TASC 2025.05 Trading The Channel█ OVERVIEW
This script implements channel-based trading strategies based on the concepts explained by Perry J. Kaufman in the article "A Test Of Three Approaches: Trading The Channel" from the May 2025 edition of TASC's Traders' Tips . The script explores three distinct trading methods for equities and futures using information from a linear regression channel. Each rule set corresponds to different market behaviors, offering flexibility for trend-following, breakout, and mean-reversion trading styles.
█ CONCEPTS
Linear regression
Linear regression is a model that estimates the relationship between a dependent variable and one or more independent variables by fitting a straight line to the observed data. In the context of financial time series, traders often use linear regression to estimate trends in price movements over time.
The slope of the linear regression line indicates the strength and direction of the price trend. For example, a larger positive slope indicates a stronger upward trend, and a larger negative slope indicates the opposite. Traders can look for shifts in the direction of a linear regression slope to identify potential trend trading signals, and they can analyze the magnitude of the slope to support trading decisions.
One caveat to linear regression is that most financial time series data does not follow a straight line, meaning a regression line cannot perfectly describe the relationships between values. Prices typically fluctuate around a regression line to some degree. As such, analysts often project ranges above and below regression lines, creating channels to model the expected extent of the data's variability. This strategy constructs a channel based on the method used in Kaufman's article. It measures the maximum distances from points on the linear regression line to historical price values, then adds those distances and the current slope to the regression points.
Depending on the trading style, traders might look for prices to move outside an established channel for breakout signals, or they might look for price action to reach extremes within the channel for potential mean reversion opportunities.
█ STRATEGY CALCULATIONS
Primary trade rules
This strategy implements three distinct sets of rules for trend, breakout, and mean-reversion trades based on the methods Kaufman describes in his article:
Trade the trend (Rule 1) : Open new positions when the sign of the slope changes, indicating a potential trend reversal. Close short trades and enter a long trade when the slope changes from negative to positive, and do the opposite when the slope changes from positive to negative.
Trade channel breakouts (Rule 2) : Open new positions when prices cross outside the linear regression channel for the current sample. Close short trades and enter a long trade when the price moves above the channel, and do the opposite when the price moves below the channel.
Trade within the channel (Rule 3) : Open new positions based on price values within the channel's range. Close short trades and enter a long trade when the price is near the channel's low, within a specified percentage of the channel's range, and do the opposite when the price is near the channel's high. With this rule, users can also filter the trades based on the channel's slope. When the filter is active, long positions are allowed only when the slope is positive, and short positions are allowed only when it is negative.
Position sizing
Kaufman's strategy uses specific trade sizes for equities and futures markets:
For an equities symbol, the number of shares traded is $10,000 divided by the current price.
For a futures symbol, the number of contracts traded is based on a volatility-adjusted formula that divides $25,000 by the product of the 20-bar average true range and the instrument's point value.
By default, this script automatically uses these sizes for its trade simulation on equities and futures symbols and does not simulate trading on other symbols. However, users can control position sizes from the "Settings/Properties" tab and enable trade simulation on other symbol types by selecting the "Manual" option in the script's "Position sizing" input.
Stop-loss
This strategy includes the option to place an accompanying stop-loss order for each trade, which users can enable from the "SL %" input in the "Settings/Inputs" tab. When enabled, the strategy places a stop-loss order at a specified percentage distance from the closing price where the entry order occurs, allowing users to compare how the strategy performs with added loss protection.
█ USAGE
This strategy adapts its display logic for the three trading approaches based on the rule selected in the "Trade rule" input:
For all rules, the script plots the linear regression slope in a separate pane. The plot is color-coded to indicate whether the current slope is positive or negative.
When the selected rule is "Trade the trend", the script plots triangles in the separate pane to indicate when the slope's direction changes from positive to negative or vice versa. Additionally, it plots a color-coded SMA on the main chart pane, allowing visual comparison of the slope to directional changes in a moving average.
When the rule is "Trade channel breakouts" or "Trade within the channel", the script draws the current period's linear regression channel on the main chart pane, and it plots bands representing the history of the channel values from the specified start time onward.
When the rule is "Trade within the channel", the script plots overbought and oversold zones between the bands based on a user-specified percentage of the channel range to indicate the value ranges where new trades are allowed.
Users can customize the strategy's calculations with the following additional inputs in the "Settings/Inputs" tab:
Start date : Sets the date and time when the strategy begins simulating trades. The script marks the specified point on the chart with a gray vertical line. The plots for rules 2 and 3 display the bands and trading zones from this point onward.
Period : Specifies the number of bars in the linear regression channel calculation. The default is 40.
Linreg source : Specifies the source series from which to calculate the linear regression values. The default is "close".
Range source : Specifies whether the script uses the distances from the linear regression line to closing prices or high and low prices to determine the channel's upper and lower ranges for rules 2 and 3. The default is "close".
Zone % : The percentage of the channel's overall range to use for trading zones with rule 3. The default is 20, meaning the width of the upper and lower zones is 20% of the range.
SL% : If the checkbox is selected, the strategy adds a stop-loss to each trade at the specified percentage distance away from the closing price where the entry order occurs. The checkbox is deselected by default, and the default percentage value is 5.
Position sizing : Determines whether the strategy uses Kaufman's predefined trade sizes ("Auto") or allows user-defined sizes from the "Settings/Properties" tab ("Manual"). The default is "Auto".
Long trades only : If selected, the strategy does not allow short positions. It is deselected by default.
Trend filter : If selected, the strategy filters positions for rule 3 based on the linear regression slope, allowing long positions only when the slope is positive and short positions only when the slope is negative. It is deselected by default.
NOTE: Because of this strategy's trading rules, the simulated results for a specific symbol or channel configuration might have significantly fewer than 100 trades. For meaningful results, we recommend adjusting the start date and other parameters to achieve a reasonable number of closed trades for analysis.
Additionally, this strategy does not specify commission and slippage amounts by default, because these values can vary across market types. Therefore, we recommend setting realistic values for these properties in the "Cost simulation" section of the "Settings/Properties" tab.
Wskaźniki i strategie
W%R Zone Scalper[BullByte] v1.0W%R Zone Scalper Strategy - The Definitive Deep Dive
1. Introduction: The Philosophy Behind the Strategy
This script, W%R Zone Scalper , is not just another Williams %R-based trading system—it is a refined, multi-filtered scalping engine designed to maximize edge in trending markets while minimizing false signals in choppy conditions . Unlike most basic %R strategies that blindly trade crossovers, this system introduces a sophisticated confluence of trend, volatility, and momentum filters , making it a high-probability scalper for intraday traders .
What Makes This Script Different?
✅ Originality: Most %R strategies rely solely on overbought/oversold levels, leading to whipsaws in ranging markets. This script intelligently combines:
- Trend confirmation (MA, Supertrend)
- Volatility filters (BB Width, Choppiness Index)
- Volume validation (to ensure real participation)
- ADX trend strength (to avoid weak, fake trends)
✅ Smart Trade Execution:
- Not just %R crossovers —entries are only taken when multiple filters align, reducing noise.
- Optional ATR-based SL/TP for disciplined risk management.
- Dashboard integration for real-time trade monitoring.
✅ Adaptability:
- Works on crypto, forex, and stocks (optimized for high-liquidity assets like BTC).
- Scalable from 1-minute scalping to 1-hour swing trades (adjust filters accordingly).
2. Core Components: A Surgical Breakdown
A. Williams %R - The Trigger Mechanism
- Default Settings:
- Length = 14 (optimal balance between sensitivity and reliability).
- Long Entry : Cross above -80 (oversold bounce with momentum).
- Short Entry : Cross below -20 (overbought rejection).
Why This Matters:
- Unlike RSI or Stochastic, %R is more aggressive in detecting reversals, making it ideal for scalping fast moves.
- However, raw %R signals are noisy—hence the need for additional filters.
B. The Moving Average (MA) - Trend Filter
- Purpose: Ensures trades are only taken in the direction of the broader trend.
- Types Available:
- SMA (Simple MA) – Smooth but laggy.
- EMA (Exponential MA) – Faster, default choice.
- WMA (Weighted MA) – More responsive to recent prices.
- HMA (Hull MA) – Minimal lag, excellent for scalping.
Entry Logic:
- Long : Price must be above MA (confirms uptrend).
- Short : Price must be below MA (confirms downtrend).
Why This Matters:
- Prevents counter-trend trades , which are high-risk in scalping.
- Works as a dynamic support/resistance .
C. Advanced Filters - The Edge Enhancers
1. Choppiness Index (CI) - Avoiding Sideways Markets
- Default:
- Length = 12
- Threshold = 38.2 (below = trending, above = choppy).
Why This Matters:
- Eliminates false signals in ranging markets (where %R crossovers fail most).
- Inspired by market cycle theory—only trades when volatility is directional.
2. ADX (Average Directional Index) - Trend Strength
- Default:
- Length = 14
- Threshold = 25 (only trade if ADX > 25 = strong trend).
Why This Matters:
- Many traders ignore ADX and get fake breakouts—this ensures trades happen only in high-momentum conditions.
3. Volume Filter - Confirming Real Moves
- Logic: Volume must be above its 50-period MA.
- Why This Matters:
- Low-volume breakouts often fail—this ensures institutional participation.
4. Bollinger Band Width (BBW) - Volatility Check
- Logic: BBW must be above its moving average (expanding volatility = good for scalping).
Why This Matters:
- Avoids low-volatility traps where price moves are insignificant.
5. Supertrend - Dynamic Trend Confirmation
- Logic:
- Longs : Price must be above Supertrend line.
- Shorts : Price must be below Supertrend line.
Why This Matters:
- Acts as a secondary trend filter , reducing whipsaws.
---
3. Risk Management - Protecting Capital
A. Position Sizing (Flexible & Adaptive)
- Default: 30% of equity per trade(aggressive but adjustable).
- Initial Capital: $1,000(example—modify based on your account size).
B. Stop Loss & Take Profit (ATR-Based)
- SL = 1.5x ATR (protects against sudden reversals).
- TP = 2x ATR (locks in profits before pullbacks).
Why ATR?
- Dynamic adjustment —wider in volatile markets, tighter in calm ones.
C. Manual Adjustments Required
- Commission: Default 0.1% (adjust per your broker).
- Leverage: Not hardcoded —apply based on your risk tolerance.
4. Optimal Time Frame & Asset Selection
- Best for: 5M - 15M charts(scalping).
- Also works on: 1H-4H(swing trades with adjusted filters).
- Best Assets:
- High-liquidity cryptos (BTC, ETH, SOL)
- Forex majors (EUR/USD, GBP/USD)
- High-beta stocks (TSLA, NVDA)
5. The Dashboard - Real-Time Trade Intelligence
- PnL Tracking (profit/loss in $ and %).
- Position Status (Long/Short/Flat).
- Filter Status (which ones are active).
- Key Indicators (%R, MA, Volume).
Why This Matters:
- No guesswork—all critical info in one place.
6. Strong Disclaimer
⚠️ This is not financial advice. Trading carries risk of loss.
- Backtest thoroughly before live trading.
- Start with small capital to validate performance.
- Modify SL/TP, leverage, and position sizing based on your risk profile.
- The developer is not liable for any losses incurred.
7. Why This Strategy Stands Out
Most %R strategies fail in real markets because they ignore:
❌ Trend context (trading reversals blindly).
❌ Volatility cycles (getting chopped up in sideways action).
❌ Volume confirmation (falling for fake breakouts).
This script solves those problems by:
✅ Only trading when multiple high-probability factors align.
✅ Using adaptive risk management (ATR-based SL/TP).
✅ Providing a real-time dashboard for decision-making.
8.Important Note on Backtesting & Customization
The performance results displayed with this script are based on:
- Asset BTC/USD
- Timeframe : 5-minute chart
- Key Filters Enabled :
- Moving Average (Trend Confirmation)
- Choppiness Index (Sideways Market Filter)
- Volume (Participation Validation)
Your Trading Approach May Vary
This configuration represents just one possible way to deploy the strategy. You can:
- Test alternative settings (adjust lengths, thresholds, or filters)
- Apply to different assets (cryptos, forex pairs, stocks)
- Experiment with timeframes (1m for ultra-scalping, 15m/1H for swing trades)
Critical Reminder
Always conduct your own forward testing before live trading. Market conditions change, and past performance never guarantees future results.
All the best!
Weighted Ichimoku StrategyLSE:HSBA
The Ichimoku Kinko Hyo indicator is a comprehensive tool that combines multiple signals to identify market trends and potential buying/selling opportunities. My weighted variant of this strategy attempts to assign specific weights to each signal, allowing for a more nuanced and customizable approach to trend identification. The intent is to try and make a more informed trading decision based on the cumulative strength of various signals.
I've tried not to make it a mishmash of this and that + MACD + RSI and on and on; most people have their preferred indicator that focuses on just that that they can use in conjunction.
The signals used can be grouped into two groups the 'Core Ichimoku Signals' & the 'Additional Signals' (at the end you will find the signals and their assigned weights followed by the thresholds where they align).
The Core Ichimoku Signals are the primary signals used in Ichimoku analysis, including Kumo Breakout, Chikou Cross, Kijun Cross, Tenkan Cross, and Kumo Twist.
While the Additional Signals provide further insights and confirmations, such as Kijun Confirmation, Tenkan-Kijun Above Cloud, Chikou Above Cloud, Price-Kijun Cross, Chikou Span Signal, and Price Positioning.
Entries are triggered when the cumulative weight of bullish signals exceeds a specified buy threshold, indicating a strong uptrend or potential trend reversal.
Exits are initiated when the cumulative weight of bearish signals surpasses a specified sell threshold, or when additional conditions such as consolidation patterns or ATR-based targets are met.
There are various exit types that you can choose between, which can be used separately or in conjunction with one another. As an example you might want to exit on a different condition during consolidation periods than during other periods or just use ATR with some other backstop.
They are listed in evaluation order i.e. ATR trumps all, Consolidation exit trumps the regular Kumo sell and so on:
**ATR Sell**: Exits trades based on ATR-based profit targets and stop-losses.
**Consolidation Exit**: Exits trades during consolidation periods to reduce drawdown.
**Sell Below Kumo**: Exits trades when the price is below the Kumo, indicating a potential downtrend.
**Sell Threshold**: Exits trades when the cumulative weight of bearish signals surpasses a specified sell threshold.
There are various 'filters' which are really behavior modifiers:
**Kumo Breakout Filter**: Requires price to close above the Kumo for buy signals (essentially a entry delay).
**Whipsaw Filter**: Ensures trend strength over specified days to reduce false signals.
**Buy Cooldown**: Prevents new entries until half the Kijun period passes after an exit (prevents flapping).
**Chikou Filter**: Delays exits unless the previous close is below the Chikou Span.
**Consolidation Trend Filter**: Prevents consolidation exits if the trend is bullish (rare, but happens).
Then there are some debugging options. Ichimoku periods have some presets (personally I like 8/22/44/22) but are freely configurable, preset to the traditional values for purists.
The list of signals and most thresholds follow, play around with them. Thats all.
Cheers,
**Core Ichimoku Signals**
**Kumo Breakout**
- 30 (Bullish) / -30 (Bearish)
- Indicates a strong trend when the price breaks above (bullish) or below (bearish) the Kumo (cloud). This signal suggests a significant shift in market sentiment.
**Chikou Cross**
- 20 (Bullish) / -20 (Bearish)
- Shows the relationship between the Chikou Span (lagging span) and the current price. A bullish signal occurs when the Chikou Span is above the price, indicating a potential uptrend. Conversely, a bearish signal occurs when the Chikou Span is below the price, suggesting a downtrend.
**Kijun Cross**
- 15 (Bullish) / -15 (Bearish)
- Signals trend changes when the Tenkan-sen (conversion line) crosses above (bullish) or below (bearish) the Kijun-sen (base line). This crossover is often used to identify potential trend reversals.
**Tenkan Cross**
- 10 (Bullish) / -10 (Bearish)
- Indicates short-term trend changes when the price crosses above (bullish) or below (bearish) the Tenkan-sen. This signal helps identify minor trend shifts within the broader trend.
**Kumo Twist**
- 5 (Bullish) / -5 (Bearish)
- Shows changes in the Kumo's direction, indicating potential trend shifts. A bullish Kumo Twist occurs when Senkou Span A crosses above Senkou Span B, and a bearish twist occurs when Senkou Span A crosses below Senkou Span B.
**Additional Signals**
**Kijun Confirmation**
- 8 (Bullish) / -8 (Bearish)
- Confirms the trend based on the price's position relative to the Kijun-sen. A bullish signal occurs when the price is above the Kijun-sen, and a bearish signal occurs when the price is below it.
**Tenkan-Kijun Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Indicates a strong bullish trend when both the Tenkan-sen and Kijun-sen are above the Kumo. Conversely, a bearish signal occurs when both lines are below the Kumo.
**Chikou Above Cloud**
- 5 (Bullish) / -5 (Bearish)
- Shows the Chikou Span's position relative to the Kumo, indicating trend strength. A bullish signal occurs when the Chikou Span is above the Kumo, and a bearish signal occurs when it is below.
**Price-Kijun Cross**
- 2 (Bullish) / -2 (Bearish)
- Signals short-term trend changes when the price crosses above (bullish) or below (bearish) the Kijun-sen. This signal is similar to the Kijun Cross but focuses on the price's direct interaction with the Kijun-sen.
**Chikou Span Signal**
- 10 (Bullish) / -10 (Bearish)
- Indicates the trend based on the Chikou Span's position relative to past price highs and lows. A bullish signal occurs when the Chikou Span is above the highest high of the past period, and a bearish signal occurs when it is below the lowest low.
**Price Positioning**
- 10 (Bullish) / -10 (Bearish)
- Shows indecision when the price is between the Tenkan-sen and Kijun-sen, indicating a potential consolidation phase. A bullish signal occurs when the price is above both lines, and a bearish signal occurs when the price is below both lines.
**Confidence Level**: Highly Sensitive
- **Buy Threshold**: 50
- **Sell Threshold**: -50
- **Notes / Significance**: ~2–3 signals, very early trend detection. High sensitivity, may capture noise and false signals.
**Confidence Level**: Entry-Level
- **Buy Threshold**: 58
- **Sell Threshold**: -58
- **Notes / Significance**: ~3–4 signals, often Chikou Cross or Kumo Breakout. Very sensitive, risks noise (e.g., false buys in choppy markets).
**Confidence Level**: Entry-Level
- **Buy Threshold**: 60
- **Sell Threshold**: -60
- **Notes / Significance**: ~3–4 signals, Kumo Breakout or Chikou Cross anchors. Entry point for early trends.
**Confidence Level**: Moderate
- **Buy Threshold**: 65
- **Sell Threshold**: -65
- **Notes / Significance**: ~4–5 signals, balances sensitivity and reliability. Suitable for moderate risk tolerance.
**Confidence Level**: Conservative
- **Buy Threshold**: 70
- **Sell Threshold**: -70
- **Notes / Significance**: ~4–5 signals, emphasizes stronger confirmations. Reduces false signals but may miss some opportunities.
**Confidence Level**: Very Conservative
- **Buy Threshold**: 75
- **Sell Threshold**: -75
- **Notes / Significance**: ~5–6 signals, prioritizes high confidence. Minimizes risk but may enter trades late.
**Confidence Level**: High Confidence
- **Buy Threshold**: 80
- **Sell Threshold**: -80
- **Notes / Significance**: ~6–7 signals, very strong confirmations needed. Suitable for cautious traders.
**Confidence Level**: Very High Confidence
- **Buy Threshold**: 85
- **Sell Threshold**: -85
- **Notes / Significance**: ~7–8 signals, extremely high confidence required. Minimizes false signals significantly.
**Confidence Level**: Maximum Confidence
- **Buy Threshold**: 90
- **Sell Threshold**: -90
- **Notes / Significance**: ~8–9 signals, maximum confidence level. Ensures trades are highly reliable but may result in fewer trades.
**Confidence Level**: Ultra Conservative
- **Buy Threshold**: 100
- **Sell Threshold**: -100
- **Notes / Significance**: ~9–10 signals, ultra-high confidence. Trades are extremely reliable but opportunities are rare.
**Confidence Level**: Extreme Confidence
- **Buy Threshold**: 110
- **Sell Threshold**: -110
- **Notes / Significance**: All signals align, extreme confidence. Trades are almost certain but very few opportunities.
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
Phoenix Pro Strategy📘 Phoenix Pro Indicator & Strategy – Technical Documentation
🔧 Overview
The Phoenix Pro Indicator is a comprehensive multi-tool indicator designed for trend detection, momentum analysis, volatility visualization, and automated strategy execution on TradingView. It integrates:
EMA, SMA (Trend Filters)
RSI (Momentum)
Bollinger Bands (Volatility)
Pivot Support/Resistance (Price Structure)
ZigZag Highs/Lows (Market Structure)
Auto Buy/Sell Strategy Logic
📊 Technical Components
🔹 1. Trend Filters (EMA/SMA)
Fast EMA (default 9): Short-term trend direction
Slow EMA (default 21): Long-term trend filter
SMA Short (default 20): Confirms price momentum
SMA Long (default 50): General market trend direction
pine
Kopyala
Düzenle
emaFast = ta.ema(close, 9)
emaSlow = ta.ema(close, 21)
🔹 2. RSI
Detects overbought/oversold conditions.
Used to time entries with trend confirmation.
pine
Kopyala
Düzenle
rsi = ta.rsi(close, 14)
🔹 3. Bollinger Bands
Measures volatility and helps detect breakouts.
pine
Kopyala
Düzenle
basis = ta.sma(close, 20)
upperBB = basis + 2 * ta.stdev(close, 20)
lowerBB = basis - 2 * ta.stdev(close, 20)
🔹 4. Pivot Support/Resistance
Highlights recent local highs and lows as potential reversal zones.
pine
Kopyala
Düzenle
pivotHigh = ta.pivothigh(high, 5, 5)
pivotLow = ta.pivotlow(low, 5, 5)
🔹 5. ZigZag
Simplifies price structure visualization to identify swing highs/lows.
pine
Kopyala
Düzenle
zigzagTop := (high >= high * (1 + dev / 100)) ? high : zigzagTop
📈 Strategy Logic
✅ Long Entry:
text
Kopyala
Düzenle
- EMA Fast > EMA Slow
- Close > SMA Short
- RSI < 60
- Close > Bollinger Basis
🔻 Short Entry:
text
Kopyala
Düzenle
- EMA Fast < EMA Slow
- Close < SMA Short
- RSI > 40
- Close < Bollinger Basis
📉 Exit Logic:
Close long if short condition triggers.
Close short if long condition triggers.
✅ Pine Script Strategy Code Snippet:
pine
Kopyala
Düzenle
strategy.entry("Long", strategy.long, when=longCond)
strategy.close("Long", when=shortCond)
strategy.entry("Short", strategy.short, when=shortCond)
strategy.close("Short", when=longCond)
🖥️ Usage in TradingView
Open TradingView
Click on Pine Editor (bottom tab)
Paste the full script
Click Add to Chart
Select the Strategy Tester tab to view performance
Adjust input parameters via settings ⚙️
⚙️ Recommended Settings (Adjust as needed)
Input Default Notes
EMA Fast 9 Short-term sensitivity
EMA Slow 21 Trend confirmation
SMA Short 20 Entry condition check
RSI Period 14 Momentum filter
RSI OB/OS 70/30 Entry condition tuning
Bollinger Length 20 For mean reversion / trend volatility
ZigZag Deviation (%) 5.0 Increase for higher-timeframe clarity
📌 Notes & Tips
Use on higher timeframes (1H, 4H, 1D) for better signals.
Combine with macro/fundamental filters for advanced setups.
Adjust parameters based on market type (ranging vs trending).
Use strategy tester to optimize performance.
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
RSI + SuperTrend Filter Strategy (45m BTCUSDT)🧠 Strategy Breakdown: RSI + SuperTrend Filter (45m BTCUSDT)
This strategy is built on a simple yet powerful principle: don’t fight the trend — and never ignore momentum exhaustion.
At its core, this setup looks for RSI-based reversal entries, but only when price action aligns with the underlying trend structure, defined by a modified SuperTrend. This combo filters out a large chunk of noise you typically get with RSI alone on lower timeframes.
📊 How It Works
Longs trigger when RSI crosses up from oversold and SuperTrend confirms a bullish bias.
Shorts trigger when RSI crosses down from overbought and SuperTrend confirms a bearish structure.
Each entry is paired with a tight SL (1%) and dynamic TP (1.5%), offering favorable risk:reward setups.
The script includes clean chart visuals — background zones, SL/TP lines, and real-time trend bands — built for clarity and decision speed.
⚙️ Why It Works
Too many RSI strategies reverse blindly — this doesn’t. By combining RSI oversold/overbought conditions with a directional SuperTrend filter, you get higher-quality entries, especially during high-volatility phases.
This is not designed for sideways markets — it’s meant to catch clean swings in structured trends. The 45m TF adds breathing room for better signal quality while still allowing for decent trade frequency.
📈 Backtest Snapshot (3m logic on 45m BTCUSDT)
💰 +213,885 USDT total P&L
🧠 239 trades, with solid coverage across sessions
📉 15% max drawdown
⚖️ Profit factor: 1.12
🔁 Dynamic execution-ready — ideal for automation or manual confirmations
🔧 Built For Traders Who:
Want non-repainting structure they can trust
Prefer mechanical entries with visual context
Are experimenting with automation-ready setups
Need something they can tweak and expand on
🔥 If you're serious about combining clean signals with trend confirmation — this is a solid foundation. Drop a comment if you want the multi-timeframe version or ideas on adding volume-based confirmations.
Quantum Phoenix Strategy📘 Quantum Phoenix Strategy – Pine Script v5
Version: 2.0
Platform: TradingView
Author: Başkan
🔧 Overview
Quantum Phoenix Strategy is a trend-following, multi-timeframe (MTF) validated algorithm that uses a combination of EMA, RSI, MACD, ATR, and Supertrend indicators to detect high-probability long and short trade opportunities. It includes risk-based position sizing, dynamic TP/SL levels, dashboard display, and alert conditions for automation.
⚙️ Core Features
Feature Description
📈 Trend Detection Uses EMA 50/200 crossovers, MACD histogram, RSI values, and Supertrend direction
🕒 MTF Trend Filter 1-hour EMA trend confirmation
💰 Risk Management ATR-based position sizing and custom risk allocation
🎯 TP/SL Targets Take Profit and Stop Loss set as percentage of price
🧠 Strategy Logic Entry and exit logic for both long and short positions
🛎️ Alerts Long/Short signal alert conditions
🖼️ Visual Panel On-chart dashboard showing strategy parameters
📉 Indicator Plots EMA lines and entry signal markers on the chart
🔍 Inputs & Parameters
Parameter Type Description
riskPercent float (0.1–10) Percentage of capital to risk per trade
accountSize float Virtual account size for position sizing
takeProfitPercent float Take Profit level in %
stopLossPercent float Stop Loss level in %
📊 Indicator Logic
✅ Long Entry:
Price > EMA200
EMA50 > EMA200
RSI between 40 and 70
MACD Histogram > 0
Supertrend direction is bullish
1-hour MTF EMA trend is upward
❌ Long Exit:
RSI > 70
MACD Histogram turns negative
⛔ Short Entry:
Price < EMA200
EMA50 < EMA200
RSI between 30 and 60
MACD Histogram < 0
Supertrend direction is bearish
1-hour MTF EMA trend is downward
🚪 Short Exit:
RSI < 30
MACD Histogram turns positive
🧮 Risk Calculation
The position size is calculated using the ATR (Average True Range) as a measure of volatility:
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riskAmount = accountSize * (riskPercent / 100)
positionSize = riskAmount / ATR
This means that for higher volatility, the position size is reduced to maintain the same risk exposure.
📺 On-Chart Dashboard
Every 10 bars, a visual panel is updated on the chart showing:
Strategy title
Risk and account size
TP/SL percentages and ATR value
MTF trend direction (UP / DOWN / FLAT)
🚨 Alerts
These alerts can be used to trigger notifications or webhook integrations:
"Long Giriş" – Triggers when long conditions are met
"Short Giriş" – Triggers when short conditions are met
🎨 Visual Elements
EMA50 and EMA200 plotted as orange and teal lines
Long signals shown with green upward labels
Short signals shown with red downward labels
🧠 Best Practices
Combine this strategy with manual confirmation or fundamental analysis
Optimize takeProfitPercent and stopLossPercent values based on asset volatility
Use alerts with a trading bot for automation (e.g., via webhook & Telegram integration)
Monitor the dashboard for MTF trend consistency
Quantum Phoenix 2.0 Quantum Phoenix 2.0 – Strategy Documentation
Version: Pine Script v5
Platform: TradingView
Script Type: Strategy (Backtest & Alerts)
Overlay: Yes
Purpose: To identify high-probability breakout entries with trend, volume, and multi-timeframe confirmation.
🔧 Inputs
Parameter Description Default
Risk % Percentage of account risked per trade 1.0%
Account Size ($) Virtual capital for position size calculation 10,000
Take Profit % Target profit per trade 3.0%
Stop Loss % Maximum allowed loss per trade 1.5%
Min. ADX Strength Minimum trend strength to validate entry 20
Volume Filter If enabled, filters out low-volume conditions Enabled
📈 Indicators Used
EMA 50 & EMA 200: Trend confirmation
RSI (14): Momentum condition
MACD Histogram: Entry timing filter
SuperTrend (3,7): Trend direction
ADX & DMI (14): Trend strength and direction
Volume + 20 SMA: Volume filter
ATR (14): Used for dynamic position sizing
MTF EMAs (1H): Higher timeframe trend confirmation
📊 Entry Conditions
🟢 LONG:
Price > EMA200
EMA50 > EMA200
RSI between 40–70
MACD Histogram > 0
1H EMA50 > 1H EMA200 (MTF Trend Up)
ADX > threshold and SuperTrend is Bullish
Volume filter (if enabled) must be met
🔴 SHORT:
Price < EMA200
EMA50 < EMA200
RSI between 30–60
MACD Histogram < 0
1H EMA50 < 1H EMA200 (MTF Trend Down)
ADX > threshold and SuperTrend is Bearish
Volume filter (if enabled) must be met
💼 Risk Management
Uses ATR-based position sizing
Position Size = (AccountSize * Risk%) / ATR
Take Profit and Stop Loss levels are calculated based on % of price
📉 Strategy Orders
pinescript
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strategy.entry("Long", strategy.long, when=longCond)
strategy.exit("TP/SL Long", from_entry="Long", limit=TP Level, stop=SL Level)
strategy.close("Long", when=MACD Histogram < 0 or RSI > 70)
strategy.entry("Short", strategy.short, when=shortCond)
strategy.exit("TP/SL Short", from_entry="Short", limit=TP Level, stop=SL Level)
strategy.close("Short", when=MACD Histogram > 0 or RSI < 30)
📊 Visual Components
EMA Lines: EMA50 (orange), EMA200 (teal)
Labels on Chart: “AL” for Long, “SAT” for Short
Dashboard Table (Top-Right):
Strategy name
Account balance
TP & SL rates
Current ADX & ATR values
Multi-Timeframe Trend Status (UP / DOWN / FLAT)
🚨 Alerts
LONG Giriş: Triggers when all Long conditions are met
SHORT Giriş: Triggers when all Short conditions are met
Ideal for automated alert-based trading bots or Telegram signal bots
📌 Notes
Script is designed for educational and strategic testing purposes.
Real trading decisions must include manual confirmation and risk assessment.
Strategy results may vary based on asset type and market conditions.
Fibonacci Key Level Delta Strategy// Fibonacci Key Level Delta Strategy
// Pine Script v5
// Created with Claude (Apr 2025)
//@version=5
strategy("Fibonacci Key Level Delta Strategy", overlay=true, default_qty_value=1, initial_capital=10000)
// Input parameters
lookback = input.int(20, "Lookback Period for Swing High/Low", minval=5)
deltaThreshold = input.int(-1000, "Negative Delta Threshold", maxval=0)
profitTarget = input.float(2.0, "Profit Target %", minval=0.1, step=0.1)
stopLoss = input.float(1.0, "Stop Loss %", minval=0.1, step=0.1)
fibZoneThreshold = input.float(0.1, "Fibonacci Zone Threshold %", minval=0.01, step=0.01)
// Find significant swing high and low for Fibonacci calculation
swingHigh = ta.highest(high, lookback)
swingLow = ta.lowest(low, lookback)
swingRange = swingHigh - swingLow
// Calculate Fibonacci retracement levels
fib_0 = swingLow // 0%
fib_236 = swingLow + swingRange * 0.236 // 23.6%
fib_382 = swingLow + swingRange * 0.382 // 38.2%
fib_500 = swingLow + swingRange * 0.500 // 50%
fib_618 = swingLow + swingRange * 0.618 // 61.8%
fib_786 = swingLow + swingRange * 0.786 // 78.6%
fib_1 = swingHigh // 100%
// Check if current price is near any Fibonacci level
isNearFibLevel(currentPrice, fibLevel, threshold) =>
math.abs(currentPrice - fibLevel) <= (fibLevel * threshold / 100)
nearFib0 = isNearFibLevel(close, fib_0, fibZoneThreshold)
nearFib236 = isNearFibLevel(close, fib_236, fibZoneThreshold)
nearFib382 = isNearFibLevel(close, fib_382, fibZoneThreshold)
nearFib500 = isNearFibLevel(close, fib_500, fibZoneThreshold)
nearFib618 = isNearFibLevel(close, fib_618, fibZoneThreshold)
nearFib786 = isNearFibLevel(close, fib_786, fibZoneThreshold)
nearFib1 = isNearFibLevel(close, fib_1, fibZoneThreshold)
// Determine if price is at any key Fibonacci level
atKeyLevel = nearFib0 or nearFib236 or nearFib382 or nearFib500 or nearFib618 or nearFib786 or nearFib1
// Get the specific Fibonacci level we're at (for reference)
currentFibLevel = nearFib0 ? fib_0 :
nearFib236 ? fib_236 :
nearFib382 ? fib_382 :
nearFib500 ? fib_500 :
nearFib618 ? fib_618 :
nearFib786 ? fib_786 :
nearFib1 ? fib_1 : na
// Calculate delta (simplified approximation using volume and price action)
volumeUp = volume * (close > open ? 1 : 0.5)
volumeDown = volume * (close < open ? 1 : 0.5)
delta = volumeUp - volumeDown
// Calculate cumulative delta with a reset
var float cumulativeDelta = 0
if atKeyLevel and not atKeyLevel
cumulativeDelta := 0
cumulativeDelta := cumulativeDelta + delta
// Track if key level was broken
var bool keyLevelBroken = false
var float brokenLevel = 0.0
var float brokenCandleLow = 0.0
var float brokenCandleHigh = 0.0
var int breakDirection = 0 // 1 for upward break, -1 for downward break
// Detect key level breaks
if atKeyLevel
if high > currentFibLevel and not keyLevelBroken
keyLevelBroken := true
brokenLevel := currentFibLevel
brokenCandleLow := low
brokenCandleHigh := high
breakDirection := 1
else if low < currentFibLevel and not keyLevelBroken
keyLevelBroken := true
brokenLevel := currentFibLevel
brokenCandleLow := low
brokenCandleHigh := high
breakDirection := -1
else if not atKeyLevel
keyLevelBroken := false
breakDirection := 0
// Entry logic for condition 1
longCondition1 = atKeyLevel and cumulativeDelta < deltaThreshold and close > open
// Entry logic for condition 2
longCondition2 = keyLevelBroken and breakDirection == 1 and delta > 0 and low < brokenCandleLow
shortCondition2 = keyLevelBroken and breakDirection == -1 and delta < 0 and high > brokenCandleHigh
// Strategy execution
if longCondition1
strategy.entry("Long1", strategy.long)
strategy.exit("Exit Long1", "Long1", profit=close * profitTarget / 100, loss=close * stopLoss / 100)
if longCondition2
strategy.entry("Long2", strategy.long)
strategy.exit("Exit Long2", "Long2", profit=close * profitTarget / 100, loss=close * stopLoss / 100)
if shortCondition2
strategy.entry("Short2", strategy.short)
strategy.exit("Exit Short2", "Short2", profit=close * profitTarget / 100, loss=close * stopLoss / 100)
// Plotting for visualization
plotshape(longCondition1, title="Long Entry 1", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small)
plotshape(longCondition2, title="Long Entry 2", location=location.belowbar, color=color.blue, style=shape.triangleup, size=size.small)
plotshape(shortCondition2, title="Short Entry 2", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
// Plot Fibonacci levels
plot(fib_0, title="Fib 0%", color=color.rgb(33, 150, 243, 80), linewidth=1)
plot(fib_236, title="Fib 23.6%", color=color.rgb(33, 150, 243, 80), linewidth=1)
plot(fib_382, title="Fib 38.2%", color=color.rgb(33, 150, 243, 80), linewidth=1)
plot(fib_500, title="Fib 50%", color=color.rgb(33, 150, 243, 80), linewidth=1)
plot(fib_618, title="Fib 61.8%", color=color.rgb(33, 150, 243, 80), linewidth=1)
plot(fib_786, title="Fib 78.6%", color=color.rgb(33, 150, 243, 80), linewidth=1)
plot(fib_1, title="Fib 100%", color=color.rgb(33, 150, 243, 80), linewidth=1)
// Highlight active Fibonacci level
plot(atKeyLevel ? currentFibLevel : na, title="Active Fib Level", color=color.yellow, linewidth=3, style=plot.style_circles)
// Indicator values for debugging
plotchar(atKeyLevel, title="At Key Level", char="K", location=location.top)
plotchar(cumulativeDelta < deltaThreshold, title="Delta Negative", char="D", location=location.top)
plotchar(keyLevelBroken, title="Level Broken", char="B", location=location.top)
Frans' Bot - StratFrans' Bot Strategy is a trend-following trading system that uses a Hull Moving Average (HMA) and Exponential Moving Average (EMA) to identify entry points for long and short positions. Designed to work in conjunction with Frans' Bot Indicator, it incorporates optional filters such as RSI, Stochastic, and Pivot Points to enhance signal accuracy. The strategy supports customizable profit targets, stop-loss levels, and an optional trailing stop. Traders can enable reversal trades based on proximity to the EMA and choose to close positions when the HMA changes color.
Phoenix Master Strategy (PMI)Phoenix Master Strategy (PMI) - Documentation
🧠 Overview
Phoenix Master Strategy (PMI) is a comprehensive Pine Script strategy combining trend detection, buy/sell signals, volatility, sentiment estimation, liquidity zones, and position sizing—all in one powerful package. It supports both visual chart analysis and strategy backtesting.
⚙️ Inputs
Parameter Description
timeframeTrend Timeframe used to determine trend (e.g., "D" for Daily).
showBackground Enables background coloring based on trend direction.
riskPercent Risk percentage per trade.
accountSize Total account size in USD. Used to calculate position size.
📈 Trend Detection - EMA
Uses two EMAs: emaFast (default: 9) and emaSlow (default: 21).
Trend Direction:
Uptrend: Fast EMA > Slow EMA
Downtrend: Fast EMA < Slow EMA
Optional background coloring to visually indicate trend.
💹 Momentum Indicators
RSI (Relative Strength Index)
Custom period (rsiLength) and overbought/oversold thresholds.
Used for momentum filtering.
MACD
Standard MACD (12, 26, 9) applied to selected source.
MACD histogram value used to assess momentum direction.
Stoch RSI
Calculates %K and %D values to detect short-term overbought/oversold areas.
Helps fine-tune signal entries.
☁️ Ichimoku Cloud
Calculates full Ichimoku components: Tenkan, Kijun, Senkou A/B, and Chikou Span.
Trend Inference:
CloudUp: Senkou A > Senkou B → Bullish Cloud
CloudDown: Senkou A < Senkou B → Bearish Cloud
Cloud visuals are included but commented out by default.
📊 Volatility Indicator
Uses ATR (Average True Range) to measure volatility.
Position size is adjusted based on ATR value.
Detects volume explosions if current volume is 2x the 20-period SMA.
📌 Support / Resistance Zones (Pivots)
Automatically plots recent pivot highs and pivot lows for dynamic support/resistance visualization.
🧭 Sentiment & Liquidity Indicators
Sentiment (News Placeholder)
Uses 50-period SMA as a placeholder sentiment indicator.
Above SMA → Bullish Sentiment
Below SMA → Bearish Sentiment
Can be replaced with live news API in future versions.
Liquidity Heatmap
Uses 20-period SMA of volume as a proxy for liquidity concentration.
Displayed using bar-style plots.
🟢🔴 Buy/Sell Signal Logic
Long Signal Conditions:
EMA Trend Up
RSI < 50
MACD Histogram > 0
Stoch RSI %K < 80
Ichimoku Cloud Bullish (CloudUp)
Short Signal Conditions:
EMA Trend Down
RSI > 50
MACD Histogram < 0
Stoch RSI %K > 20
Ichimoku Cloud Bearish (CloudDown)
🚨 Alert Conditions
longSignal → "Phoenix - BUY Signal"
shortSignal → "Phoenix - SELL Signal"
volumeExplode → "Phoenix - Volume Explosion Detected"
These alerts are compatible with TradingView's alert system for notifications.
💼 Position Sizing Calculation
Formula:
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Düzenle
Position Size = (Account Size × Risk %) / ATR
Adjusts trade size based on volatility and risk tolerance.
Visualized with a fuchsia line on the chart.
🧪 Strategy Execution
Uses Pine Script’s strategy.entry and strategy.close:
Opens long position when longSignal is true.
Opens short position when shortSignal is true.
Closes each position when the opposite signal appears.
📌 Extra Notes
Script uses Pine Script v5 and is optimized for max efficiency (max_lines_count=500).
Multiple market dynamics are integrated:
Trend
Momentum
Volume/Volatility
Sentiment
Liquidity
Risk Management
✅ Suggestions for Improvement
Integrate real news sentiment via APIs (e.g., BloombergHT RSS).
Add Take Profit / Stop Loss / Trailing Stop options.
Enhance visuals using label.new or table.new for clearer alerts.
Adapt position size logic for crypto/futures lot sizing.
Add multi-timeframe confirmation features.
Export strategy results or signals to a Telegram bot or external system.
Market Open Options Strategytrades directionally whatever first 90 seconds of trading day are for either 10 minutes or a reversal whatever comes first
Break of Structure - 1:1 RRSTILL IN TESTING PHASE FOLKS!!!! I have created a strategy script in TradingView using the basic TTA tenets. I am unable to figure out lot sizes and it doesn't work as well when I increase the winrate to 1:2 or 1:3. I used Chatgpt and Deepseek to build out a script. Iterated it and it gives me a high number of profitable trades = of course the RR is 1:1 so not getting too excited yet. Backtested for the 2024 on 4H timeframe. It tests well on GBPUSD and USDJPY (60% profitability across 18 trades in the year).
I'm struggling to code the right lot size. It keeps trading small values (my drawdown was approx 0.15% so you can imagine how low the lot size is). I will share the code and some screenshots.
Options Trading Strategy BTCOption Selling Directional Strategy based on supertrend with updated settings for option trading in forex crypto algo based
Scalping Strategy - Gold (5m)sin las etiquetas de compra y venta en otra ocasión hace uno mas desarrollado
4 EMAs with Entry and Exit Strategy🔍 Purpose of the Script:
This strategy is designed to identify bullish trends using a combination of Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI), and execute long entries and exits accordingly.
📈 Key Technical Indicators Used:
EMAs (Exponential Moving Averages):
ema9, ema21, ema63, and ema200 are calculated to determine short-, mid-, and long-term trends.
An unused ema126 is mentioned but commented out.
RSI (Relative Strength Index):
A 14-period RSI is calculated and used to avoid entries when the stock is overbought.
🟢 Entry Logic (Long):
The strategy enters a long position when:
A bullish trend is confirmed by EMA alignment:
ema9 > ema21 > ema63 > ema200
The closing price is above ema9
RSI is ≤ 60, to avoid entering overbought conditions
🔴 Exit Logic (Long Exit):
The strategy exits a long position when:
ema21 crosses below ema63 (bearish signal)
There are commented-out conditions like:
RSI > 80 (overbought)
Close > 1.4 × ema126 (price extended far above average)
🎨 Visualization:
EMAs are plotted in different colors for trend visibility.
Background color turns:
Light green in bullish trend
Light red in bearish trend
⚙️ Strategy Configuration:
Capital: ₹10,00,000
Position size: 10% of equity
Commission: 0.75% per trade (roundtrip)
Overlay: true (indicators and trades plotted on price chart)
✅ Highlights:
Clear trend detection with layered EMA logic
Avoids overbought entries using RSI ≤ 60
Customizable and extendable (e.g., you can uncomment EMA126 and add price-overextension logic)
PG2 Mean Reversion Channel - Lower Quartile Loband with MACD🧠 Strategy Overview
This is a mean reversion strategy using multi-filter smoothing for channel detection and MACD-based momentum validation. It’s designed for structured entries near volatility-based lower bounds with adaptive risk control based on dynamic equity drawdown.
⸻
📌 Core Logic
• Lower Quartile Channel Entry:
Uses 8 smoothing filters to create a distribution of lobands and selects the lower quartile as the trigger zone.
• MACD Validation:
Requires MACD histogram to flip from negative to positive, ensuring upward momentum confirmation.
• Entry Trigger:
Entry occurs when:
• Not in a position
• Price is below the lower quartile band
• MACD histogram is positive
⸻
📉 Dynamic Exit & Risk Control
• Per-Trade Equity Tracking:
Tracks equity highs/lows per trade to calculate intra-trade drawdown.
• Rolling Drawdown Threshold:
Stores drawdowns in a rolling array (up to maxGlobalTrades) and uses the max of that array as a dynamic exit threshold.
• Dynamic Drawdown Exit:
If a position is open for over minBarsForDynamicExit and drawdown exceeds the dynamic threshold → exit.
• Cascading Take Profit:
Profit target starts at 7% and slowly degrades by decrement_percent until a min threshold is hit.
• Extended Exit Logic:
After 1000 bars in a trade, triggers additional drawdown-based exit with MACD momentum check.
⸻
📊 Performance Multiplier Logic
• Uses strategy.closedtrades to calculate Profit Factor
• Multiplier is purely reporting metadata — included in alerts but not used for trade logic
• VPS or external system interprets and sizes trades accordingly
⸻
🔔 Automation-Ready Alerts
• Clean JSON payloads
• Payload includes:
• Ticker
• Action (buy3/sell3/sell1)
• Multiplier
• Timeframe & strategy name
⸻
✅ Compliance Highlights
• No repainting
• No security() calls
• No dynamic position sizing inside Pine
• Multiplier is metadata only
• Alerts structured for webhook consumption
Enhanced Momentum Wave Catcher2 minute scalping strategy using the 200 ema wave and MCB momentum wave and the 9 ema for entry.
eureka - with strategythis is based on ict teachings and it has fvg, ob, choch and so many things you cant imagine in 1 min tf
15 ORB Breakout-Retest with Pivot Points Standard1. 15 Minute Opening Range Breakout
2. Entry on Successful Breakout and Retest Confirmation
3. Pivot Points Standard
4. 21 EMA Trend table on different time frames
