ATR, Highest, Lowest).
It does not reuse open-source invite-only code.
Any future reuse of open scripts will be done with explicit permission and credit.
