Dskyz (DAFE) AI Adaptive Regime - Beginners VersionDskyz (DAFE) AI Adaptive Regime - Pro: Revolutionizing Trading for All
Introduction
In the fast-paced world of financial markets, traders need tools that can keep up with ever-changing conditions while remaining accessible. The Dskyz (DAFE) AI Adaptive Regime - Pro is a groundbreaking TradingView strategy that delivers advanced, AI-driven trading capabilities to everyday traders. Available on TradingView (TradingView Scripts), this Pine Script strategy combines sophisticated market analysis with user-friendly features, making it a standout choice for both novice and experienced traders.
Core Functionality
The strategy is built to adapt to different market regimes—trending, ranging, volatile, or quiet—using a robust set of technical indicators, including:
Moving Averages (MA): Fast and slow EMAs to detect trend direction.
Average True Range (ATR): For dynamic stop-loss and volatility assessment.
Relative Strength Index (RSI) and MACD: Multi-timeframe confirmation of momentum and trend.
Average Directional Index (ADX): To identify trending markets.
Bollinger Bands: For assessing volatility and range conditions.
Candlestick Patterns: Recognizes patterns like bullish engulfing, hammer, and double bottoms, confirmed by volume spikes.
It generates buy and sell signals based on a scoring system that weighs these indicators, ensuring trades align with the current market environment. The strategy also includes dynamic risk management with ATR-based stops and trailing stops, as well as performance tracking to optimize future trades.
What Sets It Apart
The Dskyz (DAFE) AI Adaptive Regime - Pro distinguishes itself from other TradingView strategies through several unique features, which we compare to common alternatives below:
| Feature | Dskyz (DAFE) | Typical TradingView Strategies|
|---------|-------------|------------------------------------------------------------|
| Regime Detection | Automatically identifies and adapts to **four** market regimes | Often static or limited to trend/range detection |
| Multi‑Timeframe Analysis | Uses higher‑timeframe RSI/MACD for confirmation | Rarely incorporates multi‑timeframe data |
| Pattern Recognition | Detects candlestick patterns **with volume confirmation** | Limited or no pattern recognition |
| Dynamic Risk Management | ATR‑based stops and trailing stops | Often uses fixed stops or basic risk rules |
| Performance Tracking | Adjusts thresholds based on past performance | Typically static parameters |
| Beginner‑Friendly Presets | Aggressive, Conservative, Optimized profiles | Requires manual parameter tuning |
| Visual Cues | Color‑coded backgrounds for regimes | Basic or no visual aids |
The Dskyz strategy’s ability to integrate regime detection, multi-timeframe analysis, and user-friendly presets makes it uniquely versatile and accessible, addressing the needs of everyday traders who want professional-grade tools without the complexity.
-Key Features and Benefits
[Why It’s Ideal for Everyday Traders
⚡The Dskyz (DAFE) AI Adaptive Regime - Pro democratizes advanced trading by offering professional-grade tools in an accessible package. Unlike many TradingView strategies that require deep technical knowledge or fail in changing market conditions, this strategy simplifies complex analysis while maintaining robustness. Its presets and visual aids make it easy for beginners to start, while its adaptive features and performance tracking appeal to advanced traders seeking an edge.
🔄Limitations and Considerations
Market Dependency: Performance varies by market and timeframe. Backtesting is essential to ensure compatibility with your trading style.
Learning Curve: While presets simplify use, understanding regimes and indicators enhances effectiveness.
No Guaranteed Profits: Like all strategies, success depends on market conditions and proper execution. The Reddit discussion highlights skepticism about TradingView strategies’ universal success (Reddit Discussion).
Instrument Specificity: Optimized for futures (e.g., ES, NQ) due to fixed tick values. Test on other instruments like stocks or forex to verify compatibility.
📌Conclusion
The Dskyz (DAFE) AI Adaptive Regime - Pro is a revolutionary TradingView strategy that empowers everyday traders with advanced, AI-driven tools. Its ability to adapt to market regimes, confirm signals across timeframes, and manage risk dynamically. sets it apart from typical strategies. By offering beginner-friendly presets and visual cues, it makes sophisticated trading accessible without sacrificing power. Whether you’re a novice looking to trade smarter or a pro seeking a competitive edge, this strategy is your ticket to mastering the markets. Add it to your chart, backtest it, and join the elite traders leveraging AI to dominate. Trade like a boss today! 🚀
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
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Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
Dskyz (DAFE) MAtrix with ATR-Powered Precision Dskyz (DAFE) MAtrix with ATR-Powered Precision
This cutting‐edge futures trading strategy built to thrive in rapidly changing market conditions. Developed for high-frequency futures trading on instruments such as the CME Mini MNQ, this strategy leverages a matrix of sophisticated moving averages combined with ATR-based filters to pinpoint high-probability entries and exits. Its unique combination of adaptable technical indicators and multi-timeframe trend filtering sets it apart from standard strategies, providing enhanced precision and dynamic responsiveness.
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Core Functional Components
1. Advanced Moving Averages
A distinguishing feature of the DAFE strategy is its robust, multi-choice moving averages (MAs). Clients can choose from a wide array of MAs—each with specific strengths—in order to fine-tune their trading signals. The code includes user-defined functions for the following MAs:
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Hull Moving Average (HMA):
The hma(src, len) function calculates the HMA by using weighted moving averages (WMAs) to reduce lag considerably while smoothing price data. This function computes an intermediate WMA of half the specified length, then a full-length WMA, and finally applies a further WMA over the square root of the length. This design allows for rapid adaptation to price changes without the typical delays of traditional moving averages.
Triple Exponential Moving Average (TEMA):
Implemented via tema(src, len), TEMA uses three consecutive exponential moving averages (EMAs) to effectively cancel out lag and capture price momentum. The final formula—3 * (ema1 - ema2) + ema3—produces a highly responsive indicator that filters out short-term noise.
Double Exponential Moving Average (DEMA):
Through the dema(src, len) function, DEMA calculates an EMA and then a second EMA on top of it. Its simplified formula of 2 * ema1 - ema2 provides a smoother curve than a single EMA while maintaining enhanced responsiveness.
Volume Weighted Moving Average (VWMA):
With vwma(src, len), this MA accounts for trading volume by weighting the price, thereby offering a more contextual picture of market activity. This is crucial when volume spikes indicate significant moves.
Zero Lag EMA (ZLEMA):
The zlema(src, len) function applies a correction to reduce the inherent lag found in EMAs. By subtracting a calculated lag (based on half the moving average window), ZLEMA is exceptionally attuned to recent price movements.
Arnaud Legoux Moving Average (ALMA):
The alma(src, len, offset, sigma) function introduces ALMA—a type of moving average designed to be less affected by outliers. With parameters for offset and sigma, it allows customization of the degree to which the MA reacts to market noise.
Kaufman Adaptive Moving Average (KAMA):
The custom kama(src, len) function is noteworthy for its adaptive nature. It computes an efficiency ratio by comparing price change against volatility, then dynamically adjusts its smoothing constant. This results in an MA that quickly responds during trending periods while remaining smoothed during consolidation.
Each of these functions—integrated into the strategy—is selectable by the trader (via the fastMAType and slowMAType inputs). This flexibility permits the tailored application of the MA most suited to current market dynamics and individual risk management preferences.
2. ATR-Based Filters and Risk Controls
ATR Calculation and Volatility Filter:
The strategy computes the Average True Range (ATR) over a user-defined period (atrPeriod). ATR is then used to derive both:
Volatility Assessment: Expressed as a ratio of ATR to closing price, ensuring that trades are taken only when volatility remains within a safe, predefined threshold (volatilityThreshold).
ATR-Based Entry Filters: Implemented as atrFilterLong and atrFilterShort, these conditions ensure that for long entries the price is sufficiently above the slow MA and vice versa for shorts. This acts as an additional confirmation filter.
Dynamic Exit Management:
The exit logic employs a dual approach:
Fixed Stop and Profit Target: Stops and targets are set at multiples of ATR (fixedStopMultiplier and profitTargetATRMult), helping manage risk in volatile markets.
Trailing Stop Adjustments: A trailing stop is calculated using the ATR multiplied by a user-defined offset (trailOffset), which captures additional profits as the trade moves favorably while protecting against reversals.
3. Multi-Timeframe Trend Filtering
The strategy enhances its signal reliability by leveraging a secondary, higher timeframe analysis:
15-Minute Trend Analysis:
By retrieving 15-minute moving averages (fastMA15m and slowMA15m) via request.security, the strategy determines the broader market trend. This secondary filter (enabled or disabled through useTrendFilter) ensures that entries are aligned with the prevailing market direction, thereby reducing the incidence of false signals.
4. Signal and Execution Logic
Combined MA Alignment:
The entry conditions are based primarily on the alignment of the fast and slow MAs. A long condition is triggered when the current price is above both MAs and the fast MA is above the slow MA—complemented by the ATR filter and volume conditions. The reverse applies for a short condition.
Volume and Time Window Validation:
Trades are permitted only if the current volume exceeds a minimum (minVolume) and the current hour falls within the predefined trading window (tradingStartHour to tradingEndHour). An additional volume spike check (comparing current volume to a moving average of past volumes) further filters for optimal market conditions.
Comprehensive Order Execution:
The strategy utilizes flexible order execution functions that allow pyramiding (up to 10 positions), ensuring that it can scale into positions as favorable conditions persist. The use of both market entries and automated exits (with profit targets, stop-losses, and trailing stops) ensures that risk is managed at every step.
5. Integrated Dashboard and Metrics
For transparency and real-time analysis, the strategy includes:
On-Chart Visualizations:
Both fast and slow MAs are plotted on the chart, making it easy to see the market’s technical foundation.
Dynamic Metrics Dashboard:
A built-in table displays crucial performance statistics—including current profit/loss, equity, ATR (both raw and as a percentage), and the percentage gap between the moving averages. These metrics offer immediate insight into the health and performance of the strategy.
Input Parameters: Detailed Breakdown
Every input is meticulously designed to offer granular control:
Fast & Slow Lengths:
Determine the window size for the fast and slow moving averages. Smaller values yield more sensitivity, while larger values provide a smoother, delayed response.
Fast/Slow MA Types:
Choose the type of moving average for fast and slow signals. The versatility—from basic SMA and EMA to more complex ones like HMA, TEMA, ZLEMA, ALMA, and KAMA—allows customization to fit different market scenarios.
ATR Parameters:
atrPeriod and atrMultiplier shape the volatility assessment, directly affecting entry filters and risk management through stop-loss and profit target levels.
Trend and Volume Filters:
Inputs such as useTrendFilter, minVolume, and the volume spike condition help confirm that a trade occurs in active, trending markets rather than during periods of low liquidity or market noise.
Trading Hours:
Restricting trade execution to specific hours (tradingStartHour and tradingEndHour) helps avoid illiquid or choppy markets outside of prime trading sessions.
Exit Strategies:
Parameters like trailOffset, profitTargetATRMult, and fixedStopMultiplier provide multiple layers of risk management and profit protection by tailoring how exits are generated relative to current market conditions.
Pyramiding and Fixed Trade Quantity:
The strategy supports multiple entries within a trend (up to 10 positions) and sets a predefined trade quantity (fixedQuantity) to maintain consistent exposure and risk per trade.
Dashboard Controls:
The resetDashboard input allows for on-the-fly resetting of performance metrics, keeping the strategy’s performance dashboard accurate and up-to-date.
Why This Strategy is Truly Exceptional
Multi-Faceted Adaptability:
The ability to switch seamlessly between various moving average types—each suited to particular market conditions—enables the strategy to adapt dynamically. This is a testament to the high level of coding sophistication and market insight infused within the system.
Robust Risk Management:
The integration of ATR-based stops, profit targets, and trailing stops ensures that every trade is executed with well-defined risk parameters. The system is designed to mitigate unexpected market swings while optimizing profit capture.
Comprehensive Market Filtering:
By combining moving average crossovers with volume analysis, volatility thresholds, and multi-timeframe trend filters, the strategy only enters trades under the most favorable conditions. This multi-layered filtering reduces noise and enhances signal quality.
-Final Thoughts-
The Dskyz Adaptive Futures Elite (DAFE) MAtrix with ATR-Powered Precision strategy is not just another trading algorithm—it is a multi-dimensional, fully customizable system built on advanced technical principles and sophisticated risk management techniques. Every function and input parameter has been carefully engineered to provide traders with a system that is both powerful and transparent.
For clients seeking a state-of-the-art trading solution that adapts dynamically to market conditions while maintaining strict discipline in risk management, this strategy truly stands in a class of its own.
****Please show support if you enjoyed this strategy. I'll have more coming out in the near future!!
-Dskyz
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
Scalping 15min: EMA + MACD + RSI + ATR-based SL/TP📈 Strategy: 15-Minute Scalping — EMA + MACD + RSI + ATR-based SL/TP
This scalping strategy is designed for 15-minute charts and combines trend-following and momentum confirmation with dynamic stop loss and take profit levels based on volatility.
🔧 Indicators Used:
EMA 50 — identifies the main trend
MACD Histogram — confirms momentum direction
RSI (14) — filters overbought/oversold conditions
ATR (14) — dynamically sets SL and TP based on market volatility
📊 Entry Conditions:
Long Entry:
Price is above EMA 50
MACD histogram is positive
RSI is above 50 but below 70
Short Entry:
Price is below EMA 50
MACD histogram is negative
RSI is below 50 but above 30
🛑 Risk Management:
Stop Loss: 1×ATR (user-configurable)
Take Profit: 2×ATR (user-configurable)
These values can be adjusted in the script inputs depending on your risk/reward preference or market conditions.
⚠️ Notes:
Strategy is optimized for scalping fast-moving pairs (e.g. crypto, forex).
Works best in trending markets.
Use backtesting and forward testing before live trading.
Trailing Monster StrategyTrailing Monster Strategy
This is an experimental trend-following strategy that incorporates a custom adaptive moving average (PKAMA), RSI-based momentum filtering, and dynamic trailing stop-loss logic. It is designed for educational and research purposes only, and may require further optimization or risk management considerations prior to live deployment.
Strategy Logic
The strategy attempts to participate in sustained price trends by combining:
- A Power Kaufman Adaptive Moving Average (PKAMA) for dynamic trend detection,
- RSI and Simple Moving Average (SMA) filters for market condition confirmation,
- A delayed trailing stop-loss to manage exits once a trade is in profit.
Entry Conditions
Long Entry:
- RSI exceeds the overbought threshold (default: 70),
- Price is trading above the 200-period SMA,
- PKAMA slope is positive (indicating upward momentum),
- A minimum number of bars have passed since the last entry.
Short Entry:
- RSI falls below the oversold threshold (default: 30),
- Price is trading below the 200-period SMA,
- PKAMA slope is negative (indicating downward momentum),
-A minimum number of bars have passed since the last entry.
Exit Conditions
- A trailing stop-loss is applied once the position has been open for a user-defined number of bars.
- The trailing distance is calculated as a fixed percentage of the average entry price.
Technical Notes
This script implements a custom version of the Power Kaufman Adaptive Moving Average (PKAMA), conceptually inspired by alexgrover’s public implementation on TradingView .
Unlike traditional moving averages, PKAMA dynamically adjusts its responsiveness based on recent market volatility, allowing it to better capture trend changes in fast-moving assets like altcoins.
Disclaimer
This strategy is provided for educational purposes only.
It is not financial advice, and no guarantee of profitability is implied.
Always conduct thorough backtesting and forward testing before using any strategy in a live environment.
Adjust inputs based on your individual risk tolerance, asset class, and trading style.
Feedback is encouraged. You are welcome to fork and modify this script to suit your own preferences and market approach.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
IBAC Strategy - ZygoraIBAC - Intrinsic Binary Averaging based Contrarian
A contrarian scalping strategy in the futures market, designed to stabilize market efficiency by capitalizing on price reversals. The strategy has no stop loss, instead employing a cascading approach—adding to the position size each time the price moves in the wrong direction—and closes the full position when the target profit is reached. Without delving into intricate details, the strategy adheres to the following basic rules:
Position sizing is determined by a customized indicator based on cumulative reversal probability, which also contributes to identifying the signal’s direction.
Direction is determined by the Moving Average: price above the Moving Average signals a Short position, while price below it signals a Long position.
The threshold for entries and exits is adjusted based on the range between extremes (highest high minus lowest low) over the past 100 historical bars.
The next limit entry is placed at a distance equal to the threshold length below (for Long) or above (for Short) the current average price.
The next target profit is set at a distance equal to the threshold length above (for Long) or below (for Short) the current average price.
A signal is triggered when there is a sudden price movement detected by the RSI (Relative Strength Index).
When a signal is identified, the strategy starts with a risk-reward ratio (RR) of 1:1. However, the RR worsens as the cascading steps—referred to as inventory I—increase, because the average entry price shifts unfavorably with each new position added. To mitigate the risk of liquidation, the strategy aims to hold a smaller inventory amount over time. This is achieved by using a multiple threshold multiplier: when a specified inventory limit is reached, the threshold for the next entry increases, and the threshold for the next target profit decreases. As a result, with higher inventory levels, the strategy accepts a lower RR but increases the likelihood of hitting the target profit.
The target profit is always set above the average entry price (for Long) or below it (for Short), ensuring that the strategy eventually closes at a profit. This leads to a 100% win rate but comes with relatively high drawdowns due to the absence of a stop loss and the cascading nature of the positions. The strategy performs best in a consolidation market in 1 minute timeframe, where price tends to oscillate within a range, allowing the contrarian approach to capitalize on reversals. The strategy’s name is derived from its customized indicator for position sizing, which leverages cumulative reversal probability to optimize position sizes and assist in determining the signal’s direction.
Apex Trend SniperApex Trend Sniper - Advanced Trend Trading Strategy (Pine Script v5)
🚀 Overview
The Apex Trend Sniper is an advanced, fully automated trend-following strategy designed for crypto, forex, and stock markets. It combines momentum analysis, trend confirmation, volume validation, and adaptive risk management to capture high-probability trades. Unlike many strategies, this system is 100% non-repainting, ensuring reliable backtesting and real-time execution.
🔹 How This Strategy Works (Indicator Mashup)
The Apex Trend Sniper leverages multiple indicators to create a robust multi-layered confirmation system:
1️⃣ Trend Identification with RMI & McGinley Dynamic
📌 What It Does: Identifies the dominant trend and prevents trading against market conditions.
✔ McGinley Dynamic Baseline:
A highly adaptive moving average that dynamically reacts to price changes.
Price above the baseline = bullish trend.
Price below the baseline = bearish trend.
✔ Relative Momentum Index (RMI):
A refined Relative Strength Index (RSI) that filters out weak trends.
Above 50 = bullish confirmation.
Below 50 = bearish confirmation.
2️⃣ Trend Strength Confirmation with Vortex Indicator
📌 What It Does: Confirms that a detected trend is strong and valid.
✔ Vortex Indicator (VI):
Measures directional movement and trend strength.
A bullish trend is confirmed when VI+ > VI-.
A bearish trend is confirmed when VI- > VI+.
3️⃣ Volume Spike Detection for Trade Validation
📌 What It Does: Ensures that trades are placed only during strong market participation.
✔ Volume Confirmation:
A trade signal is only valid if volume spikes above the moving average.
Helps avoid false breakouts and weak trends.
4️⃣ Entry & Exit Strategy with Multi-Level Take Profits
📌 What It Does: Enters trades only when all conditions align and manages risk effectively.
✔ Entry Conditions (All must be met):
Price is above/below McGinley Dynamic.
RMI confirms trend direction.
Vortex indicator confirms trend strength.
Volume spike is detected.
✔ Exit Conditions:
Take Profit 1 (TP1): Secures 50% of the position at the first price target.
Take Profit 2 (TP2): Closes the remaining position at the second price target.
Exit Before Reversal: If an opposite trend signal appears, the position is closed early.
Trend Weakness Exit: If momentum weakens, the trade is exited automatically.
📌 Strategy Customization
🔧 Fully customizable to fit any trading style:
✔ McGinley Dynamic Length – Adjust baseline sensitivity.
✔ RMI & Vortex Settings – Fine-tune momentum filters.
✔ Volume Thresholds – Modify spike detection for better accuracy.
✔ Take Profit Levels – Set TP1 & TP2 based on market volatility.
📢 How to Use Apex Trend Sniper
1️⃣ Apply the strategy to any TradingView chart.
2️⃣ Customize the settings to fit your trading approach.
3️⃣ Use the backtest report to evaluate performance.
4️⃣ Monitor the dashboard to track real-time trade execution.
📌 Recommended Timeframes & Markets
✔ Best Markets:
✅ Crypto (BTC, ETH, SOL, etc.)
✅ Forex (EUR/USD, GBP/USD, JPY/USD, etc.)
✅ Stocks & Indices (S&P500, NASDAQ, etc.)
✔ Optimal Timeframes:
✅ Swing Trading: 1H – 4H – 1D
✅ Intraday & Scalping: 5M – 15M – 30M
📌 Backtest Settings for Realistic Performance
✔ Initial Capital: $1000 (or more for scaling).
✔ Commission: 0.05% (to simulate exchange fees).
✔ Slippage: 1-2 (to account for execution delay).
✔ Date Range: Test across different market conditions.
📢 TradingView Disclaimer
📌 This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk, and past performance does not guarantee future results. Always test strategies thoroughly before applying them in a live market. Users are responsible for their own trading decisions.
🚀 Why Choose Apex Trend Sniper?
✅ Non-Repainting – No misleading signals.
✅ Multi-Layer Confirmation – Reduces false trades.
✅ Volume & Trend Strength Validation – Ensures high-probability entries.
✅ Adaptive Risk Management – Secures profits while maximizing trends.
✅ Versatile Across Markets & Timeframes – Works for crypto, forex, and stocks.
📢 Start Trading Smarter with Apex Trend Sniper! 🚀
🔗 Try it now on TradingView and optimize your trend-following strategy. 🔥
QuantJazz Turbine Trader BETA v1.17QuantJazz Turbine Trader BETA v1.17 - Strategy Introduction and User Guide
Strategy Introduction
Welcome to the QuantJazz Turbine Trader BETA v1.17, a comprehensive trading strategy designed for TradingView. This strategy is built upon oscillator principles, drawing inspiration from the Turbo Oscillator by RedRox, and incorporates multiple technical analysis concepts including RSI, MFI, Stochastic oscillators, divergence detection, and an optional FRAMA (Fractal Adaptive Moving Average) filter.
The Turbine Trader aims to provide traders with a flexible toolkit for identifying potential entry and exit points in the market. It presents information through a main signal line oscillator, a histogram, and various visual cues like dots, triangles, and divergence lines directly on the indicator panel. The strategy component allows users to define specific conditions based on these visual signals to trigger automated long or short trades within the TradingView environment.
This guide provides an overview of the strategy's components, settings, and usage. Please remember that this is a BETA version (v1.17). While developed with care, it may contain bugs or behave unexpectedly.
LEGAL DISCLAIMER: QuantJazz makes no claims about the fitness or profitability of this tool. Trading involves significant risk, and you may lose all of your invested capital. All trading decisions made using this strategy are solely at the user's discretion and responsibility. Past performance is not indicative of future results. Always conduct thorough backtesting and risk assessment before deploying any trading strategy with real capital.
This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International.
Core Concepts and Visual Elements
The Turbine Trader indicator displays several components in its own panel below the main price chart:
1. Signal Line (Avg & Avg2): This is the primary oscillator. It's a composite indicator derived from RSI, MFI (Money Flow Index), and Stochastic calculations, smoothed using an EMA (Exponential Moving Average).
Avg: The faster smoothed signal line.
Avg2: The slower smoothed signal line.
Color Coding: The space between Avg and Avg2 is filled. The color (Neon Blue/gColor or Neon Purple/rColor) indicates the trend based on the relationship between Avg and Avg2. Blue suggests bullish momentum (Avg > Avg2), while Purple suggests bearish momentum (Avg2 > Avg).
Zero Line Crosses: Crossovers of the Avg line with the zero level can indicate shifts in momentum.
2. Histogram (resMfi): This histogram is based on smoothed and transformed MFI calculations (Fast MFI and Slow MFI).
Color Coding: Bars are colored Neon Blue (histColorUp) when above zero, suggesting bullish pressure, and Neon Purple (histColorDn) when below zero, suggesting bearish pressure. Transparency is applied.
Zero Line Crosses: Crossovers of the histogram with the zero level can signal potential shifts in money flow.
3. Reversal Points (Dots): Dots appear on the Signal Line (specifically on Avg2) when the color changes (i.e., Avg crosses Avg2).
Small Dots: Appear when a reversal occurs while the oscillator is in an "extreme" zone (below -60 for bullish reversals, above +60 for bearish reversals).
Large Dots: Appear when a reversal occurs outside of these extreme zones.
Colors: Blue (gRdColor) for bullish reversals (Avg crossing above Avg2), Purple (rRdColor) for bearish reversals (Avg crossing below Avg2).
4. Take Profit (TP) Signals (Triangles): Small triangles appear above (+120) or below (-120) the zero line.
Bearish Triangle (Down, Purple rTpColor): Suggests a potential exit point for long positions or an entry point for short positions, based on the oscillator losing upward momentum above the 50 level.
Bullish Triangle (Up, Blue gTpColor): Suggests a potential exit point for short positions or an entry point for long positions, based on the oscillator losing downward momentum below the -50 level.
5. Divergence Lines: The strategy automatically detects and draws potential regular and hidden divergences between the price action (highs/lows) and the Signal Line (Avg).
Regular Bullish Divergence (White bullDivColor line, ⊚︎ label): Price makes a lower low, but the oscillator makes a higher low. Suggests potential bottoming.
Regular Bearish Divergence (White bearDivColor line, ⊚︎ label): Price makes a higher high, but the oscillator makes a lower high. Suggests potential topping.
Hidden Bullish Divergence (bullHidDivColor line, ⊚︎ label): Price makes a higher low, but the oscillator makes a lower low. Suggests potential continuation of an uptrend.
Hidden Bearish Divergence (bearHidDivColor line, ⊚︎ label): Price makes a lower high, but the oscillator makes a higher high. Suggests potential continuation of a downtrend.
Delete Broken Divergence Lines: If enabled, newer divergence lines originating from a similar point will replace older ones.
6. Status Line: A visual bar at the top (95 to 105) and bottom (-95 to -105) of the indicator panel. Its color intensity reflects the confluence of signals:
Score Calculation: +1 if Avg > Avg2, +1 if Avg > 0, +1 if Histogram > 0.
Top Bar (Bullish): Bright Blue (gStatColor) if score is 3, Faded Blue if score is 2, Black otherwise.
Bottom Bar (Bearish): Bright Purple (rStatColor) if score is 0, Faded Purple if score is 1, Black otherwise.
Strategy Settings Explained
The strategy's behavior is controlled via the settings panel (gear icon).
1. Date Range:
Start Date, End Date: Define the period for backtesting. Trades will only occur within this range.
2. Optional Webhook Configuration: (For Automation)
3C Email Token, 3C Bot ID: Enter your 3Commas API credentials if you plan to automate trading using webhooks. The strategy generates JSON alert messages compatible with 3Commas. You can go ahead and just leave the text field as defaulted, "TOKEN HERE" / "BOT ID HERE" if not using any bot automations at this time. You can always come back later and automate it. More info can be made available from QuantJazz should you need automation assistance with custom indicators and trading strategies.
3. 🚀 Signal Line:
Turn On/Off: Show or hide the main signal lines (Avg, Avg2).
gColor, rColor: Set the colors for bullish and bearish signal line states.
Length (RSI): The lookback period for the internal RSI calculation. Default is 2.
Smooth (EMA): The smoothing period for the EMAs applied to the composite signal. Default is 9.
RSI Source: The price source used for RSI calculation (default: close).
4. 📊 Histogram:
Turn On/Off: Show or hide the histogram.
histColorUp, histColorDn: Set the colors for positive and negative histogram bars.
Length (MFI): The base lookback period for MFI calculations. Default is 5. Fast and Slow MFI lengths are derived from this.
Smooth: Smoothing period for the final histogram output. Default is 1 (minimal smoothing).
5.💡 Other:
Show Divergence Line: Toggle visibility of regular divergence lines.
bullDivColor, bearDivColor: Colors for regular divergence lines.
Show Hidden Divergence: Toggle visibility of hidden divergence lines.
bullHidDivColor, bearHidDivColor: Colors for hidden divergence lines.
Show Status Line: Toggle visibility of the top/bottom status bars.
gStatColor, rStatColor: Colors for the status line bars.
Show TP Signal: Toggle visibility of the TP triangles.
gTpColor, rTpColor: Colors for the TP triangles.
Show Reversal points: Toggle visibility of the small/large dots on the signal line.
gRdColor, rRdColor: Colors for the reversal dots.
Delete Broken Divergence Lines: Enable/disable automatic cleanup of older divergence lines.
6. ⚙️ Strategy Inputs: (CRITICAL for Trade Logic)
This section defines which visual signals trigger trades. Each signal (Small/Large Dots, TP Triangles, Bright Bars, Signal/Histogram Crosses, Signal/Histogram Max/Min, Divergences) has a dropdown menu:
Long: This signal can trigger a long entry.
Short: This signal can trigger a short entry.
Disabled: This signal will not trigger any entry.
Must Be True Checkbox: If checked for a specific signal, that signal's condition must be met for any trade (long or short, depending on the dropdown selection for that signal) to be considered. Multiple "Must Be True" conditions act as AND logic – all must be true simultaneously.
How it Works:
The strategy first checks if all conditions marked as "Must Be True" (for the relevant trade direction - long or short) are met.
If all "Must Be True" conditions are met, it then checks if at least one of the conditions not marked as "Must Be True" (and set to "Long" or "Short" respectively) is also met.
If both steps pass, and other filters (like Date Range, FRAMA) allow, an entry order is placed.
Example: If "Large Bullish Dot" is set to "Long" and "Must Be True" is checked, AND "Bullish Divergence" is set to "Long" but "Must Be True" is not checked: A long entry requires BOTH the Large Bullish Dot AND the Bullish Divergence to occur simultaneously. If "Large Bullish Dot" was "Long" but not "Must Be True", then EITHER a Large Bullish Dot OR a Bullish Divergence could trigger a long entry (assuming no other "Must Be True" conditions are active).
Note: By default, the strategy is configured for long-only trades (strategy.risk.allow_entry_in(strategy.direction.long)). To enable short trades, you would need to comment out or remove this line in the Pine Script code and configure the "Strategy Inputs" accordingly.
7. 💰 Take Profit Settings:
Take Profit 1/2/3 (%): The percentage above the entry price (for longs) or below (for shorts) where each TP level is set. (e.g., 1.0 means 1% profit).
TP1/2/3 Percentage: The percentage of the currently open position to close when the corresponding TP level is hit. The percentages should ideally sum to 100% if you intend to close the entire position across the TPs.
Trailing Stop (%): The percentage below the highest high (for longs) or above the lowest low (for shorts) reached after the activation threshold, where the stop loss will trail.
Trailing Stop Activation (%): The minimum profit percentage the trade must reach before the trailing stop becomes active.
Re-entry Delay (Bars): The minimum number of bars to wait after a TP is hit before considering a re-entry. Default is 1 (allows immediate re-entry on the next bar if conditions met).
Re-entry Price Offset (%): The percentage the price must move beyond the previous TP level before a re-entry is allowed. This prevents immediate re-entry if the price hovers around the TP level.
8. 📈 FRAMA Filter: (Optional Trend Filter)
Use FRAMA Filter: Enable or disable the filter.
FRAMA Source, FRAMA Period, FRAMA Fast MA, FRAMA Slow MA: Parameters for the FRAMA calculation. Defaults provided are common starting points.
FRAMA Filter Type:
FRAMA > previous bars: Allows trades only if FRAMA is significantly above its recent average (defined by FRAMA Percentage and FRAMA Lookback). Typically used to confirm strong upward trends for longs.
FRAMA < price: Allows trades only if FRAMA is below the current price (framaSource). Can act as a baseline trend filter.
FRAMA Percentage (X), FRAMA Lookback (Y): Used only for the FRAMA > previous bars filter type.
How it Affects Trades: If Use FRAMA Filter is enabled:
Long entries require the FRAMA filter condition to be true.
Short entries require the FRAMA filter condition to be false (as currently coded, this acts as an inverse filter for shorts if enabled).
How to Use the Strategy
1. Apply to Chart: Open your desired chart on TradingView. Click "Indicators", find "QuantJazz Turbine Trader BETA v1.17" (you might need to add it via Invite-only scripts or if published publicly), and add it to your chart. The oscillator appears below the price chart, and the strategy tester panel opens at the bottom.
2. Configure Strategy Properties: In the Pine Script code itself (or potentially via the UI if supported), adjust the strategy() function parameters like initial_capital, default_qty_value, commission_value, slippage, etc., to match your account, broker fees, and risk settings. The user preferences provided (e.g., 1000 initial capital, 0.1% commission) are examples. Remember use_bar_magnifier is false by default in v1.17.
3. Configure Inputs (Settings Panel):
Set the Date Range for backtesting.
Crucially, configure the ⚙️ Strategy Inputs. Decide which signals should trigger entries and whether they are mandatory ("Must Be True"). Start simply, perhaps enabling only one or two signals initially, and test thoroughly. Remember the default long-only setting unless you modify the code.
Set up your 💰 Take Profit Settings, including TP levels, position size percentages for each TP, and the trailing stop parameters. Decide if you want to use the re-entry feature.
Decide whether to use the 📈 FRAMA Filter and configure its parameters if enabled.
Adjust visual elements (🚀 Signal Line, 📊 Histogram, 💡 Other) as needed for clarity.
4. Backtest: Use the Strategy Tester panel in TradingView. Analyze the performance metrics (Net Profit, Max Drawdown, Profit Factor, Win Rate, Trade List) across different assets, timeframes, and setting configurations. Pay close attention to how different "Strategy Inputs" combinations perform.
5. Refine: Based on backtesting results, adjust the input settings, TP/SL strategy, and signal combinations to optimize performance for your chosen market and timeframe, while being mindful of overfitting.
6. Automation (Optional): If using 3Commas or a similar platform:
Enter your 3C Email Token and 3C Bot ID in the settings.
Create alerts in TradingView (right-click on the chart or use the Alert panel).
Set the Condition to "QuantJazz Turbine Trader BETA v1.17".
In the "Message" box, paste the corresponding placeholder, which will pass the message in JSON from our custom code to TradingView to pass through your webhook: {{strategy.order.alert_message}}.
In the next tab, configure the Webhook URL provided by your automation platform. Put a Whale sound, while you're at it! 🐳
When an alert triggers, TradingView will send the pre-formatted JSON message from the strategy code to your webhook URL.
Final Notes
The QuantJazz Turbine Trader BETA v1.17 offers a wide range of customizable signals and strategy logic. Its effectiveness heavily depends on proper configuration and thorough backtesting specific to the traded asset and timeframe. Start with the default settings, understand each component, and methodically test different combinations of signals and parameters. Remember the inherent risks of trading and never invest capital you cannot afford to lose.
Buy on 5% dip strategy with time adjustment
This script is a strategy called "Buy on 5% Dip Strategy with Time Adjustment 📉💡," which detects a 5% drop in price and triggers a buy signal 🔔. It also automatically closes the position once the set profit target is reached 💰, and it has additional logic to close the position if the loss exceeds 14% after holding for 230 days ⏳.
Strategy Explanation
Buy Condition: A buy signal is triggered when the price drops 5% from the highest price reached 🔻.
Take Profit: The position is closed when the price hits a 1.22x target from the average entry price 📈.
Forced Sell Condition: If the position is held for more than 230 days and the loss exceeds 14%, the position is automatically closed 🚫.
Leverage & Capital Allocation: Leverage is adjustable ⚖️, and you can set the percentage of capital allocated to each trade 💸.
Time Limits: The strategy allows you to set a start and end time ⏰ for trading, making the strategy active only within that specific period.
Code Credits and References
Credits: This script utilizes ideas and code from @QuantNomad and jangdokang for the profit table and algorithm concepts 🔧.
Sources:
Monthly Performance Table Script by QuantNomad:
ZenAndTheArtOfTrading's Script:
Strategy Performance
This strategy provides risk management through take profit and forced sell conditions and includes a performance table 📊 to track monthly and yearly results. You can compare backtest results with real-time performance to evaluate the strategy's effectiveness.
The performance numbers shown in the backtest reflect what would have happened if you had used this strategy since the launch date of the SOXL (the Direxion Daily Semiconductor Bull 3x Shares ETF) 📅. These results are not hypothetical but based on actual performance from the day of the ETF’s launch 📈.
Caution ⚠️
No Guarantee of Future Results: The results are based on historical performance from the launch of the SOXL ETF, but past performance does not guarantee future results. It’s important to approach with caution when applying it to live trading 🔍.
Risk Management: Leverage and capital allocation settings are crucial for managing risk ⚠️. Make sure to adjust these according to your risk tolerance ⚖️.
FlexATRFlexATR: A Dynamic Multi-Timeframe Trading Strategy
Overview: FlexATR is a versatile trading strategy that dynamically adapts its key parameters based on the timeframe being used. It combines technical signals from exponential moving averages (EMAs) and the Relative Strength Index (RSI) with volatility-based risk management via the Average True Range (ATR). This approach helps filter out false signals while adjusting to varying market conditions — whether you’re trading on a daily chart, intraday charts (30m, 60m, or 5m), or even on higher timeframes like the 4-hour or weekly charts.
How It Works:
Multi-Timeframe Parameter Adaptation: FlexATR is designed to automatically adjust its indicator settings depending on the timeframe:
Daily and Weekly: On higher timeframes, the strategy uses longer periods for the fast and slow EMAs and standard periods for RSI and ATR to capture more meaningful trend confirmations while minimizing noise.
Intraday (e.g., 30m, 60m, 5m, 4h): The parameters are converted from “days” into the corresponding number of bars. For instance, on a 30-minute chart, a “day” might equal 48 bars. The preset values for a 30-minute chart have been slightly reduced (e.g., a fast EMA is set at 0.35 days instead of 0.4) to improve reactivity while maintaining robust filtering.
Signal Generation:
Entry Signals: The strategy enters long positions when the fast EMA crosses above the slow EMA and the RSI is above 50, and it enters short positions when the fast EMA crosses below the slow EMA with the RSI below 50. This dual confirmation helps ensure that signals are reliable.
Risk Management: The ATR is used to compute dynamic levels for stop loss and profit target:
Stop Loss: For a long position, the stop loss is placed at Price - (ATR × Stop Loss Multiplier). For a short position, it is at Price + (ATR × Stop Loss Multiplier).
Profit Target: The profit target is similarly set using the ATR multiplied by a designated profit multiplier.
Dynamic Trailing Stop: FlexATR further incorporates a dynamic trailing stop (if enabled) that adjusts according to the ATR. This trailing stop follows favorable price movements at a distance defined by a multiplier, locking in gains as the trend develops. The use of a trailing stop helps protect profits without requiring a fixed exit point.
Capital Allocation: Each trade is sized at 10% of the total equity. This percentage-based position sizing allows the strategy to scale with your account size. While the current setup assumes no leverage (a 1:1 exposure), the inherent design of the strategy means you can adjust the leverage externally if desired, with risk metrics scaling accordingly.
Visual Representation: For clarity and accessibility (especially for those with color vision deficiencies), FlexATR employs a color-blind friendly palette (the Okabe-Ito palette):
EMA Fast: Displayed in blue.
EMA Slow: Displayed in orange.
Stop Loss Levels: Rendered in vermilion.
Profit Target Levels: Shown in a distinct azzurro (light blue).
Benefits and Considerations:
Reliability: By requiring both EMA crossovers and an RSI confirmation, FlexATR filters out a significant amount of market noise, which reduces false signals at the expense of some delayed entries.
Adaptability: The automatic conversion of “day-based” parameters into bar counts for intraday charts means the strategy remains consistent across different timeframes.
Risk Management: Using the ATR for both fixed and trailing stops allows the strategy to adapt to changing market volatility, helping to protect your capital.
Flexibility: The strategy’s inputs are customizable via the input panel, allowing traders to fine-tune the parameters for different assets or market conditions.
Conclusion: FlexATR is designed as a balanced, adaptive strategy that emphasizes reliability and robust risk management across a variety of timeframes. While it may sometimes enter trades slightly later due to its filtering mechanism, its focus on confirming trends helps reduce the likelihood of false signals. This makes it particularly attractive for traders who prioritize a disciplined, multi-timeframe approach to capturing market trends.
Advanced Adaptive Grid Trading StrategyThis strategy employs an advanced grid trading approach that dynamically adapts to market conditions, including trend, volatility, and risk management considerations. The strategy aims to capitalize on price fluctuations in both rising (long) and falling (short) markets, as well as during sideways movements. It combines multiple indicators to determine the trend and automatically adjusts grid parameters for more efficient trading.
How it Works:
Trend Analysis:
Short, long, and super long Moving Averages (MA) to determine the trend direction.
RSI (Relative Strength Index) to identify overbought and oversold levels, and to confirm the trend.
MACD (Moving Average Convergence Divergence) to confirm momentum and trend direction.
Momentum indicator.
The strategy uses a weighted scoring system to assess trend strength (strong bullish, moderate bullish, strong bearish, moderate bearish, sideways).
Grid System:
The grid size (the distance between buy and sell levels) changes dynamically based on market volatility, using the ATR (Average True Range) indicator.
Grid density also adapts to the trend: in a strong trend, the grid is denser in the direction of the trend.
Grid levels are shifted depending on the trend direction (upwards in a bear market, downwards in a bull market).
Trading Logic:
The strategy opens long positions if the trend is bullish and the price reaches one of the lower grid levels.
It opens short positions if the trend is bearish and the price reaches one of the upper grid levels.
In a sideways market, it can open positions in both directions.
Risk Management:
Stop Loss for every position.
Take Profit for every position.
Trailing Stop Loss to protect profits.
Maximum daily loss limit.
Maximum number of positions limit.
Time-based exit (if the position is open for too long).
Risk-based position sizing (optional).
Input Options:
The strategy offers numerous settings that allow users to customize its operation:
Timeframe: The chart's timeframe (e.g., 1 minute, 5 minutes, 1 hour, 4 hours, 1 day, 1 week).
Base Grid Size (%): The base size of the grid, expressed as a percentage.
Max Positions: The maximum number of open positions allowed.
Use Volatility Grid: If enabled, the grid size changes dynamically based on the ATR indicator.
ATR Length: The period of the ATR indicator.
ATR Multiplier: The multiplier for the ATR to fine-tune the grid size.
RSI Length: The period of the RSI indicator.
RSI Overbought: The overbought level for the RSI.
RSI Oversold: The oversold level for the RSI.
Short MA Length: The period of the short moving average.
Long MA Length: The period of the long moving average.
Super Long MA Length: The period of the super long moving average.
MACD Fast Length: The fast period of the MACD.
MACD Slow Length: The slow period of the MACD.
MACD Signal Length: The period of the MACD signal line.
Stop Loss (%): The stop loss level, expressed as a percentage.
Take Profit (%): The take profit level, expressed as a percentage.
Use Trailing Stop: If enabled, the strategy uses a trailing stop loss.
Trailing Stop (%): The trailing stop loss level, expressed as a percentage.
Max Loss Per Day (%): The maximum daily loss, expressed as a percentage.
Time Based Exit: If enabled, the strategy exits the position after a certain amount of time.
Max Holding Period (hours): The maximum holding time in hours.
Use Risk Based Position: If enabled, the strategy calculates position size based on risk.
Risk Per Trade (%): The risk per trade, expressed as a percentage.
Max Leverage: The maximum leverage.
Important Notes:
This strategy does not guarantee profits. Cryptocurrency markets are volatile, and trading involves risk.
The strategy's effectiveness depends on market conditions and settings.
It is recommended to thoroughly backtest the strategy under various market conditions before using it live.
Past performance is not indicative of future results.
Multi-Timeframe MACD Strategy ver 1.0Multi-Timeframe MACD Strategy: Enhanced Trend Trading with Customizable Entry and Trailing Stop
This strategy utilizes the Moving Average Convergence Divergence (MACD) indicator across multiple timeframes to identify strong trends, generate precise entry and exit signals, and manage risk with an optional trailing stop loss. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trade accuracy, reduce exposure to false signals, and capture larger market moves.
Key Features:
Dual Timeframe Analysis: Calculates and analyzes the MACD on both the current chart's timeframe and a user-selected higher timeframe (e.g., Daily MACD on a 1-hour chart). This provides a broader market context, helping to confirm trends and filter out short-term noise.
Configurable MACD: Fine-tune the MACD calculation with adjustable Fast Length, Slow Length, and Signal Length parameters. Optimize the indicator's sensitivity to match your trading style and the volatility of the asset.
Flexible Entry Options: Choose between three distinct entry types:
Crossover: Enters trades when the MACD line crosses above (long) or below (short) the Signal line.
Zero Cross: Enters trades when the MACD line crosses above (long) or below (short) the zero line.
Both: Combines both Crossover and Zero Cross signals, providing more potential entry opportunities.
Independent Timeframe Control: Display and trade based on the current timeframe MACD, the higher timeframe MACD, or both. This allows you to focus on the information most relevant to your analysis.
Optional Trailing Stop Loss: Implements a configurable trailing stop loss to protect profits and limit potential losses. The trailing stop is adjusted dynamically as the price moves in your favor, based on a user-defined percentage.
No Repainting: Employs lookahead=barmerge.lookahead_off in the request.security() function to prevent data leakage and ensure accurate backtesting and real-time signals.
Clear Visual Signals (Optional): Includes optional plotting of the MACD and Signal lines for both timeframes, with distinct colors for easy visual identification. These plots are for visual confirmation and are not required for the strategy's logic.
Suitable for Various Trading Styles: Adaptable to swing trading, day trading, and trend-following strategies across diverse markets (stocks, forex, cryptocurrencies, etc.).
Fully Customizable: All parameters are adjustable, including timeframes, MACD Settings, Entry signal type and trailing stop settings.
How it Works:
MACD Calculation: The strategy calculates the MACD (using the standard formula) for both the current chart's timeframe and the specified higher timeframe.
Trend Identification: The relationship between the MACD line, Signal line, and zero line is used to determine the current trend for each timeframe.
Entry Signals: Buy/sell signals are generated based on the selected "Entry Type":
Crossover: A long signal is generated when the MACD line crosses above the Signal line, and both timeframes are in agreement (if both are enabled). A short signal is generated when the MACD line crosses below the Signal line, and both timeframes are in agreement.
Zero Cross: A long signal is generated when the MACD line crosses above the zero line, and both timeframes agree. A short signal is generated when the MACD line crosses below the zero line and both timeframes agree.
Both: Combines Crossover and Zero Cross signals.
Trailing Stop Loss (Optional): If enabled, a trailing stop loss is set at a specified percentage below (for long positions) or above (for short positions) the entry price. The stop-loss is automatically adjusted as the price moves favorably.
Exit Signals:
Without Trailing Stop: Positions are closed when the MACD signals reverse according to the selected "Entry Type" (e.g., a long position is closed when the MACD line crosses below the Signal line if using "Crossover" entries).
With Trailing Stop: Positions are closed if the price hits the trailing stop loss.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to assess its performance and optimize parameters for different assets and timeframes.
Example Use Cases:
Confirming Trend Strength: A trader on a 1-hour chart sees a bullish MACD crossover on the current timeframe. They check the MTF MACD strategy and see that the Daily MACD is also bullish, confirming the strength of the uptrend.
Filtering Noise: A trader using a 15-minute chart wants to avoid false signals from short-term volatility. They use the strategy with a 4-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and enables the trailing stop loss. As the price rises, the trailing stop is automatically adjusted upwards, protecting profits. The trade is exited either when the MACD reverses or when the price hits the trailing stop.
Disclaimer:
The MACD is a lagging indicator and can produce false signals, especially in ranging markets. This strategy is for educational and informational purposes only and should not be considered financial advice. Backtest and optimize the strategy thoroughly, combine it with other technical analysis tools, and always implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Multi-Timeframe Parabolic SAR Strategy ver 1.0Multi-Timeframe Parabolic SAR Strategy (MTF PSAR) - Enhanced Trend Trading
This strategy leverages the power of the Parabolic SAR (Stop and Reverse) indicator across multiple timeframes to provide robust trend identification, precise entry/exit signals, and dynamic trailing stop management. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trading accuracy, reduce risk, and capture more significant market moves.
Key Features:
Dual Timeframe Analysis: Simultaneously analyzes the Parabolic SAR on the current chart and a higher timeframe (e.g., Daily PSAR on a 1-hour chart). This allows you to align your trades with the dominant trend and filter out noise from lower timeframes.
Configurable PSAR: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values to optimize sensitivity for your trading style and the asset's volatility.
Independent Timeframe Control: Choose to display and trade based on either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the most relevant information for your analysis.
Clear Visual Signals: Distinct colors for the current and higher timeframe PSAR dots provide a clear visual representation of potential entry and exit points.
Multiple Entry Strategies: The strategy offers flexible entry conditions, allowing you to trade based on:
Confirmation: Both current and higher timeframe PSAR signals agree and the current timeframe PSAR has just flipped direction. (Most conservative)
Current Timeframe Only: Trades based solely on the current timeframe PSAR, ideal for when the higher timeframe is less relevant or disabled.
Higher Timeframe Only: Trades based solely on the higher timeframe PSAR.
Dynamic Trailing Stop (PSAR-Based): Implements a trailing stop-loss based on the current timeframe's Parabolic SAR. This helps protect profits by automatically adjusting the stop-loss as the price moves in your favor. Exits are triggered when either the current or HTF PSAR flips.
No Repainting: Uses lookahead=barmerge.lookahead_off in the security() function to ensure that the higher timeframe data is accessed without any data leakage, preventing repainting issues.
Fully Configurable: All parameters (PSAR settings, higher timeframe, visibility, colors) are adjustable through the strategy's settings panel, allowing for extensive customization and optimization.
Suitable for Various Trading Styles: Applicable to swing trading, day trading, and trend-following strategies across various markets (stocks, forex, cryptocurrencies, etc.).
How it Works:
PSAR Calculation: The strategy calculates the standard Parabolic SAR for both the current chart's timeframe and the selected higher timeframe.
Trend Identification: The direction of the PSAR (dots below price = uptrend, dots above price = downtrend) determines the current trend for each timeframe.
Entry Signals: The strategy generates buy/sell signals based on the chosen entry strategy (Confirmation, Current Timeframe Only, or Higher Timeframe Only). The Confirmation strategy offers the highest probability signals by requiring agreement between both timeframes.
Trailing Stop Exit: Once a position is entered, the strategy uses the current timeframe PSAR as a dynamic trailing stop. The stop-loss is automatically adjusted as the PSAR dots move, helping to lock in profits and limit losses. The strategy exits when either the Current or HTF PSAR changes direction.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to evaluate its performance and optimize the settings for different assets and timeframes.
Example Use Cases:
Trend Confirmation: A trader on a 1-hour chart observes a bullish PSAR flip on the current timeframe. They check the MTF PSAR strategy and see that the Daily PSAR is also bullish, confirming the strength of the uptrend and providing a high-probability long entry signal.
Filtering Noise: A trader on a 5-minute chart wants to avoid whipsaws caused by short-term price fluctuations. They use the strategy with a 1-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and uses the current timeframe PSAR as a trailing stop. As the price rises, the PSAR dots move upwards, automatically raising the stop-loss and protecting profits. The trade is exited when the current (or HTF) PSAR flips to bearish.
Disclaimer:
The Parabolic SAR is a lagging indicator and can produce false signals, particularly in ranging or choppy markets. This strategy is intended for educational and informational purposes only and should not be considered financial advice. It is essential to backtest and optimize the strategy thoroughly, use it in conjunction with other technical analysis tools, and implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Always conduct your own due diligence and consider your risk tolerance before making any trading decisions.
IU Gap Fill StrategyThe IU Gap Fill Strategy is designed to capitalize on price gaps that occur between trading sessions. It identifies gaps based on a user-defined percentage threshold and executes trades when the price fills the gap within a day. This strategy is ideal for traders looking to take advantage of market inefficiencies that arise due to overnight or session-based price movements. An ATR-based trailing stop-loss is incorporated to dynamically manage risk and lock in profits.
USER INPUTS
Percentage Difference for Valid Gap - Defines the minimum gap size in percentage terms for a valid trade setup. ( Default is 0.2 )
ATR Length - Sets the lookback period for the Average True Range (ATR) calculation. (default is 14 )
ATR Factor - Determines the multiplier for the trailing stop-loss, helping in risk management. ( Default is 2.00 )
LONG CONDITION
A gap-up occurs, meaning the current session opens above the previous session’s close.
The price initially dips below the previous session's close but then recovers and closes above it.
The gap meets the valid percentage threshold set by the user.
The bar is not the first or last bar of the session to avoid false signals.
SHORT CONDITION
A gap-down occurs, meaning the current session opens below the previous session’s close.
The price initially moves above the previous session’s close but then closes below it.
The gap meets the valid percentage threshold set by the user.
The bar is not the first or last bar of the session to avoid false signals.
LONG EXIT
An ATR-based trailing stop-loss is set below the entry price and dynamically adjusts upwards as the price moves in favor of the trade.
The position is closed when the trailing stop-loss is hit.
SHORT EXIT
An ATR-based trailing stop-loss is set above the entry price and dynamically adjusts downwards as the price moves in favor of the trade.
The position is closed when the trailing stop-loss is hit.
WHY IT IS UNIQUE
Precision in Identifying Gaps - The strategy focuses on real price gaps rather than minor fluctuations.
Dynamic Risk Management - Uses ATR-based trailing stop-loss to secure profits while allowing the trade to run.
Versatility - Works on stocks, indices, forex, and any market that experiences session-based gaps.
Optimized Entry Conditions - Ensures entries are taken only when the price attempts to fill the gap, reducing false signals.
HOW USERS CAN BENEFIT FROM IT
Enhance Trade Timing - Captures high-probability trade setups based on market inefficiencies caused by gaps.
Minimize Risk - The ATR trailing stop-loss helps protect gains and limit losses.
Works in Different Market Conditions - Whether markets are trending or consolidating, the strategy adapts to potential gap fill opportunities.
Fully Customizable - Users can fine-tune gap percentage, ATR settings, and stop-loss parameters to match their trading style.
Long-Only MTF EMA Cloud StrategyOverview:
The Long-Only EMA Cloud Strategy is a powerful trend-following strategy designed to help traders identify and capitalize on bullish market conditions. By utilizing an Exponential Moving Average (EMA) Cloud, this strategy provides clear and reliable signals for entering long positions when the market trend is favorable. The EMA cloud acts as a visual representation of the trend, making it easier for traders to make informed decisions. This strategy is ideal for traders who prefer to trade in the direction of the trend and focus exclusively on long positions.
Key Features:
EMA Cloud:
The strategy uses two EMAs (short and long) to create a dynamic cloud.
The cloud is bullish when the short EMA is above the long EMA, indicating a strong upward trend.
The cloud is bearish when the short EMA is below the long EMA, indicating a downward trend or consolidation.
Long Entry Signals:
A long position is opened when the EMA cloud turns bullish, which occurs when the short EMA crosses above the long EMA.
This crossover signals a potential shift in market sentiment from bearish to bullish, providing an opportunity to enter a long trade.
Adjustable Timeframe:
The EMA cloud can be calculated on the same timeframe as the chart or on a higher/lower timeframe for multi-timeframe analysis.
This flexibility allows traders to adapt the strategy to their preferred trading style and time horizon.
Risk Management:
The strategy includes adjustable stop loss and take profit levels to help traders manage risk and lock in profits.
Stop loss and take profit levels are calculated as a percentage of the entry price, ensuring consistency across different assets and market conditions.
Alerts:
Built-in alerts notify you when a long entry signal is generated, ensuring you never miss a trading opportunity.
Alerts can be customized to suit your preferences, providing real-time notifications for potential trades.
Visualization:
The EMA cloud is plotted on the chart, providing a clear visual representation of the trend.
Buy signals are marked with a green label below the price bar, making it easy to identify entry points.
How to Use:
Add the Script:
Add the script to your chart in TradingView.
Set EMA Lengths:
Adjust the Short EMA Length and Long EMA Length in the settings to suit your trading style.
For example, you might use a shorter EMA (e.g., 21) for more responsive signals or a longer EMA (e.g., 50) for smoother signals.
Choose EMA Cloud Resolution:
Select the EMA Cloud Resolution (timeframe) for the cloud calculation.
You can choose the same timeframe as the chart or a different timeframe (higher or lower) for multi-timeframe analysis.
Adjust Risk Management:
Set the Stop Loss (%) and Take Profit (%) levels according to your risk tolerance and trading goals.
For example, you might use a 1% stop loss and a 2% take profit for a 1:2 risk-reward ratio.
Enable Alerts:
Enable alerts to receive notifications for long entry signals.
Alerts can be configured to send notifications via email, SMS, or other preferred methods.
Monitor and Trade:
Monitor the chart for buy signals and execute trades accordingly.
Use the EMA cloud as a visual guide to confirm the trend direction before entering a trade.
Ideal For:
Trend-Following Traders: This strategy is perfect for traders who prefer to trade in the direction of the trend and capitalize on sustained price movements.
Long-Only Traders: If you prefer to focus exclusively on long positions, this strategy provides a clear and systematic approach to identifying bullish opportunities.
Multi-Timeframe Analysts: The adjustable EMA cloud resolution allows you to analyze trends across different timeframes, making it suitable for both short-term and long-term traders.
Risk-Averse Traders: The inclusion of stop loss and take profit levels helps manage risk and protect your capital.
Divergence IQ [TradingIQ]Hello Traders!
Introducing "Divergence IQ"
Divergence IQ lets traders identify divergences between price action and almost ANY TradingView technical indicator. This tool is designed to help you spot potential trend reversals and continuation patterns with a range of configurable features.
Features
Divergence Detection
Detects both regular and hidden divergences for bullish and bearish setups by comparing price movements with changes in the indicator.
Offers two detection methods: one based on classic pivot point analysis and another that provides immediate divergence signals.
Option to use closing prices for divergence detection, allowing you to choose the data that best fits your strategy.
Normalization Options:
Includes multiple normalization techniques such as robust scaling, rolling Z-score, rolling min-max, or no normalization at all.
Adjustable normalization window lets you customize the indicator to suit various market conditions.
Option to display the normalized indicator on the chart for clearer visual comparison.
Allows traders to take indicators that aren't oscillators, and convert them into an oscillator - allowing for better divergence detection.
Simulated Trade Management:
Integrates simulated trade entries and exits based on divergence signals to demonstrate potential trading outcomes.
Customizable exit strategies with options for ATR-based or percentage-based stop loss and profit target settings.
Automatically calculates key trade metrics such as profit percentage, win rate, profit factor, and total trade count.
Visual Enhancements and On-Chart Displays:
Color-coded signals differentiate between bullish, bearish, hidden bullish, and hidden bearish divergence setups.
On-chart labels, lines, and gradient flow visualizations clearly mark divergence signals, entry points, and exit levels.
Configurable settings let you choose whether to display divergence signals on the price chart or in a separate pane.
Performance Metrics Table:
A performance table dynamically displays important statistics like profit, win rate, profit factor, and number of trades.
This feature offers an at-a-glance assessment of how the divergence-based strategy is performing.
The image above shows Divergence IQ successfully identifying and trading a bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a bearish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bearish divergence between an indicator and price action!
The performance table is designed to provide a clear summary of simulated trade results based on divergence setups. You can easily review key metrics to assess the strategy’s effectiveness over different time periods.
Customization and Adaptability
Divergence IQ offers a wide range of configurable settings to tailor the indicator to your personal trading approach. You can adjust the lookback and lookahead periods for pivot detection, select your preferred method for normalization, and modify trade exit parameters to manage risk according to your strategy. The tool’s clear visual elements and comprehensive performance metrics make it a useful addition to your technical analysis toolbox.
The image above shows Divergence IQ identifying divergences between price action and OBV with no normalization technique applied.
While traders can look for divergences between OBV and price, OBV doesn't naturally behave like an oscillator, with no definable upper and lower threshold, OBV can infinitely increase or decrease.
With Divergence IQ's ability to normalize any indicator, traders can normalize non-oscillator technical indicators such as OBV, CVD, MACD, or even a moving average.
In the image above, the "Robust Scaling" normalization technique is selected. Consequently, the output of OBV has changed and is now behaving similar to an oscillator-like technical indicator. This makes spotting divergences between the indicator and price easier and more appropriate.
The three normalization techniques included will change the indicator's final output to be more compatible with divergence detection.
This feature can be used with almost any technical indicator.
Stop Type
Traders can select between ATR based profit targets and stop losses, or percentage based profit targets and stop losses.
The image above shows options for the feature.
Divergence Detection Method
A natural pitfall of divergence trading is that it generally takes several bars to "confirm" a divergence. This makes trading the divergence complicated, because the entry at time of the divergence might look great; however, the divergence wasn't actually signaled until several bars later.
To circumvent this issue, Divergence IQ offers two divergence detection mechanisms.
Pivot Detection
Pivot detection mode is the same as almost every divergence indicator on TradingView. The Pivots High Low indicator is used to detect market/indicator highs and lows and, consequently, divergences.
This method generally finds the "best looking" divergences, but will always take additional time to confirm the divergence.
Immediate Detection
Immediate detection mode attempts to reduce lag between the divergence and its confirmation to as little as possible while avoiding repainting.
Immediate detection mode still uses the Pivots Detection model to find the first high/low of a divergence. However, the most recent high/low does not utilize the Pivot Detection model, and instead immediately looks for a divergence between price and an indicator.
Immediate Detection Mode will always signal a divergence one bar after it's occurred, and traders can set alerts in this mode to be alerted as soon as the divergence occurs.
TradingView Backtester Integration
Divergence IQ is fully compatible with the TradingView backtester!
Divergence IQ isn’t designed to be a “profitable strategy” for users to trade. Instead, the intention of including the backtester is to let users backtest divergence-based trading strategies between the asset on their chart and almost any technical indicator, and to see if divergences have any predictive utility in that market.
So while the backtester is available in Divergence IQ, it’s for users to personally figure out if they should consider a divergence an actionable insight, and not a solicitation that Divergence IQ is a profitable trading strategy. Divergence IQ should be thought of as a Divergence backtesting toolkit, not a full-feature trading strategy.
Strategy Properties Used For Backtest
Initial Capital: $1000 - a realistic amount of starting capital that will resonate with many traders
Amount Per Trade: 5% of equity - a realistic amount of capital to invest relative to portfolio size
Commission: 0.02% - a conservative amount of commission to pay for trade that is standard in crypto trading, and very high for other markets.
Slippage: 1 tick - appropriate for liquid markets, but must be increased in markets with low activity.
Once more, the backtester is meant for traders to personally figure out if divergences are actionable trading signals on the market they wish to trade with the indicator they wish to use.
And that's all!
If you have any cool features you think can benefit Divergence IQ - please feel free to share them!
Thank you so much TradingView community!
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
Strategy SuperTrend SDI WebhookThis Pine Script™ strategy is designed for automated trading in TradingView. It combines the SuperTrend indicator and Smoothed Directional Indicator (SDI) to generate buy and sell signals, with additional risk management features like stop loss, take profit, and trailing stop. The script also includes settings for leverage trading, equity-based position sizing, and webhook integration.
Key Features
1. Date-based Trade Execution
The strategy is active only between the start and end dates set by the user.
times ensures that trades occur only within this predefined time range.
2. Position Sizing and Leverage
Uses leverage trading to adjust position size dynamically based on initial equity.
The user can set leverage (leverage) and percentage of equity (usdprcnt).
The position size is calculated dynamically (initial_capital) based on account performance.
3. Take Profit, Stop Loss, and Trailing Stop
Take Profit (tp): Defines the target profit percentage.
Stop Loss (sl): Defines the maximum allowable loss per trade.
Trailing Stop (tr): Adjusts dynamically based on trade performance to lock in profits.
4. SuperTrend Indicator
SuperTrend (ta.supertrend) is used to determine the market trend.
If the price is above the SuperTrend line, it indicates an uptrend (bullish).
If the price is below the SuperTrend line, it signals a downtrend (bearish).
Plots visual indicators (green/red lines and circles) to show trend changes.
5. Smoothed Directional Indicator (SDI)
SDI helps to identify trend strength and momentum.
It calculates +DI (bullish strength) and -DI (bearish strength).
If +DI is higher than -DI, the market is considered bullish.
If -DI is higher than +DI, the market is considered bearish.
The background color changes based on the SDI signal.
6. Buy & Sell Conditions
Long Entry (Buy) Conditions:
SDI confirms an uptrend (+DI > -DI).
SuperTrend confirms an uptrend (price crosses above the SuperTrend line).
Short Entry (Sell) Conditions:
SDI confirms a downtrend (+DI < -DI).
SuperTrend confirms a downtrend (price crosses below the SuperTrend line).
Optionally, trades can be filtered using crossovers (occrs option).
7. Trade Execution and Exits
Market entries:
Long (strategy.entry("Long")) when conditions match.
Short (strategy.entry("Short")) when bearish conditions are met.
Trade exits:
Uses predefined take profit, stop loss, and trailing stop levels.
Positions are closed if the strategy is out of the valid time range.
Usage
Automated Trading Strategy:
Can be integrated with webhooks for automated execution on supported trading platforms.
Trend-Following Strategy:
Uses SuperTrend & SDI to identify trend direction and strength.
Risk-Managed Leverage Trading:
Supports position sizing, stop losses, and trailing stops.
Backtesting & Optimization:
Can be used for historical performance analysis before deploying live.
Conclusion
This strategy is suitable for traders who want to automate their trading using SuperTrend and SDI indicators. It incorporates risk management tools like stop loss, take profit, and trailing stop, making it adaptable for leverage trading. Traders can customize settings, conduct backtests, and integrate it with webhooks for real-time trade execution. 🚀
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
is_strategyCorrection-Adaptive Trend Strategy (Open-Source)
Core Advantage: Designed specifically for the is_correction indicator, with full transparency and customization options.
Key Features:
Open-Source Code:
✅ Full access to the strategy logic – study how every trade signal is generated.
✅ Freedom to customize – modify entry/exit rules, risk parameters, or add new indicators.
✅ No black boxes – understand and trust every decision the strategy makes.
Built for is_correction:
Filters out false signals during market noise.
Works only in confirmed trends (is_correction = false).
Adaptable for Your Needs:
Change Take Profit/Stop Loss ratios directly in the code.
Add alerts, notifications, or integrate with other tools (e.g., Volume Profile).
For Developers/Traders:
Use the code as a template for your own strategies.
Test modifications risk-free on historical data.
How the Strategy Works:
Main Goal:
Automatically buys when the price starts rising and sells when it starts falling, but only during confirmed trends (ignoring temporary pullbacks).
What You See on the Chart:
📈 Up arrows ▼ (below the candle) = Buy signal.
📉 Down arrows ▲ (above the candle) = Sell signal.
Gray background = Market is in a correction (no trades).
Key Mechanics:
Buy Condition:
Price closes higher than the previous candle + is_correction confirms the main trend (not a pullback).
Example: Red candle → green candle → ▼ arrow → buy.
Sell Condition:
Price closes lower than the previous candle + is_correction confirms the trend (optional: turn off short-selling in settings).
Exit Rules:
Closes trades automatically at:
+0.5% profit (adjustable in settings).
-0.5% loss (adjustable).
Or if a reverse signal appears (e.g., sell signal after a buy).
User-Friendly Settings:
Sell – On (default: ON):
ON → Allows short-selling (selling when price falls).
OFF → Strategy only buys and closes positions.
Revers (default: OFF):
ON → Inverts signals (▼ = sell, ▲ = buy).
%Profit & %Loss:
Adjust these values (0-30%) to increase/decrease profit targets and risk.
Example Scenario:
Buy Signal:
Price rises for 3 days → green ▼ arrow → strategy buys.
Stop loss set 0.5% below entry price.
If price keeps rising → trade closes at +0.5% profit.
Correction Phase:
After a rally, price drops for 1 day → gray background → strategy ignores the drop (no action).
Stop Loss Trigger:
If price drops 0.5% from entry → trade closes automatically.
Key Features:
Correction Filter (is_correction):
Acts as a “noise filter” → avoids trades during temporary pullbacks.
Flexibility:
Disable short-selling, flip signals, or tweak profit/loss levels in seconds.
Transparency:
Open-source code → see exactly how every signal is generated (click “Source” in TradingView).
Tips for Beginners:
Test First:
Run the strategy on historical data (click the “Chart” icon in TradingView).
See how it performed in the past.
Customize It:
Increase %Profit to 2-3% for volatile assets like crypto.
Turn off Sell – On if short-selling confuses you.
Trust the Stop Loss:
Even if you think the price will rebound, the strategy will close at -0.5% to protect your capital.
Where to Find Settings:
Click the strategy name on the top-left of your chart → adjust sliders/toggles in the menu.
Русская Версия
Трендовая стратегия с открытым кодом
Главное преимущество: Полная прозрачность логики и адаптация под ваши нужды.
Особенности:
Открытый исходный код:
✅ Видите всю «кухню» стратегии – как формируются сигналы, когда открываются сделки.
✅ Меняйте правила – корректируйте тейк-профит, стоп-лосс или добавляйте новые условия.
✅ Никаких секретов – вы контролируете каждое правило.
Заточка под is_correction:
Игнорирует ложные сигналы в коррекциях.
Работает только в сильных трендах (is_correction = false).
Гибкая настройка:
Подстройте параметры под свой риск-менеджмент.
Добавьте свои индикаторы или условия для входа.
Для трейдеров и разработчиков:
Используйте код как основу для своих стратегий.
Тестируйте изменения на истории перед реальной торговлей.
Простыми словами:
Почему это удобно:
Открытый код = полный контроль. Вы можете:
Увидеть, как именно стратегия решает купить или продать.
Изменить правила закрытия сделок (например, поставить TP=2% вместо 1.5%).
Добавить новые условия (например, торговать только при высоком объёме).
Примеры кастомизации:
Новички: Меняйте только TP/SL в настройках (без кодинга).
Продвинутые: Добавьте RSI-фильтр, чтобы избегать перекупленности.
Разработчики: Встройте стратегию в свою торговую систему.
Как начать:
Скачайте код из TradingView.
Изучите логику в разделе strategy.entry/exit.
Меняйте параметры в блоке input.* (безопасно!).
Тестируйте изменения и оптимизируйте под свои цели.
Как работает стратегия:
Главная задача:
Автоматически покупает, когда цена начинает расти, и продаёт, когда падает. Но делает это «умно» — только когда рынок в основном тренде, а не во временном откате (коррекции).
Что видно на графике:
📈 Стрелки вверх ▼ (под свечой) — сигнал на покупку.
📉 Стрелки вниз ▲ (над свечой) — сигнал на продажу.
Серый фон — рынок в коррекции (не торгуем).
Как это работает:
Когда покупаем:
Если цена закрылась выше предыдущей и индикатор is_correction показывает «основной тренд» (не коррекция).
Пример: Была красная свеча → стала зелёная → появилась стрелка ▼ → покупаем.
Когда продаём:
Если цена закрылась ниже предыдущей и is_correction подтверждает тренд (опционально, можно отключить в настройках).
Когда закрываем сделку:
Автоматически при достижении:
+0.5% прибыли (можно изменить в настройках).
-0.5% убытка (можно изменить).
Или если появился противоположный сигнал (например, после покупки пришла стрелка продажи).
Настройки для чайников:
«Sell – On» (включено по умолчанию):
Если включено → стратегия будет продавать в шорт.
Если выключено → только покупки и закрытие позиций.
«Revers» (выключено по умолчанию):
Если включить → стратегия будет работать наоборот (стрелки ▼ = продажа, ▲ = покупка).
«%Profit» и «%Loss»:
Меняйте эти цифры (от 0 до 30), чтобы увеличить/уменьшить прибыль и риски.
Пример работы:
Сигнал на покупку:
Цена 3 дня растет → появляется зелёная стрелка ▼ → стратегия покупает.
Стоп-лосс ставится на 0.5% ниже цены входа.
Если цена продолжает расти → сделка закрывается при +0.5% прибыли.
Коррекция:
После роста цена падает на 1 день → фон становится серым → стратегия игнорирует это падение (не закрывает сделку).
Стоп-лосс:
Если цена упала на 0.5% от точки входа → сделка закрывается автоматически.
Важные особенности:
Фильтр коррекций (is_correction):
Это «защита от шума» — стратегия не реагирует на мелкие откаты, работая только в сильных трендах.
Гибкие настройки:
Можно запретить шорты, перевернуть сигналы или изменить уровни прибыли/убытка за 2 клика.
Прозрачность:
Весь код открыт → вы можете увидеть, как формируется каждый сигнал (меню «Исходник» в TradingView).
Советы для новичков:
Начните с теста:
Запустите стратегию на исторических данных (кнопка «Свеча» в окне TradingView).
Посмотрите, как она работала в прошлом.
Настройте под себя:
Увеличьте %Profit до 2-3%, если торгуете валюты.
Отключите «Sell – On», если не понимаете шорты.
Доверяйте стоп-лоссу:
Даже если кажется, что цена развернётся — стратегия закроет сделку при -0.5%, защитив ваш депозит.
Где найти настройки:
Кликните на название стратегии в верхнем левом углу графика → откроется меню с ползунками и переключателями.
Важно: Стратегия предоставляет «рыбу» – чтобы она стала «уловистой», адаптируйте её под свой стиль торговли!
EMA 5 Alert Candle ShortThe 5 EMA (Exponential Moving Average) Strategy is a simple yet effective trading strategy that helps traders identify short-term trends and potential entry and exit points. This strategy is widely used in intraday and swing trading, particularly in forex, stocks, and crypto markets.
Components of the 5 EMA Strategy
5 EMA: A fast-moving average that reacts quickly to price movements.
15-minute or 1-hour timeframe (commonly used, but adaptable to other timeframes).
Candlestick Patterns: To confirm entry signals.
How the 5 EMA Strategy Works
Buy (Long) Setup:
Price Above the 5 EMA: The price should be trading above the 5 EMA.
Pullback to the 5 EMA: A minor retracement or consolidation near the 5 EMA.
Bullish Candlestick Confirmation: A bullish candle (e.g., engulfing or pin bar) forms near the 5 EMA.
Entry: Enter a long trade at the close of the bullish candle.
Stop Loss: Place below the recent swing low or 5-10 pips below the 5 EMA.
Take Profit: Aim for a risk-reward ratio of at least 1:2 or trail the stop using a higher EMA (e.g., 10 or 20 EMA).
Sell (Short) Setup:
Price Below the 5 EMA: The price should be trading below the 5 EMA.
Pullback to the 5 EMA: A small retracement towards the 5 EMA.
Bearish Candlestick Confirmation: A bearish candle (e.g., engulfing or pin bar) near the 5 EMA.
Entry: Enter a short trade at the close of the bearish candle.
Stop Loss: Place above the recent swing high or 5-10 pips above the 5 EMA.
Take Profit: Aim for a 1:2 risk-reward ratio or use a trailing stop.
Additional Filters for Better Accuracy
Higher Timeframe Confirmation: Check the trend on a higher timeframe (e.g., 1-hour or 4-hour).
Volume Confirmation: Enter trades when volume is increasing.
Avoid Sideways Market: Use the strategy only when the market is trending.
Advantages of the 5 EMA Strategy
✔️ Simple and easy to use.
✔️ Works well in trending markets.
✔️ Helps traders capture short-term momentum.
Disadvantages
❌ Less effective in choppy or sideways markets.
❌ Requires discipline in following stop-loss rules.
Color Code Overlay StrategyColor Code Overlay Strategy
This strategy utilizes a custom color-coded overlay to provide accurate buy and sell signals based on dynamic color changes of the candles. The indicator works by calculating a color shift between bullish (green) and bearish (red) candles, with the color change logic driven by both price movement and volatility.
How the Color Change is Calculated:
The color change is determined by comparing the closing price relative to the opening price of each candle, as is typical with a traditional bullish or bearish candle. However, to make this strategy more adaptive to market conditions, the color change is further refined by incorporating the Average True Range (ATR).
Volatility Adjusted Color Shift: The strategy calculates a dynamic threshold based on the ATR value, which represents market volatility. If the price movement between the open and close of the candle exceeds a specific percentage of the ATR, the color of the candle shifts from red (bearish) to green (bullish) or vice versa.
Threshold Calculation: A fixed percentage (e.g., 1%) of the ATR range is used to define the minimum price movement required for a color change. This ensures that only significant price movements, adjusted for volatility, trigger the color shift. The larger the ATR (higher volatility), the greater the price movement required to cause a change in color.
Bullish to Bearish (Green to Red): When the candle closes lower than the open, and the price movement exceeds the dynamic threshold based on ATR, the candle color changes from green to red, signaling a potential bearish reversal.
Bearish to Bullish (Red to Green): When the candle closes higher than the open, and the price movement exceeds the ATR-based threshold, the candle color shifts from red to green, signaling a potential bullish reversal.
Key Features:
Dynamic Color Change: The strategy identifies key color changes from bullish to bearish (green to red) and from bearish to bullish (red to green) based on specific thresholds in candle size.
Customizable Timeframe: You can specify a custom trading window to restrict the strategy’s actions to specific hours of the day.
Stop Loss and Take Profit: The strategy incorporates risk management features, allowing you to set a stop loss and take profit based on the price in pips.
Flexible Trade Types: Choose between "Both" (long and short), "Long Only," or "Short Only" trading options to suit your preferred trading style.
Visual Alerts: Receive visual alerts with arrows when color changes occur, signaling potential trade opportunities. Green arrows indicate a bullish shift, while red arrows show a bearish shift.
This strategy is ideal for traders who prefer a color-coded overlay to easily visualize price action and make informed decisions based on bullish or bearish trends. Whether you’re looking for quick, short-term opportunities or analyzing market reversals, this strategy offers an intuitive approach to identifying trade signals.
Grim SlashOverview:
The Touch Previous Candle Strategy is a simple yet effective trading approach designed for the 1-hour chart. It focuses on price action by placing trades when the current candle interacts with key levels from the previous candle. The strategy is fully automated and includes risk management with take profit and stop loss levels.
Entry Conditions:
Buy Signal: A buy order is triggered when the low of the current candle touches or drops below the previous candle's closing price.
Sell Signal: A position is closed when the high of the current candle reaches or exceeds the previous candle's highest price.
Risk Management:
Take Profit: The trade is exited automatically when the price increases by 15% from the entry point.
Stop Loss: A stop loss is set at 5% below the entry price to minimize risk.
Best Use Cases:
Works well in volatile markets where price frequently tests previous levels.
Suitable for traders who prefer price-action-based strategies over indicators.
Can be optimized for different assets or timeframes based on market behavior.
