MA Strategy: Dual Entry FilterConfigurable MA Dual-Filter Strategy
This strategy is an enhanced and highly configurable Moving Average (MA) Crossover system designed to mitigate false signals and align trades with the prevailing market trend. It is built to offer traders granular control over entry criteria, elevating it beyond basic, built-in MA crossover indicators.
Originality & Key Features
The script's originality and utility lie in the combination of its two primary, optional filtering mechanics:
Dual Entry Mode (Key Filter): Users can choose between two distinct methods for trade entry:
Crossover (Classic): Immediate entry when the price crosses the main MA.
Full Candle Confirmation (Unique Feature): This mode requires the entire candle body (open, high, low, and close) to be completely above or below the main MA after a crossover event to confirm the signal before entry. This strict confirmation helps to filter out weak crossovers, reducing whipsaws in choppy markets.
Optional Trend Filter: A second, slower MA (Trend Filter MA) can be activated. Trades are only permitted when the faster main MA is aligned with the slower Trend MA (i.e., long only if main MA > Trend MA), ensuring trades are executed with the established higher-timeframe direction.
How to Use the Strategy
The strategy logic is built on simple MA principles but utilizes Pine Script's switch function to allow users to select from six different MA types for both the main signal and the trend filter: SMA, EMA, WMA, HMA, VWMA, and RMA.
Core Logic:
Signal: A cross of the price over the Main MA (filtered by the chosen Entry Mode).
Directional Filter: The Trend Filter must confirm the direction (if enabled).
Exit: Trades are exited on the opposite price crossover of the Main MA.
Customizable Settings Include:
Main MA Type & Length (Default: 40 EMA): The primary signal generator.
Trend Filter MA Type & Length (Default: 70 EMA): The optional, slower trend bias.
Entry Mode: Switch between Crossover or Full Candle Confirmation.
Strategy Results and High-Risk Disclaimer
The default setting for trade size is set to 40% of equity for backtesting demonstration purposes only. This high value is used to generate a large and diverse sample size of trades for historical review on the chart.
This 40% value is NOT a recommended setting for live trading. Per TradingView guidelines, traders are strongly advised to change this input to a sustainable risk level, typically 5% to 10% of equity per trade. Past performance is not a guarantee of future results.
אינדיקטורים ואסטרטגיות
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
ChronoPulse MS-MACD Resonance StrategyChronoPulse MS-MACD Resonance Strategy
A systematic trading strategy that combines higher-timeframe market structure analysis with dual MACD momentum confirmation, ATR-based risk management, and real-time quality assurance monitoring.
Core Principles
The strategy operates on the principle of multi-timeframe confluence, requiring agreement between:
Market structure breaks (CHOCH/BOS) on a higher timeframe
Dual MACD momentum confirmation (classic and crypto-tuned profiles)
Trend alignment via directional EMAs
Volatility and volume filters
Quality score composite threshold
Strategy Components
Market Structure Engine : Detects Break of Structure (BOS) and Change of Character (CHOCH) events using confirmed pivots on a configurable higher timeframe. Default structure timeframe is 240 minutes (4H).
Dual MACD Fusion : Requires agreement between two MACD configurations:
Classic MACD: 12/26/9 (default)
Fusion MACD: 8/21/5 (default, optimized for crypto volatility)
Both must agree on direction before trade execution. This can be disabled to use single MACD confirmation.
Trend Alignment : Uses two EMAs for directional bias:
Directional EMA: 55 periods (default)
Execution Trend Guide: 34 periods (default)
Both must align with trade direction.
ATR Risk Management : All risk parameters are expressed in ATR multiples:
Stop Loss: 1.5 × ATR (default)
Take Profit: 3.0 × ATR (default)
Trail Activation: 1.0 × ATR profit required (default)
Trail Distance: 1.5 × ATR behind price (default)
Volume Surge Filter : Optional gate requiring current volume to exceed a multiple of the volume SMA. Default threshold is 1.4× the 20-period volume SMA.
Quality Score Gate : Composite score (0-1) combining:
Structure alignment (0.0-1.0)
Momentum strength (0.0-1.0)
Trend alignment (0.0-1.0)
ATR volatility score (0.0-1.0)
Volume intensity (0.0-1.0)
Default threshold: 0.62. Trades only execute when quality score exceeds this threshold.
Execution Discipline : Trade budgeting system:
Maximum trades per session: 6 (default)
Cooldown bars between entries: 5 (default)
Quality Assurance Console : Real-time monitoring panel displaying:
Structure status (pass/fail)
Momentum confirmation (pass/fail)
Volatility readiness (pass/fail)
Quality score (pass/fail)
Discipline compliance (pass/fail)
Performance metrics (win rate, profit factor)
Net PnL
Certification requires: Win Rate ≥ 40%, Profit Factor ≥ 1.4, Minimum 25 closed trades, and positive net profit.
Integrity Suite : Optional validation panel that audits:
Configuration sanity checks
ATR data readiness
EMA hierarchy validity
Performance realism checks
Strategy Settings
strategy(
title="ChronoPulse MS-MACD Resonance Strategy",
shorttitle="ChronPulse",
overlay=true,
max_labels_count=500,
max_lines_count=500,
initial_capital=100000,
currency=currency.USD,
pyramiding=0,
commission_type=strategy.commission.percent,
commission_value=0.015,
slippage=2,
default_qty_type=strategy.percent_of_equity,
default_qty_value=2.0,
calc_on_order_fills=true,
calc_on_every_tick=true,
process_orders_on_close=true
)
Key Input Parameters
Structure Timeframe : 240 (4H) - Higher timeframe for structure analysis
Structure Pivot Left/Right : 3/3 - Pivot confirmation periods
Structure Break Buffer : 0.15% - Buffer for structure break confirmation
MACD Fast/Slow/Signal : 12/26/9 - Classic MACD parameters
Fusion MACD Fast/Slow/Signal : 8/21/5 - Crypto-tuned MACD parameters
Directional EMA Length : 55 - Primary trend filter
Execution Trend Guide : 34 - Secondary trend filter
ATR Length : 14 - ATR calculation period
ATR Stop Multiplier : 1.5 - Stop loss in ATR units
ATR Target Multiplier : 3.0 - Take profit in ATR units
Trail Activation : 1.0 ATR - Profit required before trailing
Trail Distance : 1.5 ATR - Distance behind price
Volume Threshold : 1.4× - Volume surge multiplier
Quality Threshold : 0.62 - Minimum quality score (0-1)
Max Trades Per Session : 6 - Daily trade limit
Cooldown Bars : 5 - Bars between entries
Win-Rate Target : 40% - Minimum for QA certification
Profit Factor Target : 1.4 - Minimum for QA certification
Minimum Trades for QA : 25 - Required closed trades
Signal Generation Logic
A trade signal is generated when ALL of the following conditions are met:
Higher timeframe structure shows bullish (CHOCH/BOS) or bearish structure break
Both MACD profiles agree on direction (if fusion enabled)
Price is above both EMAs for longs (below for shorts)
ATR data is ready and above minimum threshold
Volume exceeds threshold × SMA (if volume gate enabled)
Quality score ≥ quality threshold
Trade budget available (under max trades per day)
Cooldown period satisfied
Risk Management
Stop loss and take profit are set immediately on entry
Trailing stop activates after 1.0 ATR of profit
Trailing stop maintains 1.5 ATR distance behind highest profit point
Position sizing uses 2% of equity per trade (default)
No pyramiding (single position per direction)
Limitations and Considerations
The strategy requires sufficient historical data for higher timeframe structure analysis
Quality gate may filter out many potential trades, reducing trade frequency
Performance metrics are based on historical backtesting and do not guarantee future results
Commission and slippage assumptions (0.015% + 2 ticks) may vary by broker
The strategy is optimized for trending markets with clear structure breaks
Choppy or ranging markets may produce false signals
Crypto markets may require different parameter tuning than traditional assets
Optimization Notes
The strategy includes several parameters that can be tuned for different market conditions:
Quality Threshold : Lower values (0.50-0.60) allow more trades but may reduce average quality. Higher values (0.70+) are more selective but may miss opportunities.
Structure Timeframe : Use 240 (4H) for intraday trading, Daily for swing trading, Weekly for position trading
Volume Gate : Disable for low-liquidity pairs or when volume data is unreliable
Dual MACD Fusion : Disable for mean-reverting markets where single MACD may be more responsive
Trade Discipline : Adjust max trades and cooldown based on your risk tolerance and market volatility
Non-Repainting Guarantee
All higher timeframe data requests use lookahead=barmerge.lookahead_off to prevent repainting. Pivot detection waits for full confirmation before registering structure breaks. All visual elements (tables, labels) update only on closed bars.
Alerts
Three alert conditions are available:
ChronoPulse Long Setup : Fires when all long entry conditions are met
ChronoPulse Short Setup : Fires when all short entry conditions are met
ChronoPulse QA Certification : Fires when Quality Assurance console reaches CERTIFIED status
Configure alerts with "Once Per Bar Close" delivery to match the non-repainting design.
Visual Elements
Structure Labels : CHOCH↑, CHOCH↓, BOS↑, BOS↓ markers on structure breaks
Directional EMA : Orange line showing trend bias
Trailing Stop Lines : Green (long) and red (short) trailing stop levels
Dashboard Panel : Real-time status display (structure, MACD, ATR, quality, PnL)
QA Console : Quality assurance monitoring panel
Integrity Suite Panel : Optional validation status display
Recommended Usage
Forward test with paper trading before live deployment
Monitor the QA console until it reaches CERTIFIED status
Adjust parameters based on your specific market and timeframe
Respect the trade discipline limits to avoid over-trading
Review quality scores and adjust threshold if needed
Use appropriate commission and slippage settings for your broker
Technical Implementation
The strategy uses Pine Script v6 with the following key features:
Multi-timeframe data requests with lookahead protection
Confirmed pivot detection for structure analysis
Dynamic trailing stop management
Real-time quality score calculation
Trade budgeting and cooldown enforcement
Comprehensive dashboard and monitoring panels
All source code is open and available for review and modification.
Disclaimer
This script is for educational and informational purposes only. It is not intended as financial, investment, or trading advice. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author and TradingView are not responsible for any losses incurred from using this strategy.
NSE Bullish Swing Strategy - 7-8% TargetHelps capture bullish swing trading set ups ( PULL BACK , BREAKOUT & MOMENTUM ) and achieve 7-8 % profit in minimum possible time. Also scans the trend continuously & gives the strength of the trend. Use in daily time frame.
Only for educational use.
VWolf – Slope GuardOVERVIEW
Slope Guard combines a momentum core (WaveTrend + RSI/MFI + QQE family) with a directional bias (EMA/DEMA and a DEMA-slope filter). Trade direction can be constrained by the Supertrend regime (Normal or Pivot). Risk is managed with ATR-based stops and targets, optional Supertrend-anchored dynamic levels, and a two-stage take-profit that can shift the stop to break-even after the first partial. The strategy supports explicit Backtest and Forward-test windows and adapts certain thresholds by market type (Forex vs. Stocks).
RECOMMENDED USE
Markets: Forex and equities; use Market Type to properly scale the DEMA-slope gate.
Timeframes: M15–H4 for intraday-swing and H1–D1 for slower swing; avoid ultra-low TFs without tightening ADX/QQE.
Assets: Instruments with persistent trends and orderly pullbacks; avoid flat ranges without sufficient ADX.
Strengths
Multi-layer confluence: trend bias + momentum + regime + strength.
Flexible risk engine: ATR vs. Supertrend anchoring, staged exits, and automatic break-even.
Clean research workflow: separated Backtest and Forward-test windows.
Precautions
Structural latency: Pivot-based constructs confirm with delay; validate with Forward-test.
Filter interaction: QQE Strict + ADX + WT zero-line can become overly selective; calibrate by asset/TF.
Overfitting risk: Prefer simple, portable parameter sets and validate across symbols/TFs.
CONCLUSION
Slope Guard is a “trend + momentum” framework with risk control at its core. By enforcing a baseline bias, validating momentum with the Vuman composite, and offering ATR or Supertrend-anchored exits—plus staged profits and break-even shifts—it seeks to capture the core of directional swings while compressing drawdowns. Keep testing windows isolated, start with moderate filters (QQE Normal, ADX ~20–25), and only add stricter gates (WT zero-line, DEMA slope) once they demonstrably improve stability without starving signals.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Shadow PulseOVERVIEW
The Trend Momentum Breakout Strategy is a rule-based trading system designed to identify high-probability entries in trending markets using a combination of trend confirmation, momentum filtering, and precise trigger conditions. The strategy is suitable for intermediate to advanced traders who prefer mechanical systems with clear entry/exit logic and configurable risk management options.
At its core, this strategy seeks to enter pullbacks within strong trends, capitalizing on momentum continuation after brief pauses in price movement. By integrating multiple moving averages (MAs) for trend validation, ADX (Average Directional Index) as a strength filter, and Stochastic RSI as an entry trigger, the strategy filters out weak trends and avoids overextended market conditions. Exit logic is based on a customizable fixed stop-loss (SL) and take-profit (TP) framework, with optional dynamic risk-reduction mechanisms powered by the Supertrend indicator.
This strategy is designed to perform best in clearly trending markets and is especially effective in avoiding false breakouts or choppy sideways action thanks to its ADX-based filtering. It can be deployed across a variety of asset classes, including forex, stocks, cryptocurrencies, and indices, and is optimized for intra-day to swing trading timeframes.
RECOMMENDED USE
This strategy is designed to be flexible across multiple markets, but it performs best under certain conditions:
Best Suited For:
Trending markets with clear directional momentum.
High-volume instruments that avoid erratic price action.
Assets with intraday volatility and swing patterns.
Recommended Asset Classes:
Forex pairs (e.g., EUR/USD, GBP/JPY)
Cryptocurrencies (e.g., BTC/USD, ETH/USDT)
Major indices (e.g., S&P 500, NASDAQ, DAX)
Large-cap stocks (especially those with consistent liquidity)
Suggested Timeframes:
15-minute to 1-hour charts for intraday setups.
4-hour and daily charts for swing trading.
Lower timeframes (1–5 min) may generate too much noise unless fine-tuned.
Market Conditions to Avoid:
Ranging or sideways markets with low ADX values.
Assets with irregular price structures or low liquidity.
News-heavy periods with unpredictable price spikes.
CONCLUSION
This strategy stands out for its robust and modular approach to trend-following trading, offering a high level of customization while maintaining clear logic and structural discipline in entries and exits. By combining three distinct layers of confirmation—trend identification (via configurable moving averages), trend strength validation (via the DMI filter), and timing (via the Stochastic RSI trigger)—it aims to reduce noise and increase the probability of entering trades with directional bias and momentum on its side.
Its flexibility is one of its strongest points: users can tailor the strategy to fit various trading styles and market conditions. Whether the trader prefers conservative setups using only the slowest moving average, or more aggressive entries requiring full alignment of fast, medium, and slow MAs, the system adjusts accordingly. Likewise, exit management offers both static and dynamic methods—such as ATR-based stop losses, Supertrend-based adaptive exits, and partial profit-taking mechanisms—allowing risk to be managed with precision.
This makes the strategy particularly suitable for trend-driven markets, such as major currency pairs, indices, or volatile stocks that demonstrate clear directional moves. It is not ideal for sideways or choppy markets, where multiple filters may reduce the number of trades or result in whipsaws.
From a practical standpoint, the strategy also incorporates real-world trading mechanics, like time-based filters and account risk control, which elevate it from a purely theoretical model to a more execution-ready system.
In summary, this is a well-structured, modular trend strategy ideal for intermediate to advanced traders who want to maintain control over their system parameters while still benefiting from layered signal confirmation. With proper calibration, it has the potential to become a reliable tool in any trader’s arsenal—particularly in markets where trends emerge clearly and sustainably.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Raptor ClawOVERVIEW
The 'VWolf - Raptor Claw' is a straightforward scalping strategy designed for high-frequency trades based on the Stochastic RSI indicator. It focuses exclusively on identifying potential trend reversals through stochastic cross signals in extreme zones, without the need for additional confirmations. This makes it highly responsive to market movements, capturing rapid price shifts while maintaining simplicity.
This strategy is best suited for highly liquid and volatile markets like forex, indices, and major cryptocurrencies, where quick momentum shifts are common. It is ideal for experienced scalpers who prioritize fast entries and exits, but it can also be adapted for swing trading in lower timeframes.
Entry Conditions:
Long Entry:Stochastic RSI crosses above the oversold threshold (typically 20), indicating a potential bullish reversal.
Short Entry:Stochastic RSI crosses below the overbought threshold (typically 80), indicating a potential bearish reversal.
Exit Conditions:
Stop Loss: Set at the minimum (for longs) or maximum (for shorts) within a configurable lookback window to reduce risk.
Take Profit: Defined by a risk-reward ratio (RRR) input to optimize potential gains relative to risk.
CONCLUSION
The 'VWolf - Raptor Claw' strategy is perfect for traders seeking a simple yet aggressive approach to the markets. It capitalizes on sharp momentum shifts in extreme zones, relying on precise stop loss and take profit settings to capture rapid profits while minimizing risk. This approach is highly effective in high-volatility environments where quick decision-making is essential.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Quantum DriftOVERVIEW
The Quantum Drift strategy is a sophisticated, highly customizable trading approach designed to identify market entries and exits by leveraging multiple technical indicators. The strategy uniquely combines the Dynamic Exponential Moving Average (DEMA), QQE indicators, Volume Oscillator, and Hull Moving Average (HULL), enabling precise detection of trend direction, momentum shifts, and volatility adjustments. It stands out due to its adaptability across different market conditions by allowing significant user customization through various input parameters.
RECOMMENDED USE
Markets: Ideal for Forex and Stocks due to the strategy's volatility-sensitive and trend-following nature.
Timeframes: Best suited for medium to higher timeframes (15m, 1H, 4H), where clearer trend signals and less noise occur, enhancing strategy reliability.
CONCLUSION
The Quantum Drift strategy is tailored for intermediate to advanced traders seeking a versatile and adaptive system. Its strength lies in combining momentum, volatility, and trend-following components, providing robust entry and exit signals. However, its effectiveness relies significantly on accurate parameter tuning by traders familiar with the underlying indicators and market behavior.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf – Pivot VumanSkewOVERVIEW
This strategy blends a lightweight trend scaffold (EMA/DEMA) with a skew-of-volatility filter and VuManchu/WaveTrend momentum signals. It’s designed to participate only when trending structure, momentum alignment, and volatility asymmetry converge, while delegating execution management to either a standard SuperTrend or a Pivot-based SuperTrend. Position sizing is risk‑based, with optional two‑step profit taking and automatic stop movement once price confirms in favor.
RECOMMENDED USE
Markets: Designed for Forex and equities, and readily adaptable to indices or liquid futures.
Timeframes: Performs best from 15m to 4h where momentum and trend layers both matter; daily can be used for confirmation/context.
Conditions: Trending or range‑expansion phases with clear volatility asymmetry. Avoid extremely compressed sessions unless thresholds are relaxed.
Strengths
Multi‑layer confluence (trend + skew + momentum) reduces random signals.
Dual SuperTrend modes provide flexible trailing and regime control.
Built‑in hygiene (ADX/DMI, lockout after loss, ATR gap) curbs over‑trading.
Risk‑% sizing and two‑step exits support consistent, plan‑driven execution.
Precautions
Over‑tight thresholds can lead to missed opportunities; start from defaults and tune gradually.
High sensitivity in momentum settings may overfit to a single instrument/timeframe.
In very low volatility, ATR‑gap or skew filters may block entries—consider adaptive thresholds.
CONCLUSION
VWolf – Pivot VumanSkew is a disciplined trend‑participation strategy that waits for directional structure, volatility asymmetry, and synchronized momentum before acting. Its execution layer—selectable between Normal and Pivot SuperTrend—keeps management pragmatic: scale out early when appropriate, trail intelligently, and defend capital with volatility‑aware stops. For users building a diversified playbook, Pivot VumanSkew serves as a trend‑continuation workhorse that can be tightened for precision or relaxed for higher participation depending on the market’s rhythm.
VWolf – Momentum TwinOVERVIEW
VWolf – Momentum Twin is designed to identify high-probability momentum reversals emerging from overbought or oversold market conditions. It employs a double confirmation from the Stochastic RSI oscillator, optionally filtered by trend and directional movement conditions, before executing trades.
The strategy emphasizes consistent risk management by scaling stop-loss and take-profit targets according to market volatility (ATR), and it provides advanced position management features such as partial profit-taking and automated stop-loss adjustments.
RECOMMENDED USE
Markets: Major FX pairs, index futures, large-cap stocks, and top-volume cryptocurrencies.
Timeframes: Best suited for M15–H4; adaptable for swing trading on daily charts.
Trader Profile: Traders who value structured, volatility-adjusted momentum reversal setups.
Strengths:
Double confirmation filters out many false signals.
Multiple filter options allow strategic flexibility.
ATR scaling maintains consistent risk across assets.
Trade management tools improve adaptability in dynamic markets.
Precautions:
May produce fewer trades in strong one-direction trends.
Over-filtering can reduce trade frequency.
Requires validation across instruments and timeframes before deployment.
CONCLUSION
The VWolf – Momentum Twin offers a disciplined framework for capturing momentum reversals while preserving flexibility through its customizable filters and risk controls. Its double confirmation logic filters out a significant portion of false reversals, while ATR-based scaling ensures consistency across varying market conditions. The optional trade management features, including partial profit-taking and automatic stop adjustments, allow the strategy to adapt to both trending and ranging environments. This makes it a versatile tool for traders who value structured entries, robust risk control, and adaptable management in a variety of markets and timeframes.
VWolf – Hull VectorOVERVIEW
VWolf – Hull Vector is a momentum-driven trend strategy centered on the Hull Moving Average (HMA) angle. It layers optional confirmations from EMA/DEMA alignment, DMI/ADX strength, and Supertrend triggers to filter lower-quality entries and improve trade quality.
Risk is controlled through capital-based position sizing, ATR-anchored stops and targets, and dynamic trade management (partial exits and stop movement). The strategy supports Backtest and Forwardtest modes with configurable date ranges, and a market profile toggle (Forex vs. Stocks) to adjust internal scaling for price behavior.
RECOMMENDED USE
Markets: Major Forex pairs, index CFDs/futures, and liquid stocks with clean trend legs.
Styles: Intraday and swing applications where momentum continuation is common.
Volatility Regimes: Performs best in trending or expanding-volatility environments; consider tightening thresholds in choppy phases.
Workflow Tips:Start with HMA angle + ST trigger only; then layer DEMA and DMI/ADX if you need more selectivity.
Use Forwardtest dates to simulate out-of-sample performance after tuning Backtest parameters.
Re-evaluate angle thresholds when switching between Forex and Stocks modes.
Strengths
Clear momentum core (HMA angle) with optional, orthogonal filters (trend alignment, strength, trigger).
Robust risk tooling: ATR/ST stops, two-step profits, and capital-based sizing.
Testing discipline: Native Backtest/Forwardtest scoping supports walk-forward validation.
Broad portability: Works across instruments thanks to market-aware scaling.
Precautions
Over-filtering risk: Enabling all gates simultaneously may under-trade; calibrate selectivity to your timeframe.
Sideways markets: Expect more whipsaws when slope hovers near zero; raise angle threshold or rely more on ADX gating.
Overfitting hazard: Tune on one regime, then verify with Forwardtest windows and alternative markets/timeframes.
VWolf – Hulk StrikeOVERVIEW
VWolf – Hullk Strike is a dynamic trend-following strategy designed to capture pullbacks within established moves. It combines a configurable Moving Average (HULL, EMA, SMA, or DEMA) trend filter with DMI/ADX confirmation and a Stochastic RSI timing trigger. Risk is managed through ATR- or Supertrend-based stops, optional partial profit-taking, and automatic stop adjustments. The strategy aims to rejoin momentum after controlled retracements while maintaining consistent, quantified risk
RECOMMENDED USE
Markets: Liquid indices, major FX pairs, large-cap equities, high-liquidity crypto pairs.
Timeframes: M15 to D1 (stricter filters for lower timeframes, looser for higher).
Profiles: Traders seeking structured trend participation with systematic timing.
Strengths
Highly flexible trend engine adaptable to multiple markets.
Dual confirmation reduces false signals during pullbacks.
Risk-first design with multiple stop models and partial exits.
Precautions
Over-filtering may reduce trade frequency and miss fast continuations.
Under-filtering may increase whipsaw risk in choppy markets.
Backtest vs forward-test differences if date/session filters are inconsistent.
CONCLUSION
VWolf – Hullk Strike is designed to capture the “second leg” of a trend after a controlled retracement. With configurable MA strictness, DMI/ADX strength filters, and precise Stoch RSI timing, it enhances selectivity while keeping responsiveness. Its stop/target framework—anchored stops, proportional targets, partial exits, and dynamic stop moves—offers disciplined risk control and upside preservation.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf – EquinoxOVERVIEW
The VWolf – Equinox strategy integrates multiple technical filters, skew deviation logic, and advanced momentum indicators to identify high-probability trend continuation and reversal setups. Built upon the Vumanchu framework, this strategy applies filters such as EMA, DEMA, Supertrend, QQE, ADX/DMI, and customized skew thresholds. It combines these with divergence detection, volatility conditions, and risk-managed trade execution for dynamic adaptability across market conditions.
Its architecture is designed to provide flexibility for both backtesting and forward testing periods, while allowing traders to fine-tune entry confirmations and risk management tools based on their preferred market or timeframe.
RECOMMENDED USE
Markets: Forex, equities, and potentially crypto markets due to skew/volatility adaptability.
Timeframes: Works best on intraday (15m–1H) and swing-trading (4H–1D) horizons.
Trader Profile: Suited for intermediate to advanced traders who value multiple confirmation layers and dynamic risk management.
Strengths:
Robust filter system reduces false signals.
Flexible exit strategies with dynamic profit-taking.
Adaptability across different assets and timeframes.
Precautions:
Complexity may overwhelm beginners; careful parameter tuning is recommended.
Too many active filters can reduce signal frequency, potentially missing opportunities.
Divergence and skew thresholds require calibration to each market’s volatility regime.
CONCLUSION
The VWolf – Equinox stands out as one of the most comprehensive strategies in the VWolf library, combining skew deviation with a wide array of technical filters. Its layered confirmation system reduces noise and improves reliability across volatile markets. While powerful, its effectiveness depends on thoughtful parameter selection and disciplined risk management. This makes it a strong candidate for experienced traders seeking depth, adaptability, and dynamic trade control.
FOR MORE INFORMATION VISIT vwolftrading.com
VWolf - Basic EdgeOVERVIEW
VWolf - Basic Edge is a clean and accessible crossover strategy built on the core principle of moving average convergence. Designed for simplicity and ease of use, it allows traders to select from multiple types of moving averages—including EMA, SMA, HULL, and DEMA—and defines entry points strictly based on the crossover of two user-defined MAs.
This strategy is ideal for traders seeking a minimal, no-frills trend-following system with flexible exit conditions. Upon crossover in the selected direction (e.g., fast MA crossing above slow MA for a long entry), the strategy opens a trade and then manages the exit based on the user’s chosen method:
Signal-Based Exit:Trades are closed on the opposite crossover signal (e.g., long is exited when the fast MA crosses below the slow MA).
Fixed SL/TP Exit:The trade is closed based on fixed Stop Loss and Take Profit levels.Both SL and TP values are customizable via the strategy’s input settings.Once either the TP or SL is reached, the position is exited.
Additional filters such as date ranges and session times are available for backtesting control, but no extra indicators are used—staying true to the “basic edge” philosophy. This strategy works well as a starting framework for beginners or as a reliable, lightweight system for experienced traders wanting clean, rule-based entries and exits.
RECOMMENDED FOR
- Beginner to intermediate traders who want a transparent and easy-to-follow system.
- Traders looking to understand or build upon classic moving average crossover logic.
- Users who want a customizable but uncluttered strategy framework.
🌍 Markets & Instruments:
Well-suited for liquid and trending markets, including:Major forex pairs
Stock indices
Commodities (e.g., gold, oil)
Cryptocurrencies with stable trends (e.g., BTC, ETH)
⏱ Recommended Timeframes:
Performs best on higher intraday or swing trading timeframes, such as:15m, 1h, 4h, and 1D
Avoid low-timeframe noise (e.g., 1m, 3m) unless paired with strict filters or volatility controls.
FOR MORE INFORMATION VISIT vwolftrading.com
ATR ZigZag BreakoutATR ZigZag Breakout
This strategy uses my ATR ZigZag indicator (powered by the ZigZagCore library) to scalp breakouts at volatility-filtered highs and lows.
Everyone knows stops cluster around clear swing highs and lows. Breakout traders often pile in there, too. These levels are predictable areas where aggressive orders hit the tape. The idea here is simple:
→ Let ATR ZigZag define clean, volatility-filtered pivots
→ Arm a stop market order at those pivots
→ Join the breakout when the crowd hits the level
The key to greater success in this simple strategy lies in the ZigZag. Because the pivots are filtered by ATR instead of fixed bar counts or fractals, the levels tend to be more meaningful and less noisy.
This approach is especially suited for intraday trading on volatile instruments (e.g., NQ, GC, liquid crypto pairs).
How It Works
1. Pivot detection
The ATR ZigZag uses an ATR-based threshold to confirm swing highs and lows. Only when price has moved far enough in the opposite direction does a pivot become “official.”
2. Candidate breakout level
When a new swing direction is detected and the most recent high/low has not yet been broken in the current leg, the strategy arms a stop market order at that pivot.
• Long candidate → most recent swing high
• Short candidate → most recent swing low
These “candidate trades” are shown as dotted lines.
3. Entry, SL, and TP
If price breaks through the level, the stop order is filled and a bracket is placed:
• Stop loss = ATR × SL multiplier
• Take profit = SL distance × RR multiplier
Once a level has traded, it is not reused in the same swing leg.
4. Cancel & rotate
If the market reverses and forms a new swing in the opposite direction before the level is hit, the pending order is cancelled and a new candidate is considered in the new direction.
Additional Features
• Optional session filter for backtesting specific trading hours
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
Damians UJ Strategy20 Pip Candle Strategy (No Engulfing)
Trades taken at 6pm direcrtly after candle close
Inputs allow you to reorganize retracement pips, SL, TP, 5PM candle amount.
S&D Light+ Enhanced# S&D Light+ Enhanced - Supply & Demand Zone Trading Strategy
## 📊 Overview
**S&D Light+ Enhanced** is an advanced Supply and Demand zone identification and trading strategy that combines institutional order flow concepts with smart money techniques. This strategy automatically identifies high-probability reversal zones based on Break of Structure (BOS), momentum analysis, and first retest principles.
## 🎯 Key Features
### Smart Zone Detection
- **Automatic Supply & Demand Zone Identification** - Detects institutional zones where price is likely to react
- **Multi-Candle Momentum Analysis** - Validates zones with configurable momentum requirements
- **Break of Structure (BOS) Confirmation** - Ensures zones are created only after significant structure breaks
- **Quality Filters** - Minimum zone size and ATR-based filtering to eliminate weak zones
### Advanced Zone Management
- **Customizable Zone Display** - Choose between Geometric or Volume-Weighted midlines
- **First Retest Logic** - Option to trade only the first touch of each zone for higher probability setups
- **Zone Capacity Control** - Maintains a clean chart by limiting stored zones per type
- **Visual Zone Status** - Automatically marks consumed zones with faded midlines
### Risk Management
- **Dynamic Stop Loss** - Positioned beyond zone boundaries with adjustable buffer
- **Risk-Reward Ratio Control** - Customizable R:R for consistent risk management
- **Entry Spacing** - Minimum bars between signals prevents overtrading
- **Position Sizing** - Built-in percentage of equity allocation
## 🔧 How It Works
### Zone Creation Logic
**Supply Zones (Selling Pressure):**
1. Strong momentum downward movement (configurable body-to-range ratio)
2. Identified bullish base candle (where institutions accumulated shorts)
3. Break of Structure downward (price breaks below recent swing low)
4. Zone created at the base candle's high/low range
**Demand Zones (Buying Pressure):**
1. Strong momentum upward movement
2. Identified bearish base candle (where institutions accumulated longs)
3. Break of Structure upward (price breaks above recent swing high)
4. Zone created at the base candle's high/low range
### Entry Conditions
**Long Entry:**
- Price retests a demand zone (touches top of zone)
- Rejection confirmed (close above zone)
- Zone hasn't been used (if "first retest only" enabled)
- Minimum bars since last entry respected
**Short Entry:**
- Price retests a supply zone (touches bottom of zone)
- Rejection confirmed (close below zone)
- Zone hasn't been used (if "first retest only" enabled)
- Minimum bars since last entry respected
## ⚙️ Customizable Parameters
### Display Settings
- **Show Zones** - Toggle zone visualization on/off
- **Max Stored Zones** - Control number of active zones (1-50 per type)
- **Color Customization** - Adjust supply/demand colors and transparency
### Zone Quality Filters
- **Momentum Body Fraction** - Minimum body size for momentum candles (0.1-0.9)
- **Min Momentum Candles** - Number of consecutive momentum candles required (1-5)
- **Big Candle Body Fraction** - Alternative single-candle momentum threshold (0.5-0.95)
- **Min Zone Size %** - Minimum zone height as percentage of price (0.01-5.0%)
### BOS Configuration
- **Swing Length** - Lookback period for structure identification (3-20)
- **ATR Length** - Period for volatility measurement (1-50)
- **BOS Required Break** - ATR multiplier for valid structure break (0.1-3.0)
### Midline Options
- **None** - No midline displayed
- **Geometric** - Simple average of zone top/bottom
- **CenterVolume** - Volume-weighted center based on highest volume bar in window
### Risk Management
- **SL Buffer %** - Additional space beyond zone boundary (0-5%)
- **Take Profit RR** - Risk-reward ratio for target placement (0.5-10x)
### Entry Rules
- **Only 1st Retest per Zone** - Trade zones only once for higher quality
- **Min Bars Between Entries** - Prevent overtrading (1-20 bars)
## 📈 Recommended Settings
### Conservative (Lower Frequency, Higher Quality)
```
Momentum Body Fraction: 0.30
Min Momentum Candles: 2-3
BOS Required Break: 0.8-1.0
Min Zone Size: 0.15-0.20%
Only 1st Retest: Enabled
```
### Balanced (Default)
```
Momentum Body Fraction: 0.28
Min Momentum Candles: 2
BOS Required Break: 0.7
Min Zone Size: 0.12%
Only 1st Retest: Enabled
```
### Aggressive (Higher Frequency, More Signals)
```
Momentum Body Fraction: 0.20-0.25
Min Momentum Candles: 1-2
BOS Required Break: 0.4-0.5
Min Zone Size: 0.08-0.10%
Only 1st Retest: Disabled
```
## 🎨 Visual Elements
- **Red Boxes** - Supply zones (potential selling areas)
- **Green Boxes** - Demand zones (potential buying areas)
- **Dotted Midlines** - Center of each zone (fades when zone is used)
- **Debug Triangles** - Shows when zone creation conditions are met
- Red triangle down = Supply zone created
- Green triangle up = Demand zone created
## 📊 Best Practices
1. **Use on Higher Timeframes** - 1H, 4H, and Daily charts work best for institutional zones
2. **Combine with Trend** - Trade zones in direction of overall market structure
3. **Wait for Confirmation** - Don't enter immediately at zone touch; wait for rejection
4. **Adjust for Market Volatility** - Increase BOS multiplier in choppy markets
5. **Monitor Zone Quality** - Fresh zones typically have higher success rates
6. **Backtest Your Settings** - Optimize parameters for your specific market and timeframe
## ⚠️ Risk Disclaimer
This strategy is for educational and informational purposes only. Past performance does not guarantee future results. Always:
- Use proper position sizing
- Set appropriate stop losses
- Test thoroughly before live trading
- Consider market conditions and overall trend
- Never risk more than you can afford to lose
## 🔍 Data Window Information
The strategy provides real-time metrics visible in the data window:
- Supply Zones Count
- Demand Zones Count
- ATR Value
- Momentum Signals (Up/Down)
- BOS Signals (Up/Down)
## 📝 Version History
**v1.0 - Enhanced Edition**
- Improved BOS detection logic
- Extended base candle search range
- Added comprehensive input validation
- Enhanced visual feedback system
- Robust array bounds checking
- Debug signals for troubleshooting
## 💡 Tips for Optimization
- **Trending Markets**: Lower momentum requirements, tighter BOS filters
- **Ranging Markets**: Increase zone size minimum, enable first retest only
- **Volatile Assets**: Increase ATR multiplier and SL buffer
- **Lower Timeframes**: Reduce swing length, increase min bars between entries
- **Higher Timeframes**: Increase swing length, relax momentum requirements
---
**Created with focus on institutional order flow, smart money concepts, and practical risk management.**
*Happy Trading! 📈*
XAUUSD 1m SMC Zones (BOS + Flexible TP Modes + Trailing Runner)//@version=6
strategy("XAUUSD 1m SMC Zones (BOS + Flexible TP Modes + Trailing Runner)",
overlay = true,
initial_capital = 10000,
pyramiding = 10,
process_orders_on_close = true)
//━━━━━━━━━━━━━━━━━━━
// 1. INPUTS
//━━━━━━━━━━━━━━━━━━━
// TP / SL
tp1Pips = input.int(10, "TP1 (pips)", minval = 1)
fixedSLpips = input.int(50, "Fixed SL (pips)", minval = 5)
runnerRR = input.float(3.0, "Runner RR (TP2 = SL * RR)", step = 0.1, minval = 1.0)
// Daily risk
maxDailyLossPct = input.float(5.0, "Max daily loss % (stop trading)", step = 0.5)
maxDailyProfitPct = input.float(20.0, "Max daily profit % (stop trading)", step = 1.0)
// HTF S/R (1H)
htfTF = input.string("60", "HTF timeframe (minutes) for S/R block")
// Profit strategy (Option C)
profitStrategy = input.string("Minimal Risk | Full BE after TP1", "Profit Strategy", options = )
// Runner stop mode (your option 4)
runnerStopMode = input.string( "BE only", "Runner Stop Mode", options = )
// ATR trail settings (only used if ATR mode selected)
atrTrailLen = input.int(14, "ATR Length (trail)", minval = 1)
atrTrailMult = input.float(1.0, "ATR Multiplier (trail)", step = 0.1, minval = 0.1)
// Pip size (for XAUUSD: 1 pip = 0.10 if tick = 0.01)
pipSize = syminfo.mintick * 10.0
tp1Points = tp1Pips * pipSize
slPoints = fixedSLpips * pipSize
baseQty = input.float (1.0, "Base order size" , step = 0.01, minval = 0.01)
//━━━━━━━━━━━━━━━━━━━
// 2. DAILY RISK MANAGEMENT
//━━━━━━━━━━━━━━━━━━━
isNewDay = ta.change(time("D")) != 0
var float dayStartEquity = na
var bool dailyStopped = false
equityNow = strategy.initial_capital + strategy.netprofit
if isNewDay or na(dayStartEquity)
dayStartEquity := equityNow
dailyStopped := false
dailyPnL = equityNow - dayStartEquity
dailyPnLPct = dayStartEquity != 0 ? (dailyPnL / dayStartEquity) * 100.0 : 0.0
if not dailyStopped
if dailyPnLPct <= -maxDailyLossPct
dailyStopped := true
if dailyPnLPct >= maxDailyProfitPct
dailyStopped := true
canTradeToday = not dailyStopped
//━━━━━━━━━━━━━━━━━━━
// 3. 1H S/R ZONES (for direction block)
//━━━━━━━━━━━━━━━━━━━
htOpen = request.security(syminfo.tickerid, htfTF, open)
htHigh = request.security(syminfo.tickerid, htfTF, high)
htLow = request.security(syminfo.tickerid, htfTF, low)
htClose = request.security(syminfo.tickerid, htfTF, close)
// Engulf logic on HTF
htBullPrev = htClose > htOpen
htBearPrev = htClose < htOpen
htBearEngulf = htClose < htOpen and htBullPrev and htOpen >= htClose and htClose <= htOpen
htBullEngulf = htClose > htOpen and htBearPrev and htOpen <= htClose and htClose >= htOpen
// Liquidity sweep on HTF previous candle
htSweepHigh = htHigh > ta.highest(htHigh, 5)
htSweepLow = htLow < ta.lowest(htLow, 5)
// Store last HTF zones
var float htResHigh = na
var float htResLow = na
var float htSupHigh = na
var float htSupLow = na
if htBearEngulf and htSweepHigh
htResHigh := htHigh
htResLow := htLow
if htBullEngulf and htSweepLow
htSupHigh := htHigh
htSupLow := htLow
// Are we inside HTF zones?
inHtfRes = not na(htResHigh) and close <= htResHigh and close >= htResLow
inHtfSup = not na(htSupLow) and close >= htSupLow and close <= htSupHigh
// Block direction against HTF zones
longBlockedByZone = inHtfRes // no buys in HTF resistance
shortBlockedByZone = inHtfSup // no sells in HTF support
//━━━━━━━━━━━━━━━━━━━
// 4. 1m LOCAL ZONES (LIQUIDITY SWEEP + ENGULF + QUALITY SCORE)
//━━━━━━━━━━━━━━━━━━━
// 1m engulf patterns
bullPrev1 = close > open
bearPrev1 = close < open
bearEngulfNow = close < open and bullPrev1 and open >= close and close <= open
bullEngulfNow = close > open and bearPrev1 and open <= close and close >= open
// Liquidity sweep by previous candle on 1m
sweepHighPrev = high > ta.highest(high, 5)
sweepLowPrev = low < ta.lowest(low, 5)
// Local zone storage (one active support + one active resistance)
// Quality score: 1 = engulf only, 2 = engulf + sweep (we only trade ≥2)
var float supLow = na
var float supHigh = na
var int supQ = 0
var bool supUsed = false
var float resLow = na
var float resHigh = na
var int resQ = 0
var bool resUsed = false
// New resistance zone: previous bullish candle -> bear engulf
if bearEngulfNow
resLow := low
resHigh := high
resQ := sweepHighPrev ? 2 : 1
resUsed := false
// New support zone: previous bearish candle -> bull engulf
if bullEngulfNow
supLow := low
supHigh := high
supQ := sweepLowPrev ? 2 : 1
supUsed := false
// Raw "inside zone" detection
inSupRaw = not na(supLow) and close >= supLow and close <= supHigh
inResRaw = not na(resHigh) and close <= resHigh and close >= resLow
// QUALITY FILTER: only trade zones with quality ≥ 2 (engulf + sweep)
highQualitySup = supQ >= 2
highQualityRes = resQ >= 2
inSupZone = inSupRaw and highQualitySup and not supUsed
inResZone = inResRaw and highQualityRes and not resUsed
// Plot zones
plot(supLow, "Sup Low", color = color.new(color.lime, 60), style = plot.style_linebr)
plot(supHigh, "Sup High", color = color.new(color.lime, 60), style = plot.style_linebr)
plot(resLow, "Res Low", color = color.new(color.red, 60), style = plot.style_linebr)
plot(resHigh, "Res High", color = color.new(color.red, 60), style = plot.style_linebr)
//━━━━━━━━━━━━━━━━━━━
// 5. MODERATE BOS (3-BAR FRACTAL STRUCTURE)
//━━━━━━━━━━━━━━━━━━━
// 3-bar swing highs/lows
swHigh = high > high and high > high
swLow = low < low and low < low
var float lastSwingHigh = na
var float lastSwingLow = na
if swHigh
lastSwingHigh := high
if swLow
lastSwingLow := low
// BOS conditions
bosUp = not na(lastSwingHigh) and close > lastSwingHigh
bosDown = not na(lastSwingLow) and close < lastSwingLow
// Zone “arming” and BOS validation
var bool supArmed = false
var bool resArmed = false
var bool supBosOK = false
var bool resBosOK = false
// Arm zones when first touched
if inSupZone
supArmed := true
if inResZone
resArmed := true
// BOS after arming → zone becomes valid for entries
if supArmed and bosUp
supBosOK := true
if resArmed and bosDown
resBosOK := true
// Reset BOS flags when new zones are created
if bullEngulfNow
supArmed := false
supBosOK := false
if bearEngulfNow
resArmed := false
resBosOK := false
//━━━━━━━━━━━━━━━━━━━
// 6. ENTRY CONDITIONS (ZONE + BOS + RISK STATE)
//━━━━━━━━━━━━━━━━━━━
flatOrShort = strategy.position_size <= 0
flatOrLong = strategy.position_size >= 0
longSignal = canTradeToday and not longBlockedByZone and inSupZone and supBosOK and flatOrShort
shortSignal = canTradeToday and not shortBlockedByZone and inResZone and resBosOK and flatOrLong
//━━━━━━━━━━━━━━━━━━━
// 7. ORDER LOGIC – TWO PROFIT STRATEGIES
//━━━━━━━━━━━━━━━━━━━
// Common metrics
atrTrail = ta.atr(atrTrailLen)
// MINIMAL MODE: single trade, BE after TP1, optional trailing
// HYBRID MODE: two trades (Scalp @ TP1, Runner @ TP2)
// Persistent tracking
var float longEntry = na
var float longTP1 = na
var float longTP2 = na
var float longSL = na
var bool longBE = false
var float longRunEntry = na
var float longRunTP1 = na
var float longRunTP2 = na
var float longRunSL = na
var bool longRunBE = false
var float shortEntry = na
var float shortTP1 = na
var float shortTP2 = na
var float shortSL = na
var bool shortBE = false
var float shortRunEntry = na
var float shortRunTP1 = na
var float shortRunTP2 = na
var float shortRunSL = na
var bool shortRunBE = false
isMinimal = profitStrategy == "Minimal Risk | Full BE after TP1"
isHybrid = profitStrategy == "Hybrid | Scalp TP + Runner TP"
//━━━━━━━━━━ LONG ENTRIES ━━━━━━━━━━
if longSignal
if isMinimal
longEntry := close
longSL := longEntry - slPoints
longTP1 := longEntry + tp1Points
longTP2 := longEntry + slPoints * runnerRR
longBE := false
strategy.entry("Long", strategy.long)
supUsed := true
supArmed := false
supBosOK := false
else if isHybrid
longRunEntry := close
longRunSL := longRunEntry - slPoints
longRunTP1 := longRunEntry + tp1Points
longRunTP2 := longRunEntry + slPoints * runnerRR
longRunBE := false
// Two separate entries, each 50% of baseQty (for backtest)
strategy.entry("LongScalp", strategy.long, qty = baseQty * 0.5)
strategy.entry("LongRun", strategy.long, qty = baseQty * 0.5)
supUsed := true
supArmed := false
supBosOK := false
//━━━━━━━━━━ SHORT ENTRIES ━━━━━━━━━━
if shortSignal
if isMinimal
shortEntry := close
shortSL := shortEntry + slPoints
shortTP1 := shortEntry - tp1Points
shortTP2 := shortEntry - slPoints * runnerRR
shortBE := false
strategy.entry("Short", strategy.short)
resUsed := true
resArmed := false
resBosOK := false
else if isHybrid
shortRunEntry := close
shortRunSL := shortRunEntry + slPoints
shortRunTP1 := shortRunEntry - tp1Points
shortRunTP2 := shortRunEntry - slPoints * runnerRR
shortRunBE := false
strategy.entry("ShortScalp", strategy.short, qty = baseQty * 50)
strategy.entry("ShortRun", strategy.short, qty = baseQty * 50)
resUsed := true
resArmed := false
resBosOK := false
//━━━━━━━━━━━━━━━━━━━
// 8. EXIT LOGIC – MINIMAL MODE
//━━━━━━━━━━━━━━━━━━━
// LONG – Minimal Risk: 1 trade, BE after TP1, runner to TP2
if isMinimal and strategy.position_size > 0 and not na(longEntry)
// Move to BE once TP1 is touched
if not longBE and high >= longTP1
longBE := true
// Base SL: BE or initial SL
float dynLongSL = longBE ? longEntry : longSL
// Optional trailing after BE
if longBE
if runnerStopMode == "Structure trail" and not na(lastSwingLow) and lastSwingLow > longEntry
dynLongSL := math.max(dynLongSL, lastSwingLow)
if runnerStopMode == "ATR trail"
trailSL = close - atrTrailMult * atrTrail
dynLongSL := math.max(dynLongSL, trailSL)
strategy.exit("Long Exit", "Long", stop = dynLongSL, limit = longTP2)
// SHORT – Minimal Risk: 1 trade, BE after TP1, runner to TP2
if isMinimal and strategy.position_size < 0 and not na(shortEntry)
if not shortBE and low <= shortTP1
shortBE := true
float dynShortSL = shortBE ? shortEntry : shortSL
if shortBE
if runnerStopMode == "Structure trail" and not na(lastSwingHigh) and lastSwingHigh < shortEntry
dynShortSL := math.min(dynShortSL, lastSwingHigh)
if runnerStopMode == "ATR trail"
trailSLs = close + atrTrailMult * atrTrail
dynShortSL := math.min(dynShortSL, trailSLs)
strategy.exit("Short Exit", "Short", stop = dynShortSL, limit = shortTP2)
//━━━━━━━━━━━━━━━━━━━
// 9. EXIT LOGIC – HYBRID MODE
//━━━━━━━━━━━━━━━━━━━
// LONG – Hybrid: Scalp + Runner
if isHybrid
// Scalp leg: full TP at TP1
if strategy.opentrades > 0
strategy.exit("LScalp TP", "LongScalp", stop = longRunSL, limit = longRunTP1)
// Runner leg
if strategy.position_size > 0 and not na(longRunEntry)
if not longRunBE and high >= longRunTP1
longRunBE := true
float dynLongRunSL = longRunBE ? longRunEntry : longRunSL
if longRunBE
if runnerStopMode == "Structure trail" and not na(lastSwingLow) and lastSwingLow > longRunEntry
dynLongRunSL := math.max(dynLongRunSL, lastSwingLow)
if runnerStopMode == "ATR trail"
trailRunSL = close - atrTrailMult * atrTrail
dynLongRunSL := math.max(dynLongRunSL, trailRunSL)
strategy.exit("LRun TP", "LongRun", stop = dynLongRunSL, limit = longRunTP2)
// SHORT – Hybrid: Scalp + Runner
if isHybrid
if strategy.opentrades > 0
strategy.exit("SScalp TP", "ShortScalp", stop = shortRunSL, limit = shortRunTP1)
if strategy.position_size < 0 and not na(shortRunEntry)
if not shortRunBE and low <= shortRunTP1
shortRunBE := true
float dynShortRunSL = shortRunBE ? shortRunEntry : shortRunSL
if shortRunBE
if runnerStopMode == "Structure trail" and not na(lastSwingHigh) and lastSwingHigh < shortRunEntry
dynShortRunSL := math.min(dynShortRunSL, lastSwingHigh)
if runnerStopMode == "ATR trail"
trailRunSLs = close + atrTrailMult * atrTrail
dynShortRunSL := math.min(dynShortRunSL, trailRunSLs)
strategy.exit("SRun TP", "ShortRun", stop = dynShortRunSL, limit = shortRunTP2)
//━━━━━━━━━━━━━━━━━━━
// 10. RESET STATE WHEN FLAT
//━━━━━━━━━━━━━━━━━━━
if strategy.position_size == 0
longEntry := na
shortEntry := na
longBE := false
shortBE := false
longRunEntry := na
shortRunEntry := na
longRunBE := false
shortRunBE := false
//━━━━━━━━━━━━━━━━━━━
// 11. VISUAL ENTRY MARKERS
//━━━━━━━━━━━━━━━━━━━
plotshape(longSignal, title = "Long Signal", style = shape.triangleup,
location = location.belowbar, color = color.lime, size = size.tiny, text = "L")
plotshape(shortSignal, title = "Short Signal", style = shape.triangledown,
location = location.abovebar, color = color.red, size = size.tiny, text = "S")
AI ALGO [Ganesh]Core Strategy Components\
1. EMA (Exponential Moving Average) SystemThe strategy uses three EMAs to identify trend direction:
EMA 48 (longer-term trend)
EMA 2 (short-term momentum)
EMA 21 (medium-term trend)
How it works:
Bullish trend: When price is above EMA 21 (green cloud)
Bearish trend: When price is below EMA 21 (red cloud)
EMA Cloud: The area between EMA 2 and EMA 48/21 provides visual trend confirmation
Optional higher timeframe (HTF) analysis for multi-timeframe confirmation
2. DEMA ATR (Double EMA + Average True Range)
This is a dynamic support/resistance indicator that adapts to volatility:Components:
DEMA (Double Exponential Moving Average): Smooths price action with less lag
ATR Bands: Creates upper and lower bands based on volatility (ATR × 1.7 factor)
Signal Generation:
Green line: Uptrend (DEMA ATR rising)
Red line: Downtrend (DEMA ATR falling)
Acts as a trailing stop-loss level that adjusts with market volatility
3. Smart Trail System (Fibonacci-Based)
An advanced trailing stop system using modified true range calculations:Key Features:
Calculates true range using Wilder's smoothing method
Creates Fibonacci retracement levels (61.8%, 78.6%, 88.6%) from the trail line
Adaptive stop-loss: Adjusts based on ATR factor (4.2) and smoothing (4)
Trend Detection:
Bullish: Price > Trailing line (blue zones)
Bearish: Price < Trailing line (red zones)
The Fibonacci zones show potential support/resistance areas
4. ZigZag Indicator Identifies significant swing highs and lows:
Length parameter: 13 (sensitivity control)
Labels: Higher Highs (HH), Lower Lows (LL), etc.
Helps identify trend reversals and key pivot points
5. Support & Resistance Levels
Strength-based S/R: Identifies horizontal support/resistance zones
Zone width: Adjustable percentage-based zones
High/Low zones: Marks significant price levels
Trading LogicEntry Conditions (Implied)The strategy likely enters trades when:Long Entry:
Price crosses above DEMA ATR (green)
Price is above EMA 21 (bullish EMA cloud)
Smart Trail confirms uptrend
Price bounces from Fibonacci support levels
Short Entry:
Price crosses below DEMA ATR (red)
Price is below EMA 21 (bearish EMA cloud)
Smart Trail confirms downtrend
Price rejects from Fibonacci resistance levels
Exit/Stop-Loss Strategy
Trailing stops: Using Smart Trail Fibonacci levels
Dynamic stops: DEMA ATR line acts as a moving stop-loss
Risk management: Position sizing at 50% of equity per trade
Dashboard Features1. Weekly Performance Table
Tracks trades per day of the week
Shows win/loss statistics
Calculates win rate percentage
2. Monthly Performance Table
Monthly P&L breakdown
Yearly performance summary
Color-coded returns (green = profit, red = loss)
Strategy Parameters
Initial Capital: $5,000
Commission: 0.02% per trade
Position Size: 50% of equity
Pyramiding: Disabled (no adding to positions)
Calculation: On bar close (not tick-by-tick)
Visual Elements
EMA clouds: Green (bullish) / Red (bearish)
DEMA ATR line: Dynamic support/resistance
Smart Trail zones: Fibonacci-based colored bands
ZigZag lines: Swing high/low connections
S/R zones: Horizontal support/resistance areas
Strategy Philosophy
This is a trend-following strategy with dynamic risk management that:
Uses multiple timeframes for confirmation
Adapts to volatility through ATR-based indicators
Provides clear visual cues for trend direction
Includes comprehensive performance tracking
Combines momentum (EMAs) with volatility (ATR) for robust signals
The strategy works best in trending markets and uses the Fibonacci trail system to maximize profits while protecting against reversals with adaptive stop-losses.
5-Min Range Breakout (09:30 NY on MNQ)This is a 5 - min orb strat that a youtuber mentioned and i had a manual look for a while and thought it was actually pretty good but my results are bad. Feel free to look yourself with this code.
Basically this strat is using the 5min orb then go down to 1min timeframe and wait for a breakout with FVG confirmation. So candle after breaking candle is our entry only if FVG is formed.
However i do notice if you dump this code onto 5min timefraem and above you start consistently making money but it is a very small amount for me so you all can have it. Good starter strat on 5min or 10min timeframe
