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.
Pesquisar nos scripts por "take profit"
SmartDCA by TradeAkademiSmartDCA is an advanced position-management strategy built to deliver consistent results even as market conditions shift. Its price-action–driven structure, intelligent DCA scaling model, and multiple entry options provide a powerful automation framework suitable for both beginners and professional traders. With flexible TP/DCA configurations and safety modules such as Smart Take Profit, Risk Reset Exit, and Fail Safe Stop, positions scale more efficiently, risks are managed proactively, and capital remains protected at every stage. SmartDCA is a fully customizable, modern trading engine that offers high adaptability across different assets and timeframes.
The strategy supports five entry methodologies:
ta_default – Opens positions on breakout confirmations based on the selected period’s local highs and lows.
ta_volatility – Uses the same breakout logic while filtering entries that would place the target level outside the system’s defined safety zone.
ta_safety – Extends the volatility model with an additional candle-quality filter, avoiding structurally weak entries and behaving more conservatively.
rsi_based – Generates entries when RSI drops below 30 or rises above 70.
ema_based – Opens positions based on directional shifts in the moving average.
SmartDCA is fully configurable: entry logic, DCA percentage and multiplier, take-profit (TP) settings, maximum DCA steps, order-size mode, and directional preferences can all be tailored to fit any asset, market condition, or timeframe .
Default parameters are optimized for the 30-minute chart.
The strategy also includes three optional protective mechanisms:
Smart Take Profit – Closes profitable trades early when price approaches the target within a configurable proximity, reducing exposure to potential reversal signals.
Risk Reset Exit – After a defined DCA step, the position is closed at breakeven once price returns to the average entry level.
Fail Safe Stop – If the maximum DCA step is reached and recovery fails to occur, the trade is closed at a controlled loss.
All protection modules can be enabled individually and configured to activate only after specific DCA levels, allowing SmartDCA to remain adaptive yet controlled under varying market dynamics.
RevertX by YCGH CapitalRevertX by YCGH Capital - Professional Bitcoin Trading Strategy
RevertX is a sophisticated mean-reversion trading system designed specifically for Bitcoin and cryptocurrency markets. Built on advanced statistical analysis, this strategy identifies extreme price deviations and capitalizes on market equilibrium forces.
Key Features:
🎯 Intelligent Entry System
Precision-based signal generation using statistical price analysis
Automated entry/exit execution with no manual intervention required
Works on multiple timeframes for flexibility
📊 Comprehensive Performance Tracking
Monthly Returns Table: Visual heat-map style table displaying performance month-by-month and year-by-year
Color-coded results (green for profitable months, red for losses)
Annual performance summaries for quick assessment
Full historical performance visualization
🛡️ Advanced Risk Management
Customizable Stop Loss (default 2%)
Take Profit targets (default 4%)
Trailing Stop Loss with activation threshold - locks in profits as the market moves in your favor
Adjustable trailing offset to protect gains while allowing room for continuation
⚙️ Professional-Grade Execution
Non-repainting signals - what you see in backtest is what you get in live trading
Orders processed on candle close for reliable execution
100% equity deployment for maximum capital efficiency
Built-in slippage and commission modeling (can be adjusted)
📈 Performance Visualization
Monthly returns displayed in an easy-to-read table format
Track your performance across years at a glance
Quickly identify strong and weak periods
Professional presentation suitable for sharing with investors
Perfect For:
Bitcoin traders seeking systematic, emotion-free trading
Those who prefer mean-reversion over trend-following
Traders wanting comprehensive performance analytics
Anyone seeking a proven statistical edge in crypto markets
RevertX removes emotion from trading decisions and provides complete transparency through detailed performance metrics. The strategy is fully backtested and ready for live deployment.
Ready to Trade Like a Pro?
RevertX is a premium strategy with limited availability.
Email brijamohanjha@gmail.com to request access and pricing.
TrendSight📌 TrendSight — The All-in-One Multi-Timeframe Trend Engine
Key Features & Logic
Multi-Timeframe Trend Confirmation:
Entries are filtered by confirming bullish/bearish alignment across three distinct Supertrend timeframes (e.g., 5-min, 15-min, 45-min, etc.), combined with an EMA and volatility filter, to ensure high-conviction trades that's a powerful combination! Designing the entire strategy around the 15-minute timeframe (M15) and focusing on high-volatility coins maximizes the strategy's effectiveness .
Guaranteed Single-Entry per Signal:
The strategy uses a powerful manual flag and counter system to ensure trades fire only once when a new signal begins. It absolutely prevents immediate re-entry if the signal remains true, waiting instead for the entire trend condition to reset to false.
Dynamic Trailing Stop Loss:
The Stop Loss is set to a moving Supertrend line (current_supertrend), ensuring tight risk management that trails the price as the trade moves into profit.Guaranteed Take Profit (4% Run-up): Uses a precise Limit Order via strategy.exit() to capture profits instantly at a 4% run-up. This ensures accurate profit capture, even on sudden spikes (wicks).
Automated Risk Management:
Position size is dynamically calculated based on a fixed risk percentage (default 2% of equity) relative to the distance to the trailing stop.
🔥 Core Components
1. Adaptive Multi-Timeframe SuperTrend Dashboard
The backbone of mTrendSight is a fully customizable SuperTrend system, enhanced with a multi-timeframe confirmation table displaying ST direction & value.
This compact “Trend Dashboard” provides instant clarity on higher-timeframe direction, trend strength, and market bias.
2. Dynamic Support & Resistance Channels
Automatically detects the strongest support/resistance zones using pivot clustering.
Key Features:
Clustered S/R Channels instead of thin lines
Adaptive width based on recent swings
Breakout markers (optional) for continuation signals
Helps identify structural zones, retest areas, and liquidity pockets
3. Multi-Timeframe Color-Coded EMAs
Plot up to three EMAs, each optionally pulled from a higher timeframe.
Benefits:
Instant visual trend alignment
Bullish/Bearish dynamic color shifts
Precision EMA value table for trade planning
Works perfectly with ST & RSI for multi-layer confirmation
4. Linear Regression Trend Channel
A statistically driven trend channel that measures the most probable path of price action.
Highlights:
Uses Pearson’s R to determine trend reliability
Provides a Confidence Level to judge whether trend slope is credible
Ideal for determining over-extension and mean-reversion zones
5. ATR Volatility Analyzer
A lightweight but powerful volatility classifier using ATR.
Features:
Detects High, Low, or Normal volatility
Clean table display
Helps filter entries during low-energy markets
Strengthens trend-following filters when volatility expands
6. RSI Momentum & Trend Classifier
A significantly improved RSI with multi-layer smoothing and structure-based classification.
Provides:
Bullish / Bearish / Neutral momentum states
Short-term momentum vs long-term RSI trend
Perfect for early trend shifts, pullback entries, and momentum confirmation
⚙️ How the Strategy Works (Execution Logic)
📌 Multi-Timeframe Supertrend + EMA + Volatility Confirmation
Entries are only triggered when:
Multiple Supertrend timeframes align (e.g., 5m + 15m + 45m)
EMA direction aligns with the trend
Volatility conditions (ATR filter) is not Low allow high-probability moves
This ensures strong directional confluence before every trade.
📌 Guaranteed Single-Entry Logic
The strategy uses a flag + counter system to ensure:
Only one entry is allowed per trend signal
Re-entries do not happen until the entire trend condition resets
The Strategy Tester remains clean, without duplicate overlapping trades
This eliminates revenge trades, repeated fills, and choppy overtrading.
📌 Dynamic Supertrend Trailing Stop
Stop Loss is anchored to current Supertrend value, creating:
Automatic trailing
Tight downside control
Protection against deep pullbacks
High responsiveness during volatility expansions
📌 Precision Take-Profit (4% Run-Up Capture)
A dedicated global exit block ensures:
Take Profit triggers exactly at 4% price run-up
Uses strategy.exit() with limit orders to catch spikes (wicks)
Works consistently on all timeframes & assets
📌 Automated Position Sizing (2% Risk Default)
Position size is dynamically calculated based on:
Account Equity
Distance to trailing stop
Configured risk %
This enforces proper risk management without manual adjustments.
📈 How to Interpret Results
Reliable Exits: All exits are globally managed, so stops and take profits trigger accurately on every bar.
Clean Trade History: Because of single-entry logic, backtests show one trade per valid signal.
Consistency: Multi-timeframe logic ensures only high-quality, structured trades.
The Oracle: Dip & Top Adaptive Sniper [Hakan Yorganci]█ OVERVIEW
The Oracle: Dip & Top Adaptive Sniper is a precision-focused trend trading strategy designed to solve the biggest problem in swing trading: Timing.
Most trend-following strategies chase price ("FOMO"), buying when the asset is already overextended. The Oracle takes a different approach. It adopts a "Sniper" mentality: it identifies a strong macro trend but patiently waits for a Mean Reversion (pullback) to execute an entry at a discounted price.
By combining the structural strength of Moving Averages (SMA 50/200) with the momentum precision of RSI and the volatility filtering of ADX, this script filters out noise and targets high-probability setups.
█ HOW IT WORKS
This strategy operates on a strictly algorithmic protocol known as "The Yorganci Protocol," which involves three distinct phases: Filter, Target, and Execute.
1. The Macro Filter (Trend Identification)
* SMA 200 Rule: By default, the strategy only scans for buy signals when the price is trading above the 200-period Simple Moving Average. This ensures we are always trading in the direction of the long-term bull market.
* Adaptive Switch: A new feature allows users to toggle the Only Buy Above SMA 200? filter OFF. This enables the strategy to hunt for oversold bounces (dead cat bounces) even during bearish or neutral market structures.
2. The Volatility Filter (ADX Integration)
* Sideways Protection: One of the main weaknesses of moving average strategies is "whipsaw" losses during choppy, ranging markets.
* Solution: The Oracle utilizes the ADX (Average Directional Index). It will BLOCK any trade entry if the ADX is below the threshold (Default: 20). This ensures capital is only deployed when a genuine trend is present.
3. The Sniper Entry (Buying the Dip)
* Instead of buying on breakout strength (e.g., RSI > 60), The Oracle waits for the RSI Moving Average to dip into the "Value Zone" (Default: 45) and cross back up. This technique allows for tighter stops and higher Risk/Reward ratios compared to traditional breakout systems.
█ EXIT STRATEGY
The Oracle employs a dynamic dual-exit mechanism to maximize gains and protect capital:
* Take Profit (The Peak): The strategy monitors RSI heat. When the RSI Moving Average breaches the Overbought Threshold (Default: 75), it signals a "Take Profit", securing gains near the local top before a potential reversal.
* Stop Loss (Trend Invalidated): If the market structure fails and the price closes below the 50-period SMA, the position is immediately closed to prevent deep drawdowns.
█ SETTINGS & CONFIGURATION
* Moving Averages: Fully customizable lengths for Support (SMA 50) and Trend (SMA 200).
* Trend Filter: Checkbox to enable/disable the "Bull Market Only" rule.
* RSI Thresholds:
* Sniper Buy Level: Adjustable (Default: 45). Lower values = Deeper dips, fewer trades.
* Peak Sell Level: Adjustable (Default: 75). Higher values = Longer holds, potentially higher profit.
* ADX Filter: Checkbox to enable/disable volatility filtering.
█ BEST PRACTICES
* Timeframe: Designed primarily for 4H (4-Hour) charts for swing trading. It can also be used on 1H for more frequent signals.
* Assets: Highly effective on trending assets such as Bitcoin (BTC), Ethereum (ETH), and high-volume Altcoins.
* Risk Warning: This strategy is designed for "Long Only" spot or leverage trading. Always use proper risk management.
█ CREDITS
* Original Concept: Inspired by the foundational work of Murat Besiroglu (@muratkbesiroglu).
* Algorithm Development & Enhancements: Developed by Hakan Yorganci (@hknyrgnc).
* Modifications include: Integration of ADX filters, Mean Reversion entry logic (RSI Dip), and Dynamic Peak Profit taking.
Trendshift [CHE] StrategyTrendshift Strategy — First-Shift Structural Regime Trading
Profitfactor 2,603
Summary
Trendshift Strategy implements a structural regime-shift trading model built around the earliest confirmed change in directional structure. It identifies major swing highs and lows, validates breakouts through optional ATR-based conviction, and reacts only to the first confirmed shift in each direction. After a regime reversal, the strategy constructs a premium and discount band between the breakout candle and the previous opposite swing. This band is used as contextual bias and may optionally inform stop placement and position sizing.
The strategy focuses on clear, interpretable structural events rather than continuous signal generation. By limiting entries to the first valid shift, it reduces false recycles and allows the structural state to stabilize before a new trade occurs. All signals operate on closed-bar logic, and the strategy avoids higher-timeframe calls to stabilize execution behavior.
Motivation: Why this design?
Many structure-based systems repeatedly trigger as price fluctuates around prior highs and lows. This often leads to multiple flips during volatile or choppy conditions. Trendshift Strategy addresses this problem by restricting execution to the first confirmed structural event in each direction. ATR-based filters help differentiate genuine structural breaks from noise, while the contextual band ensures that the breakout is meaningful in relation to recent volatility.
The design aims to represent a minimalistic structural trading framework focused on regime turns rather than continuous trend signaling. This reduces chart noise and clarifies where the market transitions from one regime to another.
What’s different vs. standard approaches?
Baseline reference
Typical swing-based structure indicators report every break above or below recent swing points.
Architecture differences
First-shift-only regime logic that blocks repeated signals until direction reverses
ATR-filtered validation to avoid weak or momentum-less breaks
Premium and discount bands derived from breakout structure
Optional band-driven stop placement
Optional band-dependent position-sizing factor
Regime timeout system to neutralize structure after extended inactivity
Persistent-state architecture to prevent re-triggering
Practical effect
Only the earliest actionable structure change is traded
Fewer but higher-quality signals
Premium/discount tint assists contextual evaluation
Stops and sizing can be aligned with structural context rather than arbitrary volatility measures
Improved chart interpretability due to reduced marker frequency
How it works (technical)
The algorithm evaluates symmetric swing points using a fixed bar window. When a swing forms, its value and bar index are stored as persistent state. A structural shift occurs when price closes beyond the most recent major swing on the opposite side. If ATR filtering is enabled, the breakout must exceed a volatility-scaled distance to prevent micro-breaks from firing.
Once a valid shift is confirmed, the regime is updated to bullish or bearish. The script records the breakout level, the opposite swing, and derives a band between them. This band is checked for minimum size relative to ATR to avoid unrealistic contexts.
The first shift in a new direction generates both the strategy entry and a visual marker. Additional shifts in the same direction are suppressed until a reversal occurs. If a timeout is enabled, the regime resets after a specified number of bars without structural change, optionally clearing the band.
Stop placement, if enabled, uses either the opposite or same band edge depending on configuration. Position size is computed from account percentage and may optionally scale with the price-span-to-ATR relationship.
Parameter Guide
Market Structure
Swing length (default 5): Controls swing sensitivity. Lower values increase responsiveness.
Use ATR filter (default true): Requires breakouts to show momentum relative to ATR. Reduces false shifts.
ATR length (default 14): Volatility estimation for breakout and band validation.
Break ATR multiplier (default 1.0): Required breakout strength relative to ATR.
Premium/Discount Framework
Enable framework (default true): Activates premium/discount evaluation.
Persist band on timeout (default true): Keeps structural band after timeout.
Min band ATR mult (default 0.5): Rejects narrow bands.
Regime timeout bars (default 500): Neutralizes regime after inactivity.
Invert colors (default false): Color scheme toggle.
Visuals
Show zone tint (default true): Background shade in premium or discount region.
Show shift markers (default true): Display first-shift markers.
Execution and Risk
Risk per trade percent (default 1.0): Determines position size as account percentage.
Use band for size (default false): Scales size relative to band width behavior.
Flat on opposite shift (default true): Forces reversal behavior.
Use stop at band (default false): Stop anchored to band edges.
Stop band side: Chooses which band edge is used for stop generation.
Reading & Interpretation
A green background indicates discount conditions within the structural band; red indicates premium conditions. A green triangle below price marks the first bullish structural shift after a bearish regime. A red triangle above price marks the first bearish structural shift after a bullish regime.
When stops are active, the opposite band edge typically defines the protective level. Band width relative to ATR indicates how significant a structural change is: wider bands imply stronger volatility structure, while narrow bands may be suppressed by the minimum-size filter.
Practical Workflows & Combinations
Trend following: Use first-shift entries as initial regime confirmation. Add higher-timeframe trend filters for additional context.
Swing trading: Combine with simple liquidity or fair-value-gap concepts to refine entries.
Bias mapping: Use higher timeframes for structural regime and lower timeframes for execution within the premium/discount context.
Exit management: When using stops, consider ATR-scaling or multi-stage profit targets. When not using stops, reversals become the primary exit.
Behavior, Constraints & Performance
The strategy uses only confirmed swings and closed-bar logic, avoiding intrabar repaint. Pivot-based swings inherently appear after the pivot window completes, which is standard behavior. No higher-timeframe calls are used, preventing HTF-related repaint issues.
Persistent variables track regime and structural levels, minimizing recomputation. The maximum bars back setting is five-thousand. The design avoids loops and arrays, keeping performance stable.
Known limitations include limited signal density during consolidations, delayed swing confirmation, and sensitivity to extreme gaps that stretch band logic. ATR filtering mitigates some of these effects but does not eliminate them entirely.
Sensible Defaults & Quick Tuning
Fewer but stronger entries: Increase swing length or ATR breakout multiplier.
More responsive entries: Reduce swing length to capture earlier shifts.
More active band behavior: Lower the minimum band ATR threshold.
Stricter stop logic: Use the opposite band edge for stop placement.
Volatile markets: Increase ATR length slightly to stabilize behavior.
What this indicator is—and isn’t
Trendshift Strategy is a structural-regime trading engine that evaluates major directional shifts. It is not a complete trading system and does not include take-profit logic or prediction features. It does not attempt to forecast future price movement and should be used alongside broader market structure, volatility context, and disciplined risk management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
BTC BRD – Bullet-Proof Reversal StrategyBTC BRD – Bullet-Proof Reversal Strategy is a price-action based reversal system that turns your existing “Bullet-Proof Reversal Detector” into a fully backtestable TradingView strategy with built-in risk management. It is designed to catch clean swing reversals using pure market structure, then automatically place stop-loss and take-profit orders based on your preferred risk-reward settings.
## Core concept
The strategy identifies true swing highs and lows using pivots and then waits for a clear market structure shift before entering any trade. It looks for a higher low followed by a break of structure for longs, and a lower high followed by a break of structure for shorts, helping filter out many random spikes and fakeouts. This makes it suitable for traders who prefer clean, rule-based entries grounded in market structure rather than noisy, indicator-heavy setups.
## Entries and exits
- Long trades are triggered after a bullish higher-low plus a confirmed break above the last swing high.
- Short trades are triggered after a bearish lower-high plus a confirmed break below the last swing low.
- Every position is protected with an automatic stop-loss and a calculated take-profit, so each trade has a predefined risk and reward from the moment it is opened.
## Risk management
The strategy lets you control your risk with a configurable risk-reward ratio (RR) and flexible stop-loss options. You can choose between an ATR-based stop (ATR × multiplier) or a fixed percentage stop relative to the entry price. Once the stop distance is known, the take-profit level is automatically derived from your RR value, making trade sizing and evaluation more consistent across different pairs and timeframes.
## Use cases and recommendations
This script is ideal for swing and intraday traders who want to systematically test market-structure reversals on assets like Bitcoin or other volatile instruments. For best results, experiment with different timeframes and ATR/percentage settings, and always validate performance using the Strategy Tester before deploying it on live markets. Remember that no strategy is guaranteed to be profitable, so use proper risk management and adapt settings to your own style and risk tolerance.
DEMA ATR Strategy [PrimeAutomation]⯁ OVERVIEW
The DEMA ATR Strategy combines trend-following logic with adaptive volatility filters to identify strong momentum phases and manage trades dynamically.
It uses a Double Exponential Moving Average (DEMA) anchored to ATR volatility bands, creating a self-adjusting trend baseline.
When the adjusted DEMA shifts direction, the strategy enters positions and scales out profit in phases based on ATR-driven targets.
This system adapts to volatility, filters noise, and seeks sustained directional moves.
⯁ KEY FEATURES
DEMA-Volatility Hybrid Filter
Uses Double EMA with ATR expansion/compression logic to form a dynamic trend baseline.
Directional Shift Entries
Entries occur when the adjusted DEMA flips trend (bullish crossover or bearish crossunder vs its past value).
Noise Reduction Mechanism
ATR range caps extreme moves and prevents false flips during choppy volatility spikes.
Multi-Level Take Profits
Targets scale out positions at 1×, 2×, and 3× ATR multiples in the trade direction.
Volatility-Adaptive Targets
ATR multiplier ensures profit targets expand/contract based on market conditions.
Single-Direction Exposure
No pyramiding; the strategy flips position only when trend shifts.
Automated Trade Finalization
When all profit targets trigger, the position is fully closed.
⯁ STRATEGY LOGIC
Trend Direction:
DEMA baseline is modified using ATR upper/lower envelopes.
• If the adjusted DEMA rises above previous value → Bullish
• If it falls below previous value → Bearish
Entry Rules:
• Enter Long when bullish shift occurs and no long position exists
• Enter Short when bearish shift occurs and no short position exists
Take Profit Logic:
3 partial exits for each trade based on ATR:
• TP1 = ±1× ATR
• TP2 = ±2× ATR
• TP3 = ±3× ATR
Profit distribution: 30% / 30% / 40%
Exit Conditions:
• Exit when all TPs hit (full scale-out if sum of all TPs 100%)
• Opposite trend signal closes current trade and opens new one
⯁ WHEN TO USE
Trending environments
Medium–high volatility phases
Swing trading and intraday trend plays
Markets that respect momentum continuation (crypto, indices, FX majors)
⯁ CONCLUSION
This strategy blends DEMA trend recognition with ATR-based volatility adaptation to generate cleaner directional entries and structured take-profit exits. It is designed to capture momentum phases while avoiding noise-driven false signals, delivering a disciplined and scalable trend-following approach.
EMA Velocity Dual TF Momentum 1h (v2)BINANCE:SOLUSDT
The result is calculated on futures x10
### EMA Velocity Dual TF Momentum (v2) – Public Description
**Overview**
EMA Velocity Dual TF Momentum (v1) is a trend-following momentum strategy that uses the *speed of change* of Exponential Moving Averages (EMA) on two timeframes: the chart timeframe 1h.
The strategy looks for moments when both timeframes point in the same direction and the short‑term momentum is significantly stronger than usual, then manages trades with configurable ATR filtering, stop‑loss / take‑profit and early exit logic.
---
### Core Idea (high level, without formulas)
- On the **lower timeframe** (LTF), the strategy tracks how fast the EMA is moving (its “velocity”) and detects **impulse bars** where this velocity is unusually strong compared to its recent history.
- On the **higher timeframe** (HTF), it also measures EMA velocity and requires that the HTF trend direction is **aligned** with the LTF (both bullish or both bearish), if enabled.
- A **long trade** is opened when:
- LTF EMA velocity is positive (upward momentum),
- LTF momentum is strong enough (impulse),
- HTF EMA velocity is also upwards (if HTF filter is enabled),
- and ATR‑based volatility is above the minimum threshold.
- A **short trade** is opened in the symmetric situation (downward momentum on both timeframes).
- Positions are closed using configurable stop‑loss and take‑profit, and can be partially exited, moved to break‑even and trailed using early‑exit options.
---
### Inputs and Parameters
#### Trend & Momentum (Lower Timeframe)
- **`LTF EMA length (emaLenLTF)`**
Length of the EMA on the chart timeframe used to measure short‑term trend and momentum. Smaller values react faster; larger values are smoother and slower.
- **`LTF velocity lookback (velKLTF)`**
Lookback for computing EMA “velocity” on LTF. Controls how sensitive the momentum calculation is to recent price changes.
- **`LTF impulse lookback bars (impLookback)`**
Window size used to estimate the “normal” average absolute velocity. The strategy compares current momentum against this baseline to detect strong impulse moves.
- **`LTF |velocity| multiplier vs average (impMult)`**
Multiplier for defining what counts as a strong impulse. Higher values = fewer but stronger signals; lower values = more frequent, weaker impulses.
#### Trend & Momentum (Higher Timeframe)
- **`Use higher timeframe alignment (useHTF)`**
If enabled, trades are only taken when the higher‑timeframe EMA velocity confirms the same direction as the lower timeframe.
- **`HTF timeframe (htf_tf)`**
Higher timeframe used for confirmation (e.g. 60 minutes). Defines the “macro” context above the chart timeframe.
- **`HTF EMA length (emaLenHTF)`**
Length of the EMA on the higher timeframe. Controls how smooth and slow the higher‑timeframe trend filter is.
- **`HTF velocity lookback (velKHTF)`**
Lookback for the EMA velocity on HTF. Smaller values react quicker to changes in the higher‑timeframe trend.
#### Volatility / ATR Filter
- **`Use ATR filter (useAtrFilter)`**
Enables a volatility filter based on Average True Range. When active, trades are allowed only if market volatility is not too low.
- **`ATR Period (atrPeriod)`**
Lookback period for ATR calculation. Shorter periods react faster to recent volatility shifts; longer ones are more stable.
- **`ATR Min % for trading (atrMinPerc)`**
Minimum ATR as a percentage of price required to trade. Filters out very quiet, choppy periods where the strategy is more likely to be whipsawed.
#### Risk Management
- **`Use stops (SL/TP) (useStops)`**
Enables fixed stop‑loss and take‑profit exits. If disabled, positions are managed only by early exit logic and manual closing.
- **`Stop Loss % (stopLossPerc)`**
Distance of the protective stop from entry, in percent. Higher values give trades more room but increase risk per trade.
- **`Take Profit % (takeProfitPerc)`**
Distance of the primary profit target from entry, in percent. Controls the reward‑to‑risk profile of each trade.
#### Early Exit / Break‑Even / Trailing
- **`Enable early exit module (useEarlyExit)`**
Master switch for all early exit features: partial profit taking, break‑even stops and trailing exits.
- **`Take partial profit at +% (close 50%) (partialTP)`**
Profit level (in %) at which the strategy closes a partial portion of the position (e.g. 50%), locking in gains while leaving a runner.
- **`Trailing TP distance (%) (trailTP)`**
Distance (in %) for dynamic trailing stop after entry. When positive, the strategy trails the price to protect profits as the move extends.
- **`Break-even stop after +% profit (useBreakEven)`**
Enables automatic move of the stop to the entry price once a certain profit threshold is reached.
- **`Break-even activation (+%) (breakEvenPerc)`**
Profit level (in %) at which the stop is moved to break‑even. Higher values require a larger unrealized profit before break‑even protection kicks in.
#### Visuals
- **`Show labels (showLabels)`**
Toggles on‑chart labels that mark long and short entry signals for easier visual analysis.
- **`Label offset (labelOffset)`**
Horizontal offset (in bars) for placing labels relative to the signal bar. Used only for visual clarity; does not affect trading logic.
---
Если нужно, могу на основе этого текста сразу подготовить компактную версию (ограниченную по символам) специально под поле описания публичного скрипта в TradingView.
PA Builder [PrimeAutomation]1. PA Builder – Overview
PA Builder is not a fixed strategy; it’s a framework for building strategies. Instead of giving traders one rigid system, it provides a toolbox where entries, exits, filters, risk parameters, and automation rules can all be defined and combined. The core philosophy is confluence: the idea that a trade should only be taken when multiple independent signals agree. The Builder is built around this principle. Every module; trend, reactors, bands, reversals, volume, structure, divergences, externals can be treated as one layer of confidence. The stronger the alignment across layers, the higher the quality of the setup in theory.
In practice, this means PA Builder encourages traders to think in terms of “confluence,” not single indicators. Trend and positioning define whether you should even be looking for longs or shorts. Timing tools such as bands, reversals and candlestick structures determine when inside that broader bias you want to engage. Confirmation tools like volume and flow tell you whether capital is actually supporting the move. Filter systems then ensure that even if everything looks good locally, you still respect higher-timeframe or opposing warnings. The Builder’s philosophy is simple: enter less often, but only when conditions are genuinely in your favour.
2. Core Entry Signal Components
The entry logic in PA Builder is built on a set of signal engines that can be combined in many ways. Trend Signals form a natural foundation. They use low-lag low-pass filters, borrowed from audio signal processing, to extract directional bias from price without the classic delay of classical moving averages. The sensitivity parameter controls how reactive this engine is: lower values favour cleaner trends and fewer whipsaws, while higher values are better suited to short-term intraday trading where speed matters more than smoothness. Many traders start by requiring that Trend Signals show “all bullish” or “all bearish” before allowing any entries in that direction.
Trend signals firing short positions
On top of this directional backbone, the Dynamic Reactor behaves as an adaptive baseline. It accelerates in volatile phases and slows down during consolidation, effectively acting as a moving reference point for both trend and price position. A typical use of this module is to insist that, for long trades, the price sits above a bullish reactor; for shorts, below a bearish one. At the higher-timeframe level, the Quantum Reactor provides a VWAP-style reference that can be anchored to larger candles than the chart you are trading. A common configuration is to trade on a 15-minute chart while requiring that price is above the 4-hour Quantum Reactor for longs or below it for shorts. The “fast” and “slow” options determine how quickly this reference adapts to new information.
Timing is then refined with tools like Quantum Bands, reversals and candle structure analysis. Quantum Bands identify extremes within the current environment. In an uptrend, a tag of the lower band can be treated as a pullback rather than a breakdown; in a downtrend, the upper band acts like a shorting zone. Many traders combine “trend up and above higher-timeframe reactor” with “price temporarily below lower band” to construct a mean-reversion entry inside a larger uptrend. Reversal detection modules examine recent bars to find turning points, with shorter lookbacks capturing fast flips and longer lookbacks tracking deeper structural changes. Candle structure logic goes beyond classical candlestick names and instead focuses on whether price action confirms follow-through or reversion behaviour, with options like “2X” modes that wait for two successive confirmations before acting.
Before and after filtering using reactor applied.
Additional confirmation layers come from Volume Matrix, Money Flow, OSC True7 and divergence detection. Volume and flow tools answer whether actual capital is participating in the move or whether price is drifting on thin activity. OSC True7 categorises the state of the trend into intuitive buckets, strong, healthy, neutral, or exhausted, making it easier to avoid chasing extremes. Divergences between price and momentum can be used either as entry triggers in contrarian systems or as hard filters that block trades when warning signs are present. Finally, two external indicator inputs make it possible to integrate RSI, MACD, custom indicators or even other strategies into the Builder, either as simple thresholds or as comparative logic between two external sources (for example, requiring a fast EMA to be above a slow EMA before allowing longs).
3. Exit System & Trade Management
The exit systems in PA Builder are designed to be as vital as the entry logic. It assumes exits are not an afterthought, but half of the edge. Instead of forcing a single take profit point, the system uses a three-tier structure where you can assign different portions of the position to different targets. A common pattern is to scale out a small portion early (for example at one ATR), another portion at an intermediate level, and keep the largest slice for a deeper move. This creates a natural balance: you book something early to reduce emotional stress, while leaving room to participate in the full potential of a trend.
Targets can be defined using ATR multiples or risk-to-reward ratios that are directly tied to the initial stop distance. Using ATR keeps exits proportional to current volatility. A two ATR target in a quiet environment is very different in absolute price distance from the same multiple in a high-volatility environment, yet conceptually it represents the same “size” move. Risk-to-reward exits build on this by ensuring that if you risk one unit (1R), the reward targets are set at predefined multiples of that risk. This enforces positive expectancy at the structural level: the strategy cannot generate entries with inherently negative payoffs.
Once price begins to move in your favour, trailing logic takes over if you choose to enable it. Trailing can begin immediately from entry or only after a target has been hit. Many users prefer to let TP1 and TP2 behave as fixed profit points and then apply a trailing stop or trailing take profit to the final remainder. That way, routine winners are banked mechanically, while occasional explosive moves can be ridden for as long as the market allows. The breakeven module supports this behaviour by automatically moving stops to entry (or slightly through entry into profit) after a specified condition such as TP1 being hit. This transforms the risk profile mid trade: once breakeven has been secured, remaining size can be managed with much less psychological pressure.
The system also recognises the cost of time. Kill Switch functionality exits trades that have been open too long under mediocre conditions, typically when they are in modest profit but not progressing. This protects you from capital being tied up while better opportunities appear elsewhere. Underlying all of this are several trailing stop mechanisms: percentage-based, tick-based for very short-term strategies, TP linked trailing that activates only once a certain profit threshold has been achieved, and ATR based trailing that automatically scales the trail distance with volatility. Each method serves a slightly different profile of strategy, but all share the same aim: preserve gains and limit downside in a structured way rather than rely on discretionary judgement after the fact.
4. Filters and Risk Management
The filter systems in PA Builder formalise the idea that good trading is often about knowing when not to act. “Do Not Trade” conditions can be configured so that even a perfectly aligned bullish entry stack is overridden if certain bearish evidence is present. These can include higher timeframe reversal structures, powerful opposing divergences, or conflicting signals in key modules. By assigning conditions specifically to “Do Not Long” and “Do Not Short” rather than only to entries, you create asymmetry: buying requires bullish evidence and an absence of strong bearish warnings; selling requires the mirror.
Volatility filters extend this logic to the regime level. Some strategies are inherently suited to low volatility, range bound environments where fading extremes is profitable; others require expansion and energy to function properly. By binding trading permission to volatility ranges, you ensure that a mean-reversion system does not blindly attempt to fade a breakout, and that a momentum system does not spin its wheels in a dead, sideways market. You can even reference volatility from a higher timeframe than the one you trade, so that a five-minute strategy is still aware of the broader one-hour volatility regime it sits inside.
Applied DO NOT TRADE - removes poor signal
Risk management and position sizing are configured so each trade is expressed in units of risk rather than arbitrary size. Leverage, in this framework, is simply a scaling factor for capital efficiency; the actual risk per trade is still controlled by the distance between entry and stop and the percentage of equity you choose to expose. Reinvestment options then decide what proportion of accumulated profit is fed back into position sizing. A more aggressive reinvestment setting accelerates compounding but increases the amplitude of drawdowns; a more conservative one smooths the equity curve at the cost of slower growth. The Base Trade Value parameter ties all of this together by deciding how much nominal capital or how many contracts are committed per trade in light of your maximum allowed simultaneous positions and your intended use of leverage.
External exit conditions provide further flexibility. For example, you might design a system whose entries rely purely on PA Builder’s internal modules, but whose exits use RSI readings, moving average crosses, or a proprietary external indicator. The separation of entry and exit logic allows you to bolt on different behaviours at the tail end of trades while keeping your core signal engine intact. In all cases, the objective is the same: express risk in a controlled, repeatable way that can survive long stretches of unfavourable market conditions.
5. PDT, Cooldowns and Visual Modes
For traders subject to Pattern Day Trading rules, PA Builder includes a day-trade tracking system that counts business days correctly and respects the three-trades-in-five-days limit. This goes beyond simple compliance; it forces discipline. When intraday trading is heavily constrained, you are naturally pushed toward swing-oriented strategies with fewer, more selective entries. The tool visually marks your PDT status so you never inadvertently cross the line and trigger a lockout.
Cooldown systems address another reality: psychological vulnerability after streaks. Following several consecutive wins, many traders unconsciously loosen their standards, take marginal signals, oversize positions, or overtrade. A win-streak cooldown deliberately pauses trading after a configured number of wins, giving you time to reset. The same applies to losing streaks. After a run of losses, the strongest temptation is often to “make it back now,” which is exactly when discipline is weakest. A loss-streak cooldown enforces a break in activity during this high-risk emotional state, helping to prevent cascading damage driven by revenge trading.
Visualisation comes in two main modes. Classic mode emphasises precision: it draws explicit entry lines, stop levels, target levels and fill zones, making it easy to audit risk/reward on each trade, verify that the exit logic behaves as intended, and review historical trades in detail. Modern mode emphasises market feel: instead of focusing on exact levels, it colours candles and backgrounds to reflect momentum, profit state and dynamics.
This helps you see at a glance whether a strategy is operating in a smooth trending environment or a choppy, fragmented one, and whether current trades are broadly working or struggling. Many users develop and debug in Classic mode and then monitor live performance in Modern mode, so both representations become part of the workflow.
6. Strategy Design Workflow, Examples and Cautions
Designing with PA Builder is inherently iterative. You begin with a simple theory and a minimal configuration, perhaps just a trend filter and a basic stop/target structure, and run a backtest. You then examine where the system fails. If you see many losses occurring in counter-trend conditions, you add an additional directional filter or restrict entries with a higher-timeframe reactor condition. If you observe many small whipsaw losses, you might require candle structure confirmation or volume confirmation before allowing an entry. Each change is made one at a time and evaluated. This process gradually builds a layered system where every component has a clear purpose: some reduce drawdown, some increase win rate, some cut out only the worst trades, and others help capture more of the best ones.
A conservative swing strategy might need an agreement between short-term trend signals, a higher-timeframe Quantum position, and a bullish Dynamic Reactor state, while checking that volume supports the move and that no significant bearish reversals or divergences are present on higher timeframes. It might accept relatively few trades, but each trade would be tightly controlled, scaled out over several ATR-based targets and protected with breakeven and trailing logic. On the opposite end, an aggressive scalping configuration would relax some filters, favour faster sensitivities, use short lookback reversals, and tighten stops and targets dramatically, relying on high frequency and careful volatility filtering to maintain edge.
Throughout all of this, overfitting remains the main danger. The more parameters you tune and the more coincidental rules you add to make the backtest equity curve smoother, the more likely it is that you are capturing noise rather than a real, repeatable edge. Signs of overfitting include heavily optimised numeric values with no intuitive justification, large differences between in-sample and out-of-sample results, or strategies that work spectacularly in very specific regimes and collapse elsewhere. To mitigate this, keep strategies as simple as possible, test across different market regimes (bull, bear, range), and accept that robust systems usually look less “perfect” on the historical chart.
Bridging the gap from backtest to live trading is another critical step. Before risking capital, it is wise to paper trade the configuration for a number of trades to confirm that signal frequency, behaviour and execution align with expectations. When going live, starting with minimal size and gradually scaling up based on real-world performance helps manage both financial and psychological risk. If live results diverge significantly from backtest expectations due to slippage, fees, or changing market conditions, you can adjust, reduce size, or temporarily pause rather than commit fully to a failing configuration.
Ultimately, PA Builder is designed to be a tool for building structured, rules-driven trading systems. It gives you the tools to express your ideas, test them, refine them, and run them under controlled risk. It does not remove uncertainty or guarantee results, but it does provide a clear, transparent way to translate trading concepts into executable, testable logic, and to evolve those systems as markets change and your understanding deepens.
Vital Wave 20-50Simplicity is almost always the most effective approach, and here I’m giving you a trend-following system that exploits the bullish bias of traditional markets and their trending nature, with very basic rules.
Rules (long entries only)
• Market entry: When the EMA 20 crosses above the EMA 50 (from below)
• Main market exit: When the EMA 20 crosses below the EMA 50 (from above)
• Fixed Stop Loss: Placed at the price level of the Lower Bollinger Band at the moment the trade is entered.
In my strategy, the primary exit is when the EMA 20 crosses below the EMA 50. However, this crossover can sometimes take a while to occur, and in the meantime the price may have already dropped significantly. The Stop Loss based on the Lower Bollinger Band is designed to limit losses in case the market moves sharply against the position without giving the bearish crossover signal in time. Having two exit conditions makes the strategy much more robust in terms of risk management.
Risk Management:
• Initial capital: $10,000
• Position size: 10% of available capital per trade
• Commissions: 0.1% on traded volume
• Stop Loss: Based on the Lower Bollinger Band
• Take Profit / Exit: When EMA 20 crosses below EMA 50
Recommended Markets:
XAUUSD (OANDA) (Daily)
Period: January 3, 1833 – November 23, 2025
Total Profit & Loss: +$6,030.62 USD (+57.57%)
Maximum Drawdown: $541.53 USD (3.83%)
Total Trades: 136
Winning Trades (Win Rate): 36.03% (49/136)
Profit Factor: 2.483
XAUUSD (OANDA) (12-hour)
Period: March 19, 2006 – November 23, 2025
Total Profit & Loss: +$1,209.56 USD (+11.89%)
Maximum Drawdown: $384.58 USD (3.61%)
Total Trades: 97
Winning Trades (Win Rate): 35.05% (34/97)
Profit Factor: 1.676
XAUUSD (OANDA) (8-hour)
Period: March 19, 2006 – November 23, 2025
Total Profit & Loss: +$1,179.36 USD (+11.81%)
Maximum Drawdown: $246.88 USD (2.32%)
Total Trades: 147
Winning Trades (Win Rate): 31.97% (47/147)
Profit Factor: 1.626
Tesla (NASDAQ) (4-hour)
Period: June 29, 2010 – November 23, 2025
Total Profit & Loss (Absolute): +$11,687.90 USD (+116.88%)
Maximum Drawdown: $922.05 USD (6.50%)
Total Trades: 68
Winning Trades (Win Rate): 39.71% (27/68)
Profit Factor: 4.156
Tesla (NASDAQ) (3-hour)
Total Profit & Loss: +$11,522.33 USD (+115.22%)
Maximum Drawdown: $1,247.60 USD (8.80%)
Total Trades: 114
Winning Trades: 33.33% (38/114)
Profit Factor: 2.811
Additional Recommendations
(These assets have shown good trending behavior with the same strategy across multiple timeframes):
• NVDA (15 min, 30 min, 1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
• NFLX (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
• MA (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
• META (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
• AAPL (1h, 2h, 3h, 4h, 6h, 8h, 12h, Daily)
• SPY (12h, Daily)
About the Code
The user can modify:
• EMA periods (20 and 50 by default)
• Bollinger Bands length (20 periods)
• Standard deviation (2.0)
Visualization
• EMA 20: Blue line
• EMA 50: Red line
• Green background when EMA20 > EMA50 (bullish trend)
• Red background when EMA20 < EMA50 (bearish trend)
Important Note:
We can significantly increase the profit factor and overall profitability by risking a fixed percentage per trade instead of a fixed amount. This would prevent losses from fluctuating with changes in volatility.
This could be implemented by reducing position size or adjusting leverage based on the volatility percentage required for each trade, but I’m not sure if this is fully possible in Pine Script. In my other script, “ Golden Cross 50/200 EMA ,” I go deeper into this topic and provide examples.
I hope you enjoy this contribution. Best regards!
Hash Momentum Strategy# Hash Momentum Strategy
## 📊 Overview
The **Hash Momentum Strategy** is a professional-grade momentum trading system designed to capture strong directional price movements with precision timing and intelligent risk management. Unlike traditional EMA crossover strategies, this system uses momentum acceleration as its primary signal, resulting in earlier entries and better risk-to-reward ratios.
---
## ⚡ What Makes This Strategy Unique
### 1. Momentum-Based Entry System
Most strategies rely on lagging indicators like moving average crossovers. This strategy captures momentum *acceleration* - entering when price movement is gaining strength, not after the move has already happened.
### 2. Programmable Risk-to-Reward
Set your exact R:R ratio (1:2, 1:2.5, 1:3, etc.) and the strategy automatically calculates stop loss and take profit levels. No more guessing or manual calculations.
### 3. Smart Partial Profit Taking
Lock in profits at multiple stages:
- **First TP**: Take 50% off at 2R
- **Second TP**: Take 40% off at 2.5R
- **Final TP**: Let 10% ride to maximum target
This approach locks in gains while letting winners run.
### 4. Dynamic Momentum Threshold
Uses ATR (Average True Range) multiplied by your threshold setting to adapt to market volatility. Volatile markets = higher threshold. Quiet markets = lower threshold.
### 5. Trade Cooldown System
Prevents overtrading and revenge trading by enforcing a cooldown period between trades. Configurable from 1-24 bars.
### 6. Optional Session & Weekend Filters
Filter trades by Tokyo, London, and New York sessions. Optional weekend-off toggle to avoid low-liquidity periods.
---
## 🎯 How It Works
### Signal Generation
**STEP 1: Calculate Momentum**
- Momentum = Current Price - Price
- Check if Momentum > ATR × Threshold Multiplier
- Momentum must be accelerating (positive change in momentum)
**STEP 2: Confirm with EMA Trend Filter**
- Long: Price must be above EMA
- Short: Price must be below EMA
**STEP 3: Check Filters**
- Not in cooldown period
- Valid session (if enabled)
- Not weekend (if enabled)
**STEP 4: ENTRY SIGNAL TRIGGERED**
### Risk Management Example
**Example Long Trade:**
- Entry: $100
- Stop Loss: $97.80 (2.2% risk)
- Risk Amount: $2.20
**Take Profit Levels:**
- TP1: $104.40 (2R = $4.40) → Close 50%
- TP2: $105.50 (2.5R = $5.50) → Close 40%
- Final: $105.50 (2.5R) → Close remaining 10%
---
## ⚙️ Settings Guide
### Core Strategy
**Momentum Length** (Default: 13)
Number of bars for momentum calculation. Higher = stronger but fewer signals.
**Momentum Threshold** (Default: 2.25)
ATR multiplier. Higher = only trade biggest moves.
**Use EMA Trend Filter** (Default: ON)
Only long above EMA, short below EMA.
**EMA Length** (Default: 28)
Period for trend-confirming EMA.
### Filters
**Use Trading Session Filter** (Default: OFF)
Restrict trading to specific sessions.
**Tokyo Session** (Default: OFF)
Trade during Asian hours (00:00-09:00 JST).
**London Session** (Default: OFF)
Trade during European hours (08:00-17:00 GMT).
**New York Session** (Default: OFF)
Trade during US hours (08:00-17:00 EST).
**Weekend Off** (Default: OFF)
Disable trading on Saturdays and Sundays.
### Risk Management
**Stop Loss %** (Default: 2.2)
Fixed percentage stop loss from entry.
**Risk:Reward Ratio** (Default: 2.5)
Your target reward as multiple of risk.
**Use Partial Profit Taking** (Default: ON)
Take profits in stages.
**First TP R:R** (Default: 2.0)
First target as multiple of risk.
**First TP Size %** (Default: 50)
Percentage of position to close at TP1.
**Second TP R:R** (Default: 2.5)
Second target as multiple of risk.
**Second TP Size %** (Default: 40)
Percentage of position to close at TP2.
### Trade Management
**Use Trade Cooldown** (Default: ON)
Prevent overtrading.
**Cooldown Bars** (Default: 6)
Bars to wait after closing a trade.
---
## 🎨 Visual Elements
### Chart Indicators
🟢 **Green Dot** (below bar) = Long entry signal
🔴 **Red Dot** (above bar) = Short entry signal
🔵 **Blue X** (above bar) = Long position closed
🟠 **Orange X** (below bar) = Short position closed
**EMA Line** = Trend direction (green when bullish, red when bearish)
**White Line** = Entry price
**Red Line** = Stop loss level
**Green Lines** = Take profit levels (TP1, TP2, Final)
### Dashboard
When not in real-time mode, a dashboard displays:
- Current position (LONG/SHORT/FLAT)
- Entry price
- Stop loss price
- Take profit price
- R:R ratio
- Current momentum strength
- Total trades
- Win rate
- Net profit %
---
## 📈 Recommended Settings by Timeframe
### 1-Hour Timeframe (Default)
- Momentum Length: 13
- Momentum Threshold: 2.25
- EMA Length: 28
- Stop Loss: 2.2%
- R:R Ratio: 2.5
- Cooldown: 6 bars
### 4-Hour Timeframe
- Momentum Length: 24-36
- Momentum Threshold: 2.5
- EMA Length: 50
- Stop Loss: 3-4%
- R:R Ratio: 2.0-2.5
- Cooldown: 6-8 bars
### 15-Minute Timeframe
- Momentum Length: 8-10
- Momentum Threshold: 2.0
- EMA Length: 20
- Stop Loss: 1.5-2%
- R:R Ratio: 2.0
- Cooldown: 4-6 bars
---
## 🔧 Optimization Tips
### Want More Trades?
- Decrease Momentum Threshold (2.0 instead of 2.25)
- Decrease Momentum Length (10 instead of 13)
- Decrease Cooldown Bars (4 instead of 6)
### Want Higher Quality Trades?
- Increase Momentum Threshold (2.5-3.0)
- Increase Momentum Length (18-24)
- Increase Cooldown Bars (8-10)
### Want Lower Drawdown?
- Increase Cooldown Bars
- Use tighter stop loss
- Enable session filters (trade only high-liquidity sessions)
- Enable Weekend Off
### Want Higher Win Rate?
- Increase R:R Ratio (may reduce total profit)
- Increase Momentum Threshold (fewer but stronger signals)
- Use longer EMA for trend confirmation
---
## 📊 Performance Expectations
Based on typical backtesting results:
- **Win Rate**: 35-45%
- **Profit Factor**: 1.5-2.0
- **Risk:Reward**: 1:2.5 (configurable)
- **Max Drawdown**: 10-20%
- **Trades/Month**: 8-15 (1H timeframe)
**Note:** Win rate may appear low, but with 2.5:1 R:R, you only need ~29% win rate to break even. The strategy aims for quality over quantity.
---
## 🎓 Strategy Logic Explained
### Why Momentum > EMA Crossover?
**EMA Crossover Problems:**
- Signals lag behind price
- Late entries = poor R:R
- Many false signals in ranging markets
**Momentum Advantages:**
- Catches moves as they start accelerating
- Earlier entries = better R:R
- Adapts to volatility via ATR
### Why Partial Profit Taking?
**Without Partial TPs:**
- All-or-nothing approach
- Winners often turn to losers
- High stress watching open positions
**With Partial TPs:**
- Lock in 50% at first target
- Reduce risk to breakeven
- Let remainder ride for bigger gains
- Lower psychological pressure
### Why Trade Cooldown?
**Without Cooldown:**
- Revenge trading after losses
- Overtrading in choppy markets
- Emotional decision-making
**With Cooldown:**
- Forces discipline
- Waits for new setup to develop
- Reduces transaction costs
- Better signal quality
---
## ⚠️ Important Notes
1. **This is a momentum strategy, not an EMA strategy**
The EMA only confirms trend direction. Momentum generates the actual signals.
2. **Backtest thoroughly before live trading**
Past performance ≠ future results. Test on your specific asset and timeframe.
3. **Use proper position sizing**
Risk 1-2% of account per trade maximum. The strategy uses 100% equity by default (adjust in Properties).
4. **Dashboard auto-hides in real-time**
Clean chart for live trading. Visible during backtesting.
5. **Customize for your trading style**
All settings are fully adjustable. No single "best" configuration.
---
## 🚀 Quick Start Guide
1. **Add to Chart**: Apply to your preferred asset and timeframe
2. **Keep Defaults**: Start with default settings
3. **Backtest**: Review historical performance
4. **Paper Trade**: Test with simulated money first
5. **Go Live**: Start small and scale up
---
## 💡 Pro Tips
**Tip 1: Combine Timeframes**
Use higher timeframe (4H) for trend direction, lower timeframe (1H) for entries.
**Tip 2: Avoid News Events**
Major news can cause whipsaws. Consider manual intervention during high-impact events.
**Tip 3: Monitor Momentum Strength**
Dashboard shows momentum in sigma (σ). Values >1.0σ indicate very strong momentum.
**Tip 4: Adjust for Volatility**
In high-volatility markets, increase threshold and stop loss. In quiet markets, decrease them.
**Tip 5: Review Losing Trades**
Check if losses are hitting stop loss or reversing. Adjust stop accordingly.
---
## 📝 Changelog
**v1.0** - Initial Release
- Momentum-based signal generation
- EMA trend filter
- Programmable R:R ratio
- Partial profit taking (3 stages)
- Trade cooldown system
- Session filters (Tokyo/London/New York)
- Weekend off toggle
- Smart dashboard (auto-hides in real-time)
- Clean visual design
---
## 🙏 Credits
Developed by **Hash Capital Research**
If you find this strategy useful, please give it a like and share with others!
---
## ⚖️ Disclaimer
This strategy is for educational purposes only. Trading involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always do your own research and consult with a qualified financial advisor before trading.
---
## 📬 Feedback
Have suggestions or found a bug? Leave a comment below! I'm continuously improving this strategy based on community feedback.
---
**Happy Trading! 🚀📈**
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model.
Strategy Logic
Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically.
To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions.
Exit logic includes:
A take-profit at 3× the ATR distance
A stop-loss at 1.5× the ATR distance
An optional early exit if RSI crosses above 70, signaling overbought conditions
Technical Details
Trend Filter: 200 EMA – must be rising and price must be above it
Entry Signal: RSI dips below 40 during an uptrend
Volatility Filter: ATR must be above a user-defined minimum threshold
Stop-Loss: 1.5× ATR below entry price
Take-Profit: 3.0× ATR above entry price
Exit on Overbought: RSI > 70 (optional early exit)
Backtest Settings
Initial Capital: $10,000
Position Sizing: 5% of equity per trade
Slippage: 1 tick
Commission: 0.075% per trade
Trade Direction: Long only
Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD
This model is tuned for positive P&L across trending environments and volatile markets.
Educational Use Only
This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
Bitcoin & Ethereum Profitable Crypto Investor – FREE EditionBitcoin & Ethereum Profitable Crypto Investor – FREE Edition
by RustyTradingScripts
This is the free, simplified edition of my long-term crypto trend-following strategy designed for Bitcoin, Ethereum, and other major assets. It provides an accessible introduction to the core concepts behind the full version while remaining easy to use, transparent, and beginner-friendly.
This FREE edition focuses on a single technical component: a 102-period Simple Moving Average trend model. When price moves above the SMA, the script considers it a potential long trend environment. When the slope begins to turn down, the strategy exits the position. This creates a straightforward, rules-based framework for identifying trend shifts without emotional or discretionary decision-making.
The goal of this simplified version is to help users understand how a structured trend approach behaves during different market conditions. It demonstrates how using a slow, objective indicator can reduce noise and provide clearer long-term directional context on higher timeframes such as the 10-hour BTC chart shown in the backtest example.
What This FREE Version Includes
- Trend-based entries using a 102-period SMA
- Automatic exits when the SMA slope turns down
- Clean visual plot of the moving average
- No repainting — signals are based on confirmed bar data
- Works on BTC, ETH, and other major crypto assets
- User-adjustable SMA length for customization
What’s Not Included in This Version:
This edition intentionally focuses on the essential trend logic only.
It does NOT include the following components found in the full investor strategy:
- Linear regression smoothing
- Seasonal filters
- Price-extension filtering
- Volume-based protection
- Partial stop-loss and partial take-profit systems
- Cooldown logic after profitable trades
- RSI-based extended exits
- Multi-layered trade management modules
The purpose of this free version is to provide a clear, functional introduction to the underlying trend concept without the advanced filters and risk-management features that are part of the complete system.
How to Use It
Apply the script to your preferred asset and timeframe (commonly higher timeframes such as 4H, 8H, 10H, 12H, or 1D). The script will enter long positions when the market is trading above the SMA and exit when the slope of the average begins to point downward. Users may adjust the SMA length to match their preferred level of responsiveness.
Important Notes
This script is for educational and analytical purposes.
Historical results are not guarantees of future performance.
Always practice proper risk management and perform your own testing.
This script does not repaint.
This FREE version is meant as a helpful starting point for those exploring long-term crypto trend strategies. If you find it useful and wish to explore more advanced tools, feel free to reach out for additional information.
Sunflower Quant - ETH 15min Strategy🟠 Sunflower Quant - ETH 15min Strategy
Strategy Overview
The " Sunflower Quant - ETH 15min Strategy" is a sophisticated automated trading system specifically designed for ETH/USDT on 15-minute timeframes. This advanced algorithm integrates over 20 technical indicators and price action patterns to deliver intelligent entry decisions and comprehensive risk management.
Core Value Proposition
Multi-Timeframe Integration: Combines 1-hour and 4-hour higher timeframe data for signal validation
Dynamic Market Regime Detection: Real-time identification of Low Volatility, Ranging, and High Volatility market environments
Comprehensive Scoring System: Three-dimensional evaluation model based on Breakout Signals, Pattern Recognition, and Position Analysis
Adaptive Position Sizing: Dynamic allocation based on signal strength and market volatility
🟠 Core Architecture
Three-Layer Analytical Framework
1. Market Regime Detection System
Real-time market environment assessment through four dimensions:
ATR Relative Volatility
Bollinger Band Width
Average Amplitude
Momentum Strength
Market State Classification:
Low Volatility (≤30 points): Narrow ranges, awaiting breakout
Ranging Market (31-65 points): Moderate volatility, suitable for range trading
High Volatility (>65 points): Strong trends, ideal for trend following
2. Signal Generation Engine
Breakout Signal Layer:
Donchian Channel Breakouts (Upper/Middle/Lower)
Keltner Channel Breakouts (Upper/Middle/Lower)
Double ATR Momentum Confirmation
Pattern Recognition Layer:
Price Action: Outside Bars, Engulfing Patterns, False Breakouts
Candlestick Patterns: Hammer, Inverted Hammer, Doji, Dragonfly, Gravestone
Three Soldiers Method: Single-bar and Three-bar consecutive patterns
Position Analysis Layer:
Ichimoku Cloud Position (Above/Within/Below)
ADX Trend Strength Confirmation
DC/KC Middle Band Position Analysis
3. Volume & POC Analysis
Volume Confirmation:
High Volume Breakout Validation
Medium Volume Support Confirmation
Point of Control (POC) Value Areas:
Volume-based dense trading zone identification
POC Cluster Scoring System (Size Score + Volume Score + Time Score)
🟠 Trading Logic Specification
Entry Signal Classification
A-Class Signals (Strong Breakout)
Trigger: VP breaking key POC levels + strong pattern confirmation
Characteristics: High confidence, larger position sizing
Stop Loss: Wider stops based on historical ATR volatility
B-Class Signals (Pattern Confirmed)
Trigger: Clear price patterns + volume confirmation
Characteristics: Medium confidence, standard position sizing
Stop Loss: Based on pattern lows/highs
C-Class Signals (Weak Reversal)
Trigger: Single indicator signals + positional support
Characteristics: Lower confidence, small exploratory positions
Stop Loss: Tight stops for quick exits
Scoring Weight Distribution
text
Base Score = Breakout(30%) + Patterns(40%) + Position(30%)
Final Score = Base Score × Market Regime Coefficient × Cloud Position Coefficient
🟠 Risk Management System
Dynamic Stop Loss Strategy
Initial Stop Loss: ATR-based volatility + market regime adjustment
Trailing Stop: Phased tracking, progressively locking profits
Position Management
text
Base Position = Initial Capital × Base Coefficient / Stop Distance
Final Position = Base Position × Signal Strength Coefficient × Market Volatility Coefficient
Take Profit System
Scaled Profit Taking: 8 profit levels with proportional position distribution
Dynamic Adjustment: Trailing stop activation upon reaching specific profit tiers
🟠 Configuration Parameters
Market Regime Thresholds
pinescript
Low Volatility: ≤30 points
Ranging Market: 31-65 points
High Volatility: >65 points
Signal Strength Thresholds
pinescript
// Current Entry Thresholds (No Position)
Low Volatility: Long 82 / Short 82
Ranging: Long 75 / Short 80
High Volatility: Long 80 / Short 85
// Reversal Entry Thresholds
Low Volatility: Long 75 / Short 90
Ranging: Long 85 / Short 90
High Volatility: Long 90 / Short 100
🟠 Usage Guide
1. Initial Setup
Apply to ETH/USDT 15-minute chart
Configure webhook Signal ID and UID
Adjust initial capital parameters according to account size
2. Key Monitoring Elements
Market Regime Indicator: Watch background color changes
Signal Score Display: Monitor real-time long/short scores
POC Value Areas: Identify key support/resistance levels
3. Trading Decision Process
Trend Confirmation Phase:
text
1. Observe market regime background
2. Confirm Ichimoku cloud position
3. Check ADX trend strength
Entry Signal Screening:
text
1. Comprehensive score > corresponding threshold
2. Multiple indicator signal confluence
3. Volume confirmation alignment
Risk Management Execution:
text
1. Automatic position size calculation
2. Set scaled take profit and stop loss
3. Monitor trailing stop updates
4. Advanced Features
Lookback Mode: Historical signal validation
Special Close: Early exit based on ATR ratio
Signal Filtering: Optimize signal quality through component weight adjustment
This systematic multi-factor scoring strategy delivers stable automated trading decisions in complex market environments, particularly well-suited for the short-term volatility characteristics of cryptocurrencies like Ethereum.
Strategy Name: Sunflower Quantitative Strategy
Symbol: ETH/USDT
Timeframe: 15-minute
Market: Cryptocurrency
Strategy Type: Multi-timeframe Quantitative Analysis
Risk Level: Medium-High
Recommended Capital: $10,000+ for optimal position sizing
"向日葵量化"是一款专为ETH 15分钟图表设计的全自动量化交易策略。该策略通过多维度技术分析框架，集成超过20种技术指标与价格行为模式，实现智能化的入场决策与风险控制。
核心价值
多时间框架协同：整合1小时、4小时高周期数据，确保信号质量
动态市场状态识别：实时识别低波动、震荡、高波动三种市场环境
综合评分系统：基于突破信号、形态识别、位置分析的三维评分模型
智能仓位管理：根据信号强度与市场波动率动态调整仓位规模
🟠【核心架构】
策略基于三层分析框架构建：
1. 市场状态识别系统
通过ATR相对波动率、布林带宽、平均振幅、动量强度四个维度，实时判断当前市场环境：
低波动市场（≤30分）：窄幅震荡，等待突破
震荡市场（31-65分）：中等波动，适合区间交易
高波动市场（＞65分）：趋势明确，适合趋势跟踪
2. 信号生成引擎
突破信号层：
DC通道突破（上轨/中轨/下轨）
KC通道突破（上轨/中轨/下轨）
双ATR动量确认
形态识别层：
价格行为模式：外包线、吞没形态、假突破
K线形态：锤子线、倒锤子线、十字星、蜻蜓线、墓碑线
三兵三法：单根强度与三根连续形态
位置分析层：
云图位置关系（之上/之中/之下）
ADX趋势强度确认
DC/KC中轨位置判断
3. 成交量与POC分析
成交量确认：
高成交量突破确认
中等成交量支撑确认
POC价值区域：
基于成交量分布的密集成交区识别
POC集群评分系统（规模分+成交量分+时间分）
🟠【交易逻辑详解】
入场信号分类
A类信号（强势突破）
触发条件：VP突破POC关键位 + 强势形态确认
特征：高置信度，大仓位配置
止损设置：相对宽松，基于ATR历史波动率
B类信号（形态确认）
触发条件：明确价格形态 + 成交量确认
特征：中等置信度，标准仓位
止损设置：基于形态低点/高点
C类信号（弱势反弹）
触发条件：单一指标信号 + 位置支撑
特征：低置信度，小仓位试探
止损设置：紧凑止损，快速离场
评分权重分配
text
基础分 = 突破分(30%) + 形态分(40%) + 位置分(30%)
最终分 = 基础分 × 市场状态系数 × 云图位置系数
🟠【风险管理系统】
动态止损策略
初始止损：基于ATR波动率 + 市场状态调整系数
移动止损：分阶段跟踪，逐级锁定利润
仓位管理
text
基础仓位 = 初始资金 × 基础系数 / 止损距离
最终仓位 = 基础仓位 × 信号强度系数 × 市场波动系数
止盈系统
分级止盈：8个止盈级别，按仓位比例分配
动态调整：达到特定止盈级别后启动移动止损
🟠【配置参数】
市场状态阈值
pinescript
低波动区间：≤30分
震荡区间：31-65分
高波动区间：＞65分
信号强度阈值
pinescript
// 当前开仓阈值（无持仓）
低波动：做多82分 / 做空82分
震荡：做多75分 / 做空80分
高波动：做多80分 / 做空85分
// 反转开仓阈值
低波动：做多75分 / 做空90分
震荡：做多85分 / 做空90分
高波动：做多90分 / 做空100分
🟠【使用指南】
1. 初始设置
添加到ETH/USDT 15分钟图表
配置webhook信号ID和UID
根据资金量调整初始资本参数
2. 监控要点
市场状态指示器：关注背景颜色变化
信号评分显示：实时查看多头/空头得分
POC价值区域：识别关键支撑阻力
3. 交易决策流程
趋势确认阶段：
text
1. 观察市场状态背景色
2. 确认云图位置关系
3. 检查ADX趋势强度
入场信号筛选：
text
1. 综合评分 > 对应阈值
2. 多指标信号共振
3. 成交量确认配合
风险管理执行：
text
1. 自动计算仓位大小
2. 设置分级止盈止损
3. 监控移动止损更新
4. 高级功能
回看模式：启用历史信号验证
特殊平仓：基于ATR比率的提前离场
信号过滤：通过调整各组件权重优化信号质量
该策略通过系统化的多因子评分机制，在复杂的市场环境中实现稳定的自动化交易决策，特别适合ETH等加密货币的短期波动特性。
KDH v2.0 (English) Trading Strategy Indicator# KDH Diamond Strategy v3.3 - TradingView Description
---
## 🇬🇧 ENGLISH VERSION
### 📊 KDH Diamond Strategy v3.3
**Professional High-Leverage Futures Trading System**
---
#### 🎯 Overview
KDH Diamond is an advanced algorithmic trading strategy specifically optimized for **1-hour timeframe futures trading** with high-leverage environments. Built on proven institutional concepts including Fair Value Gaps (FVG), Volume Profile analysis, and multi-layered confirmation filters, this strategy delivers consistent results without repainting.
---
#### ✨ Key Features
**🔥 Optimized for 1H Timeframe**
- Extensively backtested across multiple markets
- Highest profit rate achieved on 1-hour charts
- Perfect for swing traders and active position management
**🎨 No Repainting - 100% Reliable Signals**
- All signals are confirmed and locked on bar close
- What you see in backtest is what you get in real-time
- Complete transparency with `calc_on_order_fills=true`
**💎 Automated Risk Management**
- Automatic Stop Loss and Take Profit calculation
- Intelligent SL/TP placement based on market structure
- Built-in position sizing controls (adjustable % per trade)
**🚀 High-Leverage Futures Optimized**
- Designed specifically for leveraged futures trading
- Risk-reward ratios calibrated for 10-20x leverage environments
- Precision entry timing to maximize profit potential
**🔄 Advanced Position Management**
- Automatic reversal entries at TP levels
- Multiple re-entry opportunities per signal
- Dynamic trade management based on market conditions
**🎛️ Multi-Layer Confirmation System**
- **SMA50 Filter (1H)**: Trend alignment confirmation
- **Momentum Filter**: KAMA-based directional strength
- **RSI Divergence Filter**: Reversal detection at extremes
- **Volume Profile Filter**: Order flow and liquidity analysis
---
#### 📈 How It Works
**Signal Generation**
The strategy identifies **Inverted Fair Value Gaps (IFVG)** - institutional order blocks that signal high-probability reversal or continuation zones. Each signal is validated through multiple confirmation filters before execution.
**Entry Logic**
- Limit orders placed at optimal price levels within FVG zones
- Price must touch the midline and close in favorable direction
- All filters must align for signal activation
**Exit Strategy**
- Stop Loss: Placed at the next opposing FVG level
- Take Profit: Calculated using nearest FVG in profit direction
- Automatic reversal entry option at TP levels
**Visual System**
- Color-coded boxes show FVG zones (green/red)
- Real-time position tracking with entry, SL, and TP lines
- Comprehensive dashboard displaying filter status and P&L
---
#### 🎯 Who Is This For?
✅ **Perfect For:**
- Futures traders using 10-20x leverage
- Traders seeking systematic, rule-based strategies
- Those who want automated SL/TP management
- 1-hour chart swing traders
- Traders familiar with institutional concepts (FVG, order flow)
❌ **Not Ideal For:**
- Scalpers (designed for 1H timeframe)
- Spot-only traders (optimized for leveraged futures)
- Beginners unfamiliar with leverage risks
- Set-and-forget automated trading (requires monitoring)
---
#### 📊 What You Get
**Strategy Features:**
- Complete FVG detection and inversion system
- 4 professional-grade confirmation filters
- Automated SL/TP calculation and placement
- TP reversal entry system
- Volume Profile sentiment analysis
- Real-time position tracking dashboard
- Webhook alert support for automation
- Clean, organized code with detailed comments
**Visual Components:**
- FVG boxes with inversion coloring
- Volume Profile sentiment boxes (optional)
- Entry, SL, and TP lines for each position
- Position status table with live P&L
- Filter status dashboard
---
#### ⚙️ Customization Options
**Adjustable Filters (User Control):**
- SMA50 Filter (1H) - Trend alignment ON/OFF
- Momentum Filter - Directional strength ON/OFF
- RSI Divergence Filter - Reversal detection ON/OFF
- Volume Profile Filter - Order flow analysis ON/OFF
**Fixed Parameters (Optimized):**
- All core parameters are pre-optimized for 1H timeframe
- Ensures consistent performance without overwhelming options
- Prevents parameter over-fitting by users
---
#### ⚠️ Important Disclaimers
**Risk Warning:**
This strategy is designed for leveraged futures trading, which carries substantial risk. High leverage (10-20x) can result in rapid losses. Only trade with capital you can afford to lose.
**Performance:**
Past performance does not guarantee future results. Always backtest on your specific market and timeframe before live trading.
**Usage:**
This is a trading tool, not financial advice. Users are responsible for their own trading decisions and risk management.
**Requirements:**
- Understanding of futures trading and leverage
- Familiarity with Fair Value Gaps and institutional concepts
- Ability to monitor positions (not fully automated)
- Proper risk management discipline
---
#### 🔧 Technical Specifications
- **Platform:** TradingView Pine Script v5
- **Type:** Strategy (with backtesting capabilities)
- **Timeframe:** Optimized for 1H (works on other timeframes)
- **Markets:** Any futures market (crypto, stocks, indices, forex)
- **Repainting:** NO - All signals are final on bar close
- **Alerts:** Full webhook support for automation
- **Default Settings:** 10% position size, pyramiding enabled (max 10 positions)
---
#### 📞 Support
Questions about setup or usage? Contact the author through TradingView messages.
**Note:** This indicator is for educational and trading tool purposes only. The author is not responsible for trading losses. Trade responsibly and within your risk tolerance.
Braid Filter StrategyThis strategy is like a sophisticated set of traffic lights and speed limit signs for trading. It only allows a trade when multiple indicators line up to confirm a strong move, giving it its "Braid Filter" name—it weaves together several conditions.
The strategy is set up to use 100% of your account equity (your trading funds) on a trade and does not "pyramid" (it won't add to an existing trade).
1. The Main Trend Check (The Traffic Lights)
The strategy uses three main filters that must agree before it considers a trade.
A. The "Chad Filter" (Direction & Strength)
This is the heart of the strategy, a custom combination of three different Moving AveragesThese averages have fast, medium, and slow settings (3, 7, and 14 periods).
Go Green (Buy Signal): The fastest average is higher than the medium average, AND the three averages are sufficiently separated (not tangled up, which indicates a strong move).
Go Red (Sell Signal): The medium average is higher than the fastest average, AND the three averages are sufficiently separated.
Neutral (Wait): If the averages are tangled or the separation isn't strong enough.
Key Trigger: A primary condition for a signal is when the Chad Filter changes color (e.g., from Red/Grey to Green).
B. The EMA Trend Bars (Secondary Confirmation)
This is a simpler, longer-term filter using a 34-period Exponential Moving Average (EMA). It checks if the current candle's average price is above or below this EMA.
Green Bars: The price is above the 34 EMA (Bullish Trend).
Red Bars: The price is below the 34 EMA (Bearish Trend).
Trades only happen if the signal direction matches the bar color. For a Buy, the bar must be Green. For a Sell, the bar must be Red.
C. ADX/DI Filter (The Speed Limit Sign)
This uses the Average Directional Index (ADX) and Directional Movement Indicators (DI) to check if a trend is actually in motion and getting stronger.
Must-Have Conditions:
The ADX value must be above 20 (meaning there is a trend, not just random movement).
The ADX line must be rising (meaning the trend is accelerating/getting stronger).
The strategy will only trade when the trend is strong and building momentum.
2. The Trading Action (Entry and Exit)
When all three filters (Chad Filter color change, EMA Trend Bar color, and ADX strength/slope) align, the strategy issues a signal, but it doesn't enter immediately.
Entry Strategy (The "Wait-for-Confirmation" Approach):
When a Buy Signal appears, the strategy sets a "Buy Stop" order at the signal candle's closing price.
It then waits for up to 3 candles (Candles Valid for Entry). The price must move up and hit that Buy Stop price within those 3 candles to confirm the move and enter the trade.
A Sell Signal works the same way but uses a "Sell Stop" at the closing price, waiting for the price to drop and hit it.
Risk Management (Stop Loss and Take Profit):
Stop Loss: To manage risk, the strategy finds a recent significant low (for a Buy) or high (for a Sell) over the last 20 candles and places the Stop Loss there. This is a logical place where the current move would be considered "broken" if the price reaches it.
Take Profit: It uses a fixed Risk:Reward Ratio (set to 1.5 by default). This means the potential profit (Take Profit distance) is $1.50 for every $1.00 of risk (Stop Loss distance).
3. Additional Controls
Time Filter: You can choose to only allow trades during specific hours of the day.
Visuals: It shows a small triangle on the chart where the signal happens and colors the background to reflect the Chad Filter's trend (Green/Red/Grey) and the candle bars to show the EMA trend (Lime/Red).
🎯 Summary of the Strategy's Goal
This strategy is designed to capture strong, confirmed momentum moves. It uses a fast, custom indicator ("Chad Filter") to detect the start of a new move, confirms that move with a slower trend filter (34 EMA), and then validates the move's strength with the ADX. By waiting a few candles for the price to hit the entry level, it aims to avoid false signals.
Braid Filter StrategyAnother of TradeIQ's youtube strategies. It looks a little messy but it combines all the indicators into one so there are no extra panes. This strategy is like a sophisticated set of traffic lights and speed limit signs for trading. It only allows a trade when multiple indicators line up to confirm a strong move, giving it its "Braid Filter" name—it weaves together several conditions.
The strategy is set up to use 100% of your account equity (your trading funds) on a trade and does not "pyramid" (it won't add to an existing trade).
1. The Main Trend Check (The Traffic Lights)
The strategy uses three main filters that must agree before it considers a trade.
A. The "Braid Filter" (Direction & Strength)
This is the heart of the strategy, a custom combination of three different Moving Averages
These averages have fast, medium, and slow settings (3, 7, and 14 periods).
Go Green (Buy Signal): The fastest average is higher than the medium average, AND the three averages are sufficiently separated (not tangled up, which indicates a strong move).
Go Red (Sell Signal): The medium average is higher than the fastest average, AND the three averages are sufficiently separated.
Neutral (Wait): If the averages are tangled or the separation isn't strong enough.
Key Trigger: A primary condition for a signal is when the Chad Filter changes color (e.g., from Red/Grey to Green).
B. The EMA Trend Bars (Secondary Confirmation)
This is a simpler, longer-term filter using a 34-period Exponential Moving Average (EMA). It checks if the current candle's average price is above or below this EMA.
Green Bars: The price is above the 34 EMA (Bullish Trend).
Red Bars: The price is below the 34 EMA (Bearish Trend).
Trades only happen if the signal direction matches the bar color. For a Buy, the bar must be Green. For a Sell, the bar must be Red.
C. ADX/DI Filter (The Speed Limit Sign)
This uses the Average Directional Index (ADX) and Directional Movement Indicators (DI) to check if a trend is actually in motion and getting stronger.
Must-Have Conditions:
The ADX value must be above 20 (meaning there is a trend, not just random movement).
The ADX line must be rising (meaning the trend is accelerating/getting stronger).
The strategy will only trade when the trend is strong and building momentum.
2. The Trading Action (Entry and Exit)
When all three filters (Chad Filter color change, EMA Trend Bar color, and ADX strength/slope) align, the strategy issues a signal, but it doesn't enter immediately.
Entry Strategy (The "Wait-for-Confirmation" Approach):
When a Buy Signal appears, the strategy sets a "Buy Stop" order at the signal candle's closing price.
It then waits for up to 3 candles (Candles Valid for Entry). The price must move up and hit that Buy Stop price within those 3 candles to confirm the move and enter the trade.
A Sell Signal works the same way but uses a "Sell Stop" at the closing price, waiting for the price to drop and hit it.
Risk Management (Stop Loss and Take Profit):
Stop Loss: To manage risk, the strategy finds a recent significant low (for a Buy) or high (for a Sell) over the last 20 candles and places the Stop Loss there. This is a logical place where the current move would be considered "broken" if the price reaches it.
Take Profit: It uses a fixed Risk:Reward Ratio (set to 1.5 by default). This means the potential profit (Take Profit distance) is $1.50 for every $1.00 of risk (Stop Loss distance).
3. Additional Controls
Time Filter: You can choose to only allow trades during specific hours of the day.
Visuals: It shows a small triangle on the chart where the signal happens and colors the background to reflect the Chad Filter's trend (Green/Red/Grey) and the candle bars to show the EMA trend (Lime/Red).
🎯 Summary of the Strategy's Goal
This strategy is designed to capture strong, confirmed momentum moves. It uses a fast, custom indicator ("Chad Filter") to detect the start of a new move, confirms that move with a slower trend filter (34 EMA), and then validates the move's strength with the ADX. By waiting a few candles for the price to hit the entry level, it aims to avoid false signals.
Quasimodo Pattern Strategy Back Test [TradingFinder] QM Trading🔵 Introduction
The QM pattern, also known as the Quasimodo pattern, is one of the popular patterns in price action, and it is often used by technical analysts. The QM pattern is used to identify trend reversals and provides a very good risk-to-reward ratio. One of the advantages of the QM pattern is its high frequency and visibility in charts.
Additionally, due to its strength, it is highly profitable, and as mentioned, its risk-to-reward ratio is very good. The QM pattern is highly popular among traders in supply and demand, and traders also use this pattern.
The Price Action QM pattern, like other Price Action patterns, has two types: Bullish QM and Bearish QM patterns. To identify this pattern, you need to be familiar with its types to recognize it.
🔵 Identifying the QM Pattern
🟣 Bullish QM
In the bullish QM pattern, as you can see in the image below, an LL and HH are formed. As you can see, the neckline is marked as a dashed line. When the price reaches this range, it will start its upward movement.
🟣 Bearish QM
The Price Action QM pattern also has a bearish pattern. As you can see in the image below, initially, an HH and LL are formed. The neckline in this image is the dashed line, and when the LL is formed, the price reaches this neckline. However, it cannot pass it, and the downward trend resumes.
🔵 How to Use
The Quasimodo pattern is one of the clearest structures used to identify market reversals. It is built around the concept of a structural break followed by a pullback into an area of trapped liquidity. Instead of relying on lagging indicators, this pattern focuses purely on price action and how the market reacts after exhausting one side of liquidity. When understood correctly, it provides traders with precise entry points at the transition between trend phases.
🟣 Bullish Quasimodo
A bullish Quasimodo forms after a clear downtrend when sellers start losing control. The market continues to make lower lows until a sudden higher high appears, signaling that buyers are entering with strength. Price then pulls back to retest the previous low, creating what is known as the Quasimodo low.
This area often becomes the final trap for sellers before the market shifts upward. A visible rejection or displacement from this zone confirms bullish momentum. Traders usually place entries near this level, stops below the low, and targets at previous highs or the next resistance zone. Combining the setup with demand zones or Fair Value Gaps increases its accuracy.
🟣 Bearish Quasimodo
A bearish Quasimodo forms near the top of an uptrend when buyers begin to lose strength. The market continues to make higher highs until a sudden lower low breaks the bullish structure, showing that selling pressure is entering the market. Price then retraces upward to retest the previous high, forming the Quasimodo high, where breakout buyers are often trapped.
Once rejection appears at this level, it indicates a likely reversal. Traders can enter short near this area, with stop-losses placed above the high and targets near the next support or previous lows. The setup gains more reliability when aligned with supply zones, SMT divergence, or bearish Fair Value Gaps.
🔵 Setting
Pivot Period : You can use this parameter to use your desired period to identify the QM pattern. By default, this parameter is set to the number 5.
Take Profit Mode : You can choose your desired Take Profit in three ways. Based on the logic of the QM strategy, you can select two Take Profit levels, TP1 and TP2. You can also choose your take profit based on the Reward to Risk ratio. You must enter your desired R/R in the Reward to Risk Ratio parameter.
Stop Loss Refine : The loss limit of the QM strategy is based on its logic on the Head pattern. You can refine it using the ATR Refine option to prevent Stop Hunt. You can enter your desired coefficient in the Stop Loss ATR Adjustment Coefficient parameter.
Reward to Risk Ratio : If you set Take Profit Mode to R/R, you must enter your desired R/R here. For example, if your loss limit is 10 pips and you set R/R to 2, your take profit will be reached when the price is 20 pips away from your entry point.
Stop Loss ATR Adjustment Coefficient : If you set Stop Loss Refine to ATR Refine, you must adjust your loss limit coefficient here. For example, if your buy position's loss limit is at the price of 1000, and your ATR is 10, if you set Stop Loss ATR Adjustment Coefficient to 2, your loss limit will be at the price of 980.
Entry Level Validity : Determines how long the Entry level remains valid. The higher the level, the longer the entry level will remain valid. By default it is 2 and it can be set between 2 and 15.
🔵 Results
The following examples show the backtest results of the Quasimodo (QM) strategy in action. Each image is based on specific settings for the symbol, timeframe, and input parameters, illustrating how the QM logic can generate signals under different market conditions. The detailed configuration for each backtest is also displayed on the image.
⚠ Important Note : Even with identical settings and the same symbol, results may vary slightly across different brokers due to data feed variations and pricing differences.
Default Properties of Backtests :
OANDA:XAUUSD | TimeFrame: 5min | Duration: 1 Year :
BINANCE:BTCUSD | TimeFrame: 5min | Duration: 1 Year :
CAPITALCOM:US30 | TimeFrame: 5min | Duration: 1 Year :
NASDAQ:QQQ | TimeFrame: 5min | Duration: 5 Year :
OANDA:EURUSD | TimeFrame: 5min | Duration: 5 Year :
PEPPERSTONE:US500 | TimeFrame: 5min | Duration: 5 Year :
coinbot_mr_table이 스크립트는 **"MA 리본(Moving Average Ribbon) 기반 자동매매 전략"**입니다.
이름(coinbot_mr_table)에 모든 기능이 요약되어 있습니다.
coinbot: user_id, exchange, leverage 등 자동매매 봇과 연동하기 위한 웹훅(Webhook) 신호 전송 기능이 포함되어 있습니다.
mr (MA Ribbon): 18개(5~90)의 이동평균선(EMA 또는 SMA)이 100 이평선을 기준으로 정배열/역배열되는지를 색상(LIME/RUBI)으로 구분하여 추세를 판단합니다.
table: 전략의 백테스팅 성과(총 승률, 일일 수익률 등)를 차트 위에 '누적 통계'와 '일일 통계' 테이블로 시각화해 줍니다.
이 스크립트의 매매 로직과 자동매매 신호에 대한 자세한 설명을 한글과 영어로 각각 제공해 드립니다.
🇰🇷 한글 (Korean)
이 스크립트는 **"MA 리본(Moving Average Ribbon)"**을 핵심 엔진으로 사용하는 완전 자동매매(Autotrade) 전략 신호 생성기입니다.
이 지표의 목적은 차트에서 추세를 시각적으로 보여주는 것을 넘어, 구체적인 매매 신호(진입, 분할 익절, 손절)가 발생할 때마다 JSON 형식의 명령어를 자동매매 봇으로 전송하는 것입니다.
1. 📈 매매 전략: MA 리본 추세 추종
이 전략은 18개의 단기/중기 이동평균선(5~90)과 1개의 장기 이동평균선(100)을 사용하여 추세를 정의합니다.
100 이평선: 장기 추세를 가르는 기준선(강/약을 나누는 분수령)입니다.
18개 리본: 이 리본들이 100 이평선 위에서 모두 상승(LIME 색상)하면 '강세 추세', 아래에서 모두 하락(RUBI 색상)하면 '약세 추세'로 판단합니다.
2. 🚦 진입 및 청산 신호
이 전략은 '전환(Reversing)' 전략입니다. 즉, 롱 신호가 발생하면 숏 포지션을 종료하고 롱으로 진입하며, 그 반대도 마찬가지입니다. (항상 롱 또는 숏 포지션을 유지합니다.)
진입 신호 (Long):
추세 확정: 모든 리본이 100 이평선 위에서 '강세(LIME)'로 통일될 때.
재진입 (불타기): 강세 추세 중, 리본이 일시적으로 조정(GREEN)을 보이다가 다시 '강세(LIME)'로 복귀할 때.
진입 신호 (Short):
추세 확정: 모든 리본이 100 이평선 아래에서 '약세(RUBI)'로 통일될 때.
재진입 (물타기): 약세 추세 중, 리본이 일시적으로 반등(MAROON)하다가 다시 '약세(RUBI)'로 복귀할 때.
청산 신호 (자동매매):
진입 (ENTRY): 롱/숏 신호 발생 시, 설정한 user_id, exchange, leverage 등을 포함한 JSON 메시지를 전송합니다.
익절 (TAKE_PROFIT): 롱/숏 포지션이 사용자가 설정한 TP1, TP2, TP3 목표가에 도달하면, 설정된 물량(qty_percent)만큼 분할 익절하라는 JSON 메시지를 전송합니다.
손절 (CLOSE): 포지션이 설정한 sl_percent에 도달하면, 포지션을 즉시 종료하라는 JSON 메시지를 전송합니다.
3. 📊 핵심 기능: 통계 테이블
이 스크립트는 백테스팅 성과를 두 개의 테이블로 요약하여 차트에 실시간으로 표시합니다.
누적 통계 (Total Stats): 전체 기간의 총 진입 횟수, 승/패, 승률(Winrate), 총수익률(Total Profit) 등을 보여줍니다.
일일 통계 (Daily Stats): '오늘' 하루 동안 발생한 매매의 성과(승/패, 승률, 수익률)만 따로 집계하여 보여줍니다.
🇺🇸 영어 (English)
This script is an automated trading (Autotrade) strategy signal generator based on a "Moving Average (MA) Ribbon."
Its purpose extends beyond visual trend analysis; it is designed to generate specific JSON-formatted commands and send them to an automated trading bot whenever a trade signal (entry, take-profit, stop-loss) occurs.
1. 📈 Trading Strategy: MA Ribbon Trend Following
This strategy uses 18 short-to-mid-term Moving Averages (5 to 90) and one long-term Moving Average (100) to define the trend.
100-MA: This acts as the baseline filter, dividing the market into a long-term bull or bear state.
18-MA Ribbon: When all 18 ribbons are above the 100-MA and rising (LIME color), it defines a 'Strong Bull Trend'. When all are below the 100-MA and falling (RUBI color), it defines a 'Strong Bear Trend'.
2. 🚦 Entry and Exit Signals
This is a 'Reversing' strategy. This means when a long signal occurs, it closes any existing short position and enters long, and vice-versa. It is designed to hold a position (either long or short) at all times.
Long Entry Signals:
Trend Confirmation: When all ribbons unify into a 'Strong Bull' (LIME) state above the 100-MA.
Re-entry (Buy the Dip): During a bull trend, if the ribbon shows a temporary pullback (GREEN) and then flips back to 'Strong Bull' (LIME).
Short Entry Signals:
Trend Confirmation: When all ribbons unify into a 'Strong Bear' (RUBI) state below the 100-MA.
Re-entry (Sell the Rally): During a bear trend, if the ribbon shows a temporary rally (MAROON) and then flips back to 'Strong Bear' (RUBI).
Exit Signals (For Automation):
ENTRY: When a long/short signal occurs, it sends a JSON message with the user's user_id, exchange, leverage, etc.
TAKE_PROFIT: When a position reaches the user-defined TP1, TP2, or TP3 price targets, it sends a JSON message to take profit on the specified quantity (qty_percent) for that portion.
CLOSE (Stop-Loss): When a position hits the sl_percent threshold, it sends a JSON message to immediately close the entire position.
3. 📊 Key Feature: Statistics Tables
The script provides two real-time summary tables on the chart to visualize backtesting performance.
Cumulative Stats: Shows lifetime performance, including total trades, wins, losses, win rate, and total profit.
Daily Stats: Isolates and displays the performance metrics (wins, losses, win rate, profit) for "Today's" trading activity only.
CEO Synapse v1.0CEO Synapse — Uyarlanabilir Rejim Stratejisi
This script is invite-only.
What Does This Strategy Do?
Markets are complex systems requiring various expertise. The "CEO Synapse" strategy adopts a "digital dashboard" approach based on the reality that a single viewpoint is insufficient. The strategy combines multiple analytical engines, each developed by me, analyzing different aspects of the market (structure, momentum, rhythm). It detects trend and momentum deviations in markets. A trading decision is made only when there is consensus among these expert engines. The "Synapse Engine" uses adaptive filtering and consensus logic for position management based on market regime (trend/range).
It eliminates the problem of traditional indicators generating misleading signals alone and failing to adapt to volatility and regime changes. Its dynamic threshold mechanism, adaptive periods, and special noise filters reduce unnecessary trades.
Original Methodology and Proprietary Logic: This algorithm does not rely on or copy any open source strategy code. The system uses commonly accepted indicators' mathematical principles such as ADX, EMA, SMA, ATR, True Range, etc., as data sources. The author's methodology combines dynamic period EMA, multi-filter consensus, adaptive threshold, and regime-based execution.
Though our strategy creates an original decision-making mechanism, it leverages foundational building blocks of technical analysis. The traditional indicators we use and their purposes are:
ADX (Average Directional Index): This indicator measures a trend’s strength, not its direction. Our strategy uses ADX as a filter to open positions only under sufficiently strong and distinct trend market conditions. This largely prevents misleading signals in weak or sideways markets.
Moving Averages (EMA and SMA): They form the backbone to determine the main trend direction. By smoothing price data, they reduce noise and reveal the market's general trend. But our strategy processes their outputs not as traditional crossover signals, but as input to an advanced consensus logic with dynamically adjusted periods based on market rhythm combined with other filters.
ATR (Average True Range): This indicator does not produce direct buy-sell signals but measures current market volatility. Especially in "Sideways Market" regime, take profit and stop loss levels are dynamically set based on ATR instead of fixed values, enabling risk management to adapt to market conditions.
Bollinger Band Logic (using Standard Deviation): Though the strategy does not plot Bollinger Bands directly, it uses Standard Deviation, the underlying mathematical concept, to detect excessive price deviations and volatility spikes, producing critical signals for the AMF PG core engine.
"Synapse Engine" consists of two layers: Decision Center (Dynamic Threshold) which automatically adjusts risk appetite based on performance and regime; and Filter Committee (Consensus Score) which weights separate filters to produce a single score. This combination is not reproducible and commercially valuable. Closed source is mandatory.
No classic open source code used. Only publicly available indicators are used. Parameters, order, and usage are fully customized.
Generated Signals: Trend/range entry/exit (long/short), adaptive trailing stop position management, additional risk control signals with Shock Absorber and Quantum Filter.
Purpose: Detect trend breaks and momentum deviations. Components: Volatility filters, adaptive signal weighting, EMA/SMA. Methodology: Combines price and volume change rates via dynamic weighting functions.
What Problem Does CEO Synapse Solve?
CEO Synapse addresses three main issues caused by traditional technical analysis and single indicator usage:
Problem: Misleading Signals and Market Noise
Traditional indicators (MACD, RSI, etc.) generate many "false" buy-sell signals, especially in sideways and choppy markets, causing traders to constantly enter and exit positions (whipsaw) and incur losses.
CEO Synapse Solution: The strategy never relies on a single signal. The Consensus-Based Decision Mechanism ensures no position is opened unless different analytical engines (structural, momentum, rhythm) agree. This "board of directors" approach filters market noise, processing only high-probability signals.
Problem: Static Analysis and Changing Market Conditions
Markets constantly change character; sometimes strong trend, sometimes narrow range. Most strategies try to function with fixed parameters across all conditions, leading to failure.
CEO Synapse Solution: The strategy has Adaptive Regime Switching. It actively analyzes whether the market is in "Trend Mode" or "Sideways Market Mode" and automatically adjusts entry/exit rules and risk management (take profit/stop loss) to the current regime, allowing chameleon-like adaptation to conditions.
Problem: Fixed Parameters and Declining Performance
Many traders believe they find the "best" settings and never change them for months or years. But as market volatility and cycles change, fixed settings lose effectiveness.
CEO Synapse Solution: The strategy operates on Full Adaptation principle.
Market Rhythm Adaptation: Dynamically adjusts analysis speed (e.g., EMA periods) according to market’s natural cycles.
Performance Adaptation: Continuously optimizes risk appetite (signal threshold) based on recent strategy performance, becoming bolder with gains and more cautious with losses.
In summary, CEO Synapse simplifies decision-making, eliminates market noise, and smartly adapts to changing market conditions, protecting the user from common mistakes.
Why "Invite-Only"?
Offering CEO Synapse as "Invite-Only" is a strategic decision to protect the strategy's commercial value and intellectual property and to provide users with the highest quality experience. Key reasons:
Protection of Proprietary IP:
CEO Synapse is the result of hundreds of hours of research, development, and testing. Its consensus logic, adaptive threshold mechanism, and engine integration are unique and patented. Open sourcing it would instantly destroy this trade secret and competitive edge.
Maintaining Performance Integrity and Effectiveness:
Uncontrolled distribution could lead to misuse or signal theft and sale by malicious actors. The invite-only model preserves the strategy’s integrity and ensures access only for serious investors.
Quality User Experience and Support:
Controlled distribution allows better user experience. High-quality documentation explaining features and best practices can be provided, and future updates and support services can be managed better for a limited user base.
Business Model:
CEO Synapse is positioned as a premium analysis tool. Invite-only access reflects its value and compensates the developer for ongoing maintenance, support, and future improvements.
Usage: Available on all timeframes.
Based entirely on my own adaptive filtering methodology.
Proprietary logic: The algorithm’s unique, non-reproducible logic and methodology. Example: Multi-filter consensus + adaptive threshold + regime-based execution.
Why Is This a Premium Tool?
"CEO Synapse"’s value stems from being a proprietary, integrated system beyond free standard indicators:
Advanced Noise Filtering: Not just reduces noise but adjusts filter sensitivity to current market character. Inspired by public mathematical concepts (cycle analysis, statistical filtering) but uniquely combined with proprietary weighting mechanisms and adaptive consensus logic forming the strategy's commercial value. Core indicators (EMA, ATR, ADX, DMI, etc.) are uniquely processed inside this proprietary system.
Full Adaptation: Instead of fixed parameters, the strategy continuously adapts to the market's natural rhythm, volatility, and past performance.
Consensus-Based Decision Making: Relies on collective intelligence of multiple analytical engines, not a single failure point.
These features substantially increase the ability to extract meaningful, actionable insights from raw market data, making it premium. It improves signal accuracy, reduces risk, and adapts to regime shifts. The dynamic threshold mechanism continuously adjusts risk appetite based on recent performance (profitability) and market regime.
By using this script, you agree not to redistribute, sell, or reverse engineer the source code.
This strategy is for educational purposes only. Past performance does not guarantee future results. Always apply proper risk management and protect your capital.
Risk Management: Maximum Drawdown Protection
The strategy includes a built-in capital protection mechanism. Users can specify the percentage drop from peak capital they tolerate. If the capital hits this drawdown limit, protection activates, closing all open positions and blocking new trades, acting as an emergency brake to guard capital against unexpected market conditions.
Automation Ready: Customizable Webhook Alerts
Fully Compatible Automation (JSON): The strategy outputs fully configurable JSON-formatted alert messages for buy, sell, and close actions. This allows connecting CEO Synapse signals to automation platforms like 3Commas and PineConnector for fully automated trading. Dynamic values like position size ({{strategy.order.contracts}}) are automatically included in alerts.
Strategy Backtest Information
Please remember past performance is not indicative of future results. The published chart and report are based on the BTCUSD pair in a 3-hour timeframe with the following settings:
Test Period: January 1, 2018 – November 3, 2025
Default Position Size: 15% of capital
Pyramiding: Off
Commission: 0.0008
Slippage: 2 ticks
Test Approach: The published test contains 201 trades and is statistically significant. Performing your own tests on different assets and timeframes is strongly recommended. Default settings are a template and should be adjusted per your analysis.
Mean Reversion Trading V1Overview
This is a simple mean reversion strategy that combines RSI, Keltner Channels, and MACD Histograms to predict reversals. Current parameters were optimized for NASDAQ 15M and performance varies depending on asset. The strategy can be optimized for specific asset and timeframe.
How it works
Long Entry (All must be true):
1. RSI < Lower Threshold
2. Close < Lower KC Band
3. MACD Histogram > 0 and rising
4. No open trades
Short Entry (All must be true):
1. RSI > Upper Threshold
2. Close > Upper KC Band
3. MACD Histogram < 0 and falling
4. No open trades
Long Exit:
1. Stop Loss: Average position size x ( 1 - SL percent)
2. Take Profit: Average position size x ( 1 + TP percent)
3. MACD Histogram crosses below zero
Short Exit:
1. Stop Loss: Average position size x ( 1 + SL percent)
2. Take Profit: Average position size x ( 1 - TP percent)
3. MACD Histogram crosses above zero
Settings and parameters are explained in the tooltips.
Important
Initial capital is set as 100,000 by default and 100 percent equity is used for trades
FluxGate Daily Swing StrategySummary in one paragraph
FluxGate treats long and short as different ecosystems. It runs two independent engines so the long side can be bold when the tape rewards upside persistence while the short side can stay selective when downside is messy. The core reads three directional drivers from price geometry then removes overlap before gating with clean path checks. The complementary risk module anchors stop distance to a higher timeframe ATR so a unit means the same thing on SPY and BTC. It can add take profit breakeven and an ATR trail that only activates after the trade earns it. If a stop is hit the strategy can re enter in the same direction on the next bar with a daily retry cap that you control. Add it to a clean chart. Use defaults to see the intended behavior. For conservative workflows evaluate on bar close.
Scope and intent
• Markets. Large cap equities and liquid ETFs major FX pairs US index futures and liquid crypto pairs
• Timeframes. From one minute to daily
• Default demo in this publication. SPY on one day timeframe
• Purpose. Reduce false starts without missing sustained trends by fusing independent drivers and suppressing activity when the path is noisy
• Limits. This is a strategy. Orders are simulated on standard candles. Non standard chart types are not supported for execution
Originality and usefulness
• Unique fusion. FluxGate extracts three drivers that look at price from different angles. Direction measures slope of a smoothed guide and scales by realized volatility so a point of slope does not mean a different thing on different symbols. Persistence looks at short sign agreement to reward series of closes that keep direction. Curvature measures the second difference of a local fit to wake up during convex pushes. These three are then orthonormalized so a strong reading in one does not double count through another.
• Gates that matter. Efficiency ratio prefers direct paths over treadmills. Entropy turns up versus down frequency into an information read. Light fractal cohesion punishes wrinkly paths. Together they slow the system in chop and allow it to open up when the path is clean.
• Separate long and short engines. Threshold tilts adapt to the skew of score excursions. That lets long engage earlier when upside distribution supports it and keeps short cautious where downside surprise and venue frictions are common.
• Practical risk behavior. Stops are ATR anchored on a higher timeframe so the unit is portable. Take profit is expressed in R so two R means the same concept across symbols. Breakeven and trailing only activate after a chosen R so early noise does not squeeze a good entry. Re entry after stop lets the system try again without you babysitting the chart.
• Testability. Every major window and the aggression controls live in Inputs. There is no hidden magic number.
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close for stability and easy aggregation through time. Realized volatility is the standard deviation of returns over a moving window.
• Range basis for risk. ATR computed on a higher timeframe anchor such as day week or month. That anchor is steady across venues and avoids chasing chart specific quirks.
Components
• Directional intensity. Use an EMA of typical price as a guide. Take the day to day slope as raw direction. Divide by realized volatility to get a unit free measure. Soft clip to keep outliers from dominating.
• Persistence. Encode whether each bar closed up or down. Measure short sign agreement so a string of higher closes scores better than a jittery sequence. This favors push continuity without guessing tops or bottoms.
• Curvature. Fit a short linear regression and compute the second difference of the fitted series. Strong curvature flags acceleration that slope alone may miss.
• Efficiency gate. Compare net move to path length over a gate window. Values near one indicate direct paths. Values near zero indicate treadmill behavior.
• Entropy gate. Convert up versus down frequency into a probability of direction. High entropy means coin toss. The gate narrows there.
• Fractal cohesion. A light read of path wrinkliness relative to span. Lower cohesion reduces the urge to act.
• Phase assist. Map price inside a recent channel to a small signed bias that grows with confidence. This helps entries lean toward the right half of the channel without becoming a breakout rule.
• Shock control. Compare short volatility to long volatility. When short term volatility spikes the shock gate temporarily damps activity so the system waits for pressure to normalize.
Fusion rule
• Normalize the three drivers after removing overlap
• Blend with weights that adapt to your aggression input
• Multiply by the gates to respect path quality
• Smooth just enough to avoid jitter while keeping timing responsive
• Compute an adaptive mean and deviation of the score and set separate long and short thresholds with a small tilt informed by skew sign
• The result is one long score and one short score that can cross their thresholds at different times for the same tape which is a feature not a bug
Signal rule
• A long suggestion appears when the long score crosses above its long threshold while all gates are active
• A short suggestion appears when the short score crosses below its short threshold while all gates are active
• If any required gate is missing the state is wait
• When a position is open the status is in long or in short until the complementary risk engine exits or your entry mode closes and flips
Inputs with guidance
Setup Long
• Base length Long. Master window for the long engine. Typical range twenty four to eighty. Raising it improves selectivity and reduces trade count. Lowering it reacts faster but can increase noise
• Aggression Long. Zero to one. Higher values make thresholds more permissive and shorten smoothing
Setup Short
• Base length Short. Master window for the short engine. Typical range twenty eight to ninety six
• Aggression Short. Zero to one. Lower values keep shorts conservative which is often useful on upward drifting symbols
Entries and UI
• Entry mode. Both or Long only or Short only
Complementary risk engine
• Enable risk engine. Turns on bracket exits while keeping your signal logic untouched
• ATR anchor timeframe. Day Week or Month. This sets the structural unit of stop distance
• ATR length. Default fourteen
• Stop multiple. Default one point five times the anchor ATR
• Use take profit. On by default
• Take profit in R. Default two R
• Breakeven trigger in R. Default one R
Usage recipes
Intraday trend focus
• Entry mode Both
• ATR anchor Week
• Aggression Long zero point five Aggression Short zero point three
• Stop multiple one point five Take profit two R
• Expect fewer trades that stick to directional pushes and skip treadmill noise
Intraday mean reversion focus
• Session windows optional if you add them in your copy
• ATR anchor Day
• Lower aggression both sides
• Breakeven later and trailing later so the first bounce has room
• This favors fade entries that still convert into trends when the path stays clean
Swing continuation
• Signal timeframe four hours or one day
• Confirm timeframe one day if you choose to include bias
• ATR anchor Week or Month
• Larger base windows and a steady two R target
• This accepts fewer entries and aims for larger holds
Properties visible in this publication
• Initial capital 25.000
• Base currency USD
• Default order size percent of equity value three - 3% of the total capital
• Pyramiding zero
• Commission zero point zero three percent - 0.03% of total capital
• Slippage five ticks
• Process orders on close off
• Recalculate after order is filled off
• Calc on every tick off
• Bar magnifier off
• Any request security calls use lookahead off everywhere
Realism and responsible publication
• No performance promises. Past results never guarantee future outcomes
• Fills and slippage vary by venue and feed
• Strategies run on standard candles only
• Shapes can update while a bar is forming and settle on close
• Keep risk per trade sensible. Around one percent is typical for study. Above five to ten percent is rarely sustainable
Honest limitations and failure modes
• Sudden news and thin liquidity can break assumptions behind entropy and cohesion reads
• Gap heavy symbols often behave better with a True Range basis for risk than a simple range
• Very quiet regimes can reduce score contrast. Consider longer windows or higher thresholds when markets sleep
• Session windows follow the exchange time of the chart if you add them
• If stop and target can both be inside a single bar this strategy prefers stop first to keep accounting conservative
Open source reuse and credits
• No reused open source beyond public domain building blocks such as ATR EMA and linear regression concepts
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on history and in simulation with realistic costs
