Mutanabby_AI | ATR+ | Trend-Following StrategyThis document presents the Mutanabby_AI | ATR+ Pine Script strategy, a systematic approach designed for trend identification and risk-managed position entry in financial markets. The strategy is engineered for long-only positions and integrates volatility-adjusted components to enhance signal robustness and trade management.
Strategic Design and Methodological Basis
The Mutanabby_AI | ATR+ strategy is constructed upon a foundation of established technical analysis principles, with a focus on objective signal generation and realistic trade execution.
Heikin Ashi for Trend Filtering: The core price data is processed via Heikin Ashi (HA) methodology to mitigate transient market noise and accentuate underlying trend direction. The script offers three distinct HA calculation modes, allowing for comparative analysis and validation:
Manual Calculation: Provides a transparent and deterministic computation of HA values.
ticker.heikinashi(): Utilizes TradingView's built-in function, employing confirmed historical bars to prevent repainting artifacts.
Regular Candles: Allows for direct comparison with standard OHLC price action.
This multi-methodological approach to trend smoothing is critical for robust signal generation.
Adaptive ATR Trailing Stop: A key component is the Average True Range (ATR)-based trailing stop. ATR serves as a dynamic measure of market volatility. The strategy incorporates user-defined parameters (
Key Value and ATR Period) to calibrate the sensitivity of this trailing stop, enabling adaptation to varying market volatility regimes. This mechanism is designed to provide a dynamic exit point, preserving capital and locking in gains as a trend progresses.
EMA Crossover for Signal Generation: Entry and exit signals are derived from the interaction between the Heikin Ashi derived price source and an Exponential Moving Average (EMA). A crossover event between these two components is utilized to objectively identify shifts in momentum, signaling potential long entry or exit points.
Rigorous Stop Loss Implementation: A critical feature for risk mitigation, the strategy includes an optional stop loss. This stop loss can be configured as a percentage or fixed point deviation from the entry price. Importantly, stop loss execution is based on real market prices, not the synthetic Heikin Ashi values. This design choice ensures that risk management is grounded in actual market liquidity and price levels, providing a more accurate representation of potential drawdowns during backtesting and live operation.
Backtesting Protocol: The strategy is configured for realistic backtesting, employing fill_orders_on_standard_ohlc=true to simulate order execution at standard OHLC prices. A configurable Date Filter is included to define specific historical periods for performance evaluation.
Data Visualization and Metrics: The script provides on-chart visual overlays for buy/sell signals, the ATR trailing stop, and the stop loss level. An integrated information table displays real-time strategy parameters, current position status, trend direction, and key price levels, facilitating immediate quantitative assessment.
Applicability
The Mutanabby_AI | ATR+ strategy is particularly suited for:
Cryptocurrency Markets: The inherent volatility of assets such as #Bitcoin and #Ethereum makes the ATR-based trailing stop a relevant tool for dynamic risk management.
Systematic Trend Following: Individuals employing systematic methodologies for trend capture will find the objective signal generation and rule-based execution aligned with their approach.
Pine Script Developers and Quants: The transparent code structure and emphasis on realistic backtesting provide a valuable framework for further analysis, modification, and integration into broader quantitative models.
Automated Trading Systems: The clear, deterministic entry and exit conditions facilitate integration into automated trading environments.
Implementation and Evaluation
To evaluate the Mutanabby_AI | ATR+ strategy, apply the script to your chosen chart on TradingView. Adjust the input parameters (Key Value, ATR Period, Heikin Ashi Method, Stop Loss Settings) to observe performance across various asset classes and timeframes. Comprehensive backtesting is recommended to assess the strategy's historical performance characteristics, including profitability, drawdown, and risk-adjusted returns.
I'd love to hear your thoughts, feedback, and any optimizations you discover! Drop a comment below, give it a like if you find it useful, and share your results.
Cari dalam skrip untuk "the strat"
Marcius Studio® - Cross-Asset Correlator™Cross-Asset Correlator™ — a pair-trading strategy that identifies correlation breakdowns between two assets and captures profit opportunities from market inefficiencies.
The strategy enters trades when the correlation drops below a set threshold and closes positions once correlation recovers.
The main concept is to exploit temporary divergence between two assets by going long the stronger one and short the weaker one, aiming to profit when their correlation reverts.
Important : This script illustrates asset correlation concepts for educational purposes only. It's not for live trading—requires adjustments and offers no performance guarantees. Always apply risk management.
TradingView Limitation
By default, TradingView’s built-in Strategy interface does not support backtesting with two different assets .
To overcome this, the script is implemented as an indicator with a fully custom backtesting engine that calculates PnL, trades, and performance statistics directly on the chart.
Idea
Markets move in clusters : altcoins follow BTC, memecoins track Solana, L2 projects mirror Ethereum. But correlations aren’t perfect—temporary divergences create pricing inefficiencies.
The logic:
When an asset lags or overshoots its usual correlation, it’s a mispricing opportunity.
Trade the reversion: buy undervalued divergence, sell overextended convergence.
The market eventually corrects, but the inefficiency window allows profit before realignment.
OKX Signal Bot Integration
This script includes a built-in interface for OKX Signal Bot .
It can generate structured JSON alerts (ENTER / EXIT, long / short) and directly manage trades on OKX exchange .
This allows seamless automation of correlation-based strategies without manual order execution.
Note : The OKX Signal Bot (for demo use only) assists with alerts & trade management but does not ensure profits. You are fully responsible for your trades—always apply risk management.
Strategy Parameters
Symbol 1 / Symbol 2 : trading instruments to be analyzed.
SMA Period : smoothing period for price averages.
Correlation Period : number of bars used to calculate correlation coefficient.
Upper Correlation Threshold : level above which trades are closed.
Lower Correlation Threshold : level below which new trades are opened.
percentage_investment (%) : allocation per entry signal (used for OKX integration).
Example Settings OKX:FARTCOINUSDT.P / OKX:PENGUUSDT.P
Timeframe : 1H
SMA Period : 60
Correlation Period : 25
Upper Threshold : 0.9
Lower Threshold : 0.1
percentage_investment : 10%
How the Code Works
Retrieves closing prices of two selected assets.
Calculates correlation coefficient and moving averages.
When correlation breaks below the lower threshold, the script opens a pair trade (long/short depending on SMA relation).
When correlation recovers above the upper threshold, all open trades are closed.
Real-time alerts are generated in JSON format for OKX bots (ENTER/EXIT signals).
Built-in backtesting engine tracks PnL, trades, and statistics (7d / 30d / total).
Visual labels mark entries, exits, and PnL results directly on the chart.
Disclaimer
Trading involves risk — always do your own research (DYOR) and seek professional financial advice. We are not responsible for any potential financial losses.
Wickless Tap Signals Wickless Tap Signals — TradingView Indicator (v6)
A precision signal-only tool that marks BUY/SELL events when price “retests” the base of a very strong impulse candle (no wick on the retest side) in the direction of trend.
What it does (in plain English)
Finds powerful impulse candles:
Bull case: a green candle with no lower wick (its open ≈ low).
Bear case: a red candle with no upper wick (its open ≈ high).
Confirms trend with an EMA filter:
Only looks for bullish bases while price is above the EMA.
Only looks for bearish bases while price is below the EMA.
Waits for the retest (“tap”):
Later, if price revisits the base of that wickless candle
Bullish: taps the candle’s low/open → BUY signal
Bearish: taps the candle’s high/open → SELL signal
Optional level “consumption” so each base can trigger one signal, not many.
The idea: a wickless impulse often marks strong initiative order flow. The first retest of that base frequently acts as a springboard (bull) or ceiling (bear).
Exact rules (formal)
Let tick = syminfo.mintick, tol = tapTicks * tick.
Trend filter
inUp = close > EMA(lenEMA)
inDn = close < EMA(lenEMA)
Wickless impulse candles (confirmed on bar close)
Bullish wickless: close > open and abs(low - open) ≤ tol
Bearish wickless: close < open and abs(high - open) ≤ tol
When such a candle closes with trend alignment:
Store bullTapLevel = low (for bull case) and its bar index.
Store bearTapLevel = high (for bear case) and its bar index.
Signals (must happen on a later bar than the origin)
BUY: low ≤ bullTapLevel + tol and inUp and bar_index > bullBarIdx
SELL: high ≥ bearTapLevel - tol and inDn and bar_index > bearBarIdx
One-shot option
If enabled, once a signal fires, the stored level is cleared so it won’t trigger again.
Inputs (Settings)
Trend EMA Length (lenEMA): Default 200.
Use 50–100 for intraday, 200 for swing/position.
Tap Tolerance (ticks) (tapTicks): Default 1.
Helps account for tiny feed discrepancies. Set 0 for strict equality.
One Signal per Level (oneShot): Default ON.
If OFF, multiple taps can create multiple signals.
Plot Tap Levels (plotLevels): Draws horizontal lines at active bases.
Show Pattern Labels (showLabels): Marks the origin wickless candles.
Plots & Visuals
EMA trend line for context.
Tap Levels:
Green line at bullish base (origin candle’s low/open).
Red line at bearish base (origin candle’s high/open).
Signals:
BUY: triangle-up below the bar on the tap.
SELL: triangle-down above the bar on the tap.
Labels (optional):
Marks the original wickless impulse candle that created each level.
Alerts
Two alert conditions are built in:
“BUY Signal” — fires when a bullish tap occurs.
“SELL Signal” — fires when a bearish tap occurs.
How to set:
Add the indicator to your chart.
Click Alerts (⏰) → Condition = this indicator.
Choose BUY Signal or SELL Signal.
Set your alert frequency and delivery method.
Recommended usage
Timeframes: Works on any; start with 5–15m intraday, or 1H–1D for swing.
Markets: Equities, futures, FX, crypto. For thin/illiquid assets, consider a slightly larger Tap Tolerance.
Confluence ideas (optional, but helpful):
Higher-timeframe trend agreeing with your chart timeframe.
Volume surge on the origin wickless candle.
S/R, order blocks, or SMC structures near the tap level.
Avoid major news moments when slippage is high.
No-repaint behavior
Origin patterns are detected only on bar close (barstate.isconfirmed), so bases are created with confirmed data.
Signals come after the origin bar, on subsequent taps.
There is no lookahead; lines and shapes reflect information known at the time.
(As with all real-time indicators, an intrabar tap can trigger an alert during the live bar; the signal then remains if that condition held at bar close.)
Known limitations & design choices
Single active level per side: The script tracks only the most recent bullish base and most recent bearish base.
Want a queue of multiple simultaneous bases? That’s possible with arrays; ask and we’ll extend it.
Heikin Ashi / non-standard candles: Wick definitions change; for consistent behavior use regular OHLC candles.
Gaps: On large gaps, taps can occur instantly at the open. Consider one-shot ON to avoid rapid repeats.
This is an indicator, not a strategy: It does not place trades or compute PnL. For backtesting, we can convert it into a strategy with SL/TP logic (ATR or structure-based).
Practical tips
Tap Tolerance:
If you miss obvious taps by a hair, increase to 1–2 ticks.
For FX/crypto with tiny ticks, even 0 or 1 is often enough.
EMA length:
Shorten for faster signals; lengthen for cleaner trend selection.
Risk management (manual suggestion):
For BUY signals, consider a stop slightly below the tap level (or ATR-based).
For SELL signals, consider a stop slightly above the tap level.
Scale out or trail using structure or ATR.
Quick checklist
✅ Price above EMA → watch for a green no-lower-wick candle → store its low → BUY on tap.
✅ Price below EMA → watch for a red no-upper-wick candle → store its high → SELL on tap.
✅ Use Tap Tolerance to avoid missing precise touches by one tick.
✅ Consider One Signal per Level to keep trades uncluttered.
FAQ
Q: Why did I not get a signal even though price touched the level?
A: Check Tap Tolerance (maybe too strict), trend alignment at the tap bar, and that the tap happened after the origin candle. Also confirm you’re on regular candles.
Q: Can I see multiple bases at once?
A: This version tracks the latest bull and bear bases. We can extend to arrays to keep N recent bases per side.
Q: Will it repaint?
A: No. Bases form on confirmed closes, and signals only on later bars.
Q: Can I backtest it?
A: This is a study. Ask for the strategy variant and we’ll add entries, exits, SL/TP, and stats.
ALMA & UT Bot Confluence StrategyALMA & UT Bot Confluence Strategy
This is a comprehensive trend-following and momentum strategy designed to identify high-probability trade setups by combining multiple layers of confirmation. It is built around an ALMA (Arnaud Legoux Moving Average) and a long-term EMA, and then enhances signal quality with the popular UT Bot indicator, a Volume Filter, and an adaptive hold mechanism.
The primary goal of this strategy is to filter out market noise, avoid low liquidity traps, and provide more robust and selective trading logic by adapting its timing to changing market volatility.
Key Features and How It Works
This strategy is not a simple crossover system. An entry signal is generated by the confluence of only a few conditions:
Underlying Trend and Signal Engine:
ALMA (Arnaud Legoux Moving Average): Provides a responsive, low-latency signal line for entries. EMA (Exponential Moving Average): A longer-term EMA acts as a primary trend filter, ensuring trades are executed only in line with the overall market trend.
Confirmation Layer:
UT Bot Confirmation: A trade is considered valid only when the UT Bot indicator provides a relevant buy or sell signal. This acts as a strong secondary confirmation, reducing false entries.
Advanced Filters for Signal Quality:
Volume Filter: This is an important safety mechanism that prevents trades from being executed in low-volume, illiquid markets where price action can be erratic and unreliable.
Momentum Filter (ADX and RSI): The strategy uses the ADX to check for sufficient market momentum and the RSI to ensure it doesn't enter overbought/oversold zones.
Volatility Filter (Bollinger Bands): This helps prevent entries when the price deviates too far from its average, preventing "buying at the top" or "selling at the bottom." Adaptive Timing (Dynamic Cool-Down):
Instead of a fixed waiting period between trades, this strategy uses a dynamic cooling-down period based on the ATR. It automatically waits longer during periods of high volatility (to prevent volatility) and becomes more responsive in calmer markets. How to Use This Strategy:
Long Entry (BUY): When all bullish conditions align, a green "BUY" triangle appears below the price.
Short Entry (SELL): When all bearish conditions align, a red "SELL" triangle appears above the price.
Trend Visualization: The chart background is color-coded according to UT Bot's trend direction (Green for an uptrend, Red for a downtrend), allowing for at-a-glance market analysis.
Double Exit Strategy Options
You have full control over how you exit trades:
Classic SL/TP: Use a standard Stop-Loss and Take-Profit order based on ATR (Average True Range) multipliers. UT Bot Trailing Stop (Recommended): A dynamic exit mechanism that follows the price allows your winning trades to catch up to larger trends while protecting your profits.
Disclaimer
This script is for educational purposes only and should not be construed as financial advice. Past performance is not indicative of future results. All trades involve risk. Before risking any capital, we strongly recommend extensively backtesting this strategy across your preferred assets and timeframes to understand its behavior and find settings that suit your personal trading style.
The author recommends using this strategy with Heikin-Ashi candlesticks. Using this method will significantly increase the strategy's trading success rate and profitability in backtests.
You should change the settings according to your preferred chart time range. You can find the best value for you by observing the value changes you make on the chart.
Gemini Trend Following SystemStrategy Description: The Gemini Trend Following System
Core Philosophy
This is a long-term trend-following system designed for a position trader or a patient swing trader, not a day trader. The fundamental goal is to capture the majority of a stock's major, multi-month or even multi-year uptrend.
The core principle is: "Buy weakness in a confirmed uptrend, and sell only when the uptrend's structure is fundamentally broken."
It operates on the belief that it's more profitable to ride a durable trend than to chase short-term breakouts or worry about daily price fluctuations. It prioritizes staying in a winning trade over frequent trading.
The Three Pillars of the Strategy
The script's logic is built on three distinct pillars, processed in order:
1. The Regime Filter: "Is This Stock in a Healthy Uptrend?"
Before even considering a trade, the script acts as a strict gatekeeper. It will only "watch" a stock if it meets all the criteria of a healthy, long-term uptrend. This is the most important part of the strategy as it filters out weak or speculative stocks.
A stock passes this filter if:
The 50-day Simple Moving Average (SMA) is above the 200-day SMA. This is the classic definition of a "Golden Cross" state, indicating the medium-term trend is stronger than the long-term trend—a hallmark of a bull market for the stock.
The stock's performance over the last year is positive. The Rate of Change (ROC) must be above a minimum threshold (e.g., 15%). This ensures we are only looking at stocks that have already demonstrated significant strength.
The 200-day SMA itself is rising. This is a crucial check to ensure the very foundation of the trend is solid and not flattening out or beginning to decline.
If a stock doesn't meet these conditions, the script ignores it completely.
2. The Entry Trigger: "When to Buy the Dip"
Once a stock is confirmed to be in a healthy uptrend, the script does not buy immediately. Instead, it patiently waits for a point of lower risk and higher potential reward—a pullback.
The entry trigger is a specific, two-step sequence:
The stock price first dips and closes below its 50-day SMA. This signifies a period of temporary weakness or profit-taking.
The price then recovers and closes back above the 50-day SMA within a short period (10 bars).
This sequence is a powerful signal. It suggests that institutional buyers view the 50-day SMA as a key support level and have stepped in to defend it, overpowering the sellers. The entry occurs at this point of confirmed support, marking the likely resumption of the uptrend. On the chart, this event is highlighted with a teal background.
3. The Exit Strategy: "When is the Trend Over?"
The exit logic is designed to keep you in the trade as long as possible and only sell when the trend's character has fundamentally changed. It uses a dual-exit system:
Primary Exit (Trend Failure): The main reason to sell is a "Death Cross"—when the 50-day SMA crosses below the 200-day SMA. This is a robust, albeit lagging, signal that the long-term uptrend is over and a bearish market structure is taking hold. This exit condition is designed to ignore normal market corrections and only trigger when the underlying trend has truly broken. On the chart, this is highlighted with a maroon background.
Safety-Net Exit (Catastrophic Stop-Loss): To protect against a sudden market crash or a company-specific disaster, a "safety-net" stop-loss is placed at the time of entry. This stop is set far below the entry price, typically underneath the 200-day SMA. It is a "just-in-case" measure that should only be triggered in a severe and rapid decline, protecting your capital from an unexpected black swan event.
Who is This Strategy For?
Position Traders: Investors who are comfortable holding a stock for many months to over a year.
Patient Swing Traders: Traders who want to capture large price swings over weeks and months, not days.
Investors using a Rules-Based Approach: Anyone looking to apply a disciplined, non-emotional system to their long-term portfolio.
Ideal Market Conditions
This strategy excels in markets with clear, durable trends. It performs best on strong, leading stocks during a sustained bull market. It will underperform significantly or generate losses in choppy, sideways, or range-bound markets, where the moving averages will frequently cross back and forth, leading to "whipsaw" trades.
Keltner Channel Based Grid Strategy # KC Grid Strategy - Keltner Channel Based Grid Trading System
## Strategy Overview
KC Grid Strategy is an innovative grid trading system that combines the power of Keltner Channels with dynamic position sizing to create a mean-reversion trading approach. This strategy automatically adjusts position sizes based on price deviation from the Keltner Channel center line, implementing a systematic grid-based approach that capitalizes on market volatility and price oscillations.
## Core Principles
### Keltner Channel Foundation
The strategy builds upon the Keltner Channel indicator, which consists of:
- **Center Line**: Moving average (EMA or SMA) of the price
- **Upper Band**: Center line + (ATR/TR/Range × Multiplier)
- **Lower Band**: Center line - (ATR/TR/Range × Multiplier)
### Grid Trading Logic
The strategy implements a sophisticated grid system where:
1. **Position Direction**: Inversely correlated to price position within the channel
- When price is above center line → Short positions
- When price is below center line → Long positions
2. **Position Size**: Proportional to distance from center line
- Greater deviation = Larger position size
3. **Grid Activation**: Positions are adjusted only when the difference exceeds a predefined grid threshold
### Mathematical Foundation
The core calculation uses the KC Rate formula:
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
This creates a mean-reversion system where positions increase as price moves further from the mean, expecting eventual return to equilibrium.
## Parameter Guide
### Time Range Settings
- **Start Date**: Beginning of strategy execution period
- **End Date**: End of strategy execution period
### Core Parameters
1. **Number of Grids (NumGrid)**: Default 12
- Controls grid sensitivity and position adjustment frequency
- Higher values = More frequent but smaller adjustments
- Lower values = Less frequent but larger adjustments
2. **Length**: Default 10
- Period for moving average and volatility calculations
- Shorter periods = More responsive to recent price action
- Longer periods = Smoother, less noisy signals
3. **Grid Coefficient (kcRateMult)**: Default 1.33
- Multiplier for channel width calculation
- Higher values = Wider channels, less frequent trades
- Lower values = Narrower channels, more frequent trades
4. **Source**: Default Close
- Price source for calculations (Close, Open, High, Low, etc.)
- Close price typically provides most reliable signals
5. **Use Exponential MA**: Default True
- True = Uses EMA (more responsive to recent prices)
- False = Uses SMA (equal weight to all periods)
6. **Bands Style**: Default "Average True Range"
- **Average True Range**: Smoothed volatility measure (recommended)
- **True Range**: Current bar's volatility only
- **Range**: Simple high-low difference
## How to Use
### Setup Instructions
1. **Apply to Chart**: Add the strategy to your desired timeframe and instrument
2. **Configure Parameters**: Adjust settings based on market characteristics:
- Volatile markets: Increase Grid Coefficient, reduce Number of Grids
- Stable markets: Decrease Grid Coefficient, increase Number of Grids
3. **Set Time Range**: Define your backtesting or live trading period
4. **Monitor Performance**: Watch strategy performance metrics and adjust as needed
### Optimal Market Conditions
- **Range-bound markets**: Strategy performs best in sideways trending markets
- **High volatility**: Benefits from frequent price oscillations around the mean
- **Liquid instruments**: Ensures efficient order execution and minimal slippage
### Position Management
The strategy automatically:
- Calculates optimal position sizes based on account equity
- Adjusts positions incrementally as price moves through grid levels
- Maintains risk control through maximum position limits
- Executes trades only during specified time periods
## Risk Warnings
### ⚠️ Important Risk Considerations
1. **Trending Market Risk**:
- Strategy may underperform or generate losses in strong trending markets
- Mean-reversion assumption may fail during sustained directional moves
- Consider market regime analysis before deployment
2. **Leverage and Position Size Risk**:
- Strategy uses pyramiding (up to 20 positions)
- Large positions may accumulate during extended moves
- Monitor account equity and margin requirements closely
3. **Volatility Risk**:
- Sudden volatility spikes may trigger multiple rapid position adjustments
- Consider volatility filters during high-impact news events
- Backtest across different volatility regimes
4. **Execution Risk**:
- Strategy calculates on every tick (calc_on_every_tick = true)
- May generate frequent orders in volatile conditions
- Ensure adequate execution infrastructure and consider transaction costs
5. **Parameter Sensitivity**:
- Performance highly dependent on parameter optimization
- Over-optimization may lead to curve-fitting
- Regular parameter review and adjustment may be necessary
## Suitable Scenarios
### Ideal Market Conditions
- **Sideways/Range-bound markets**: Primary use case
- **Mean-reverting instruments**: Forex pairs, some commodities
- **Stable volatility environments**: Consistent ATR patterns
- **Liquid markets**: Major currency pairs, popular stocks/indices
## Important Notes
### Strategy Limitations
1. **No Stop Loss**: Strategy relies on mean reversion without traditional stop losses
2. **Capital Requirements**: Requires sufficient capital for grid-based position sizing
3. **Market Regime Dependency**: Performance varies significantly across different market conditions
## Disclaimer
This strategy is provided for educational and research purposes only. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Users should thoroughly test the strategy and understand its mechanics before risking real capital. The author assumes no responsibility for trading losses incurred through the use of this strategy.
---
# KC网格策略 - 基于肯特纳通道的网格交易系统
## 策略概述
KC网格策略是一个创新的网格交易系统，它将肯特纳通道的力量与动态仓位调整相结合，创建了一个均值回归交易方法。该策略根据价格偏离肯特纳通道中心线的程度自动调整仓位大小，实施系统化的网格方法，利用市场波动和价格振荡获利。
## 核心原理
### 肯特纳通道基础
该策略建立在肯特纳通道指标之上，包含：
- **中心线**: 价格的移动平均线（EMA或SMA）
- **上轨**: 中心线 + (ATR/TR/Range × 乘数)
- **下轨**: 中心线 - (ATR/TR/Range × 乘数)
### 网格交易逻辑
该策略实施复杂的网格系统：
1. **仓位方向**: 与价格在通道中的位置呈反向关系
- 当价格高于中心线时 → 空头仓位
- 当价格低于中心线时 → 多头仓位
2. **仓位大小**: 与距离中心线的距离成正比
- 偏离越大 = 仓位越大
3. **网格激活**: 只有当差异超过预定义的网格阈值时才调整仓位
### 数学基础
核心计算使用KC比率公式：
```
kcRate = (close - ma) / bandWidth
targetPosition = kcRate × maxAmount × (-1)
```
这创建了一个均值回归系统，当价格偏离均值越远时仓位越大，期望最终回归均衡。
## 参数说明
### 时间范围设置
- **开始日期**: 策略执行期间的开始时间
- **结束日期**: 策略执行期间的结束时间
### 核心参数
1. **网格数量 (NumGrid)**: 默认12
- 控制网格敏感度和仓位调整频率
- 较高值 = 更频繁但较小的调整
- 较低值 = 较少频繁但较大的调整
2. **长度**: 默认10
- 移动平均线和波动率计算的周期
- 较短周期 = 对近期价格行为更敏感
- 较长周期 = 更平滑，噪音更少的信号
3. **网格系数 (kcRateMult)**: 默认1.33
- 通道宽度计算的乘数
- 较高值 = 更宽的通道，较少频繁的交易
- 较低值 = 更窄的通道，更频繁的交易
4. **数据源**: 默认收盘价
- 计算的价格来源（收盘价、开盘价、最高价、最低价等）
- 收盘价通常提供最可靠的信号
5. **使用指数移动平均**: 默认True
- True = 使用EMA（对近期价格更敏感）
- False = 使用SMA（对所有周期等权重）
6. **通道样式**: 默认"平均真实范围"
- **平均真实范围**: 平滑的波动率测量（推荐）
- **真实范围**: 仅当前K线的波动率
- **范围**: 简单的高低价差
## 使用方法
### 设置说明
1. **应用到图表**: 将策略添加到您所需的时间框架和交易品种
2. **配置参数**: 根据市场特征调整设置：
- 波动市场：增加网格系数，减少网格数量
- 稳定市场：减少网格系数，增加网格数量
3. **设置时间范围**: 定义您的回测或实盘交易期间
4. **监控表现**: 观察策略表现指标并根据需要调整
### 最佳市场条件
- **区间震荡市场**: 策略在横盘趋势市场中表现最佳
- **高波动性**: 受益于围绕均值的频繁价格振荡
- **流动性强的品种**: 确保高效的订单执行和最小滑点
### 仓位管理
策略自动：
- 根据账户权益计算最优仓位大小
- 随着价格在网格水平移动逐步调整仓位
- 通过最大仓位限制维持风险控制
- 仅在指定时间段内执行交易
## 风险警示
### ⚠️ 重要风险考虑
1. **趋势市场风险**:
- 策略在强趋势市场中可能表现不佳或产生损失
- 在持续方向性移动期间均值回归假设可能失效
- 部署前考虑市场制度分析
2. **杠杆和仓位大小风险**:
- 策略使用金字塔加仓（最多20个仓位）
- 在延长移动期间可能积累大仓位
- 密切监控账户权益和保证金要求
3. **波动性风险**:
- 突然的波动性激增可能触发多次快速仓位调整
- 在高影响新闻事件期间考虑波动性过滤器
- 在不同波动性制度下进行回测
4. **执行风险**:
- 策略在每个tick上计算（calc_on_every_tick = true）
- 在波动条件下可能产生频繁订单
- 确保充足的执行基础设施并考虑交易成本
5. **参数敏感性**:
- 表现高度依赖于参数优化
- 过度优化可能导致曲线拟合
- 可能需要定期参数审查和调整
## 适用场景
### 理想市场条件
- **横盘/区间震荡市场**: 主要用例
- **均值回归品种**: 外汇对，某些商品
- **稳定波动性环境**: 一致的ATR模式
- **流动性市场**: 主要货币对，热门股票/指数
## 注意事项
### 策略限制
1. **无止损**: 策略依赖均值回归而无传统止损
2. **资金要求**: 需要充足资金进行基于网格的仓位调整
3. **市场制度依赖性**: 在不同市场条件下表现差异显著
## 免责声明
该策略仅供教育和研究目的。过往表现不保证未来结果。交易涉及重大损失风险，并非适合所有投资者。用户应在投入真实资金前彻底测试策略并理解其机制。作者对使用此策略产生的交易损失不承担任何责任。
---
**Strategy Version**: Pine Script v6
**Author**: Signal2Trade
**Last Updated**: 2025-8-9
**License**: Open Source (Mozilla Public License 2.0)
Gelişmiş Mum Ters StratejiAdvanced Candle Reversal Strategy Overview
This TradingView PineScript indicator detects potential reversal signals in candlestick patterns, focusing on a sequence of directional candles followed by a wick-based reversal candle. Here's a step-by-step breakdown:
User Inputs:
candleCount (default: 6): Number of consecutive candles required (2–20).
wickRatio (default: 1.5): Minimum wick-to-body ratio for reversal (1.0–5.0).
Options to show background colors and an info table.
Candle Calculations:
Computes body size (|close - open|), upper wick (high - max(close, open)), and lower wick (min(close, open) - low).
Identifies bullish (close > open) or bearish (close < open) candles.
Checks for long upper wick (≥ body * wickRatio) for short signals or long lower wick for long signals.
Sequence Check:
Verifies if the last candleCount candles are all bearish (for long signal) or all bullish (for short signal), including the current candle.
Signal Conditions:
Long Signal: candleCount bearish candles + current candle has long lower wick (plotted as green upward triangle below bar with "LONG" text).
Short Signal: candleCount bullish candles + current candle has long upper wick (plotted as red downward triangle above bar with "SHORT" text).
Additional Features:
Alerts for signals with custom messages.
Optional translucent background color (green for long, red for short).
Plots tiny crosses for long wicks not triggering full signals (yellow above for upper, orange below for lower).
Info table (top-right): Displays strategy summary, candle count, and signal explanations.
Debug label: On signals, shows wick/body ratio above the bar.
The strategy aims for reversals after trends (e.g., after 6 red candles, a red candle with long lower wick signals buy). Customize via inputs; backtest for effectiveness. Not financial advice.
Canuck Trading Traders Strategy [Candle Entropy Edition]Canuck Trading Traders Strategy: A Unique Entropy-Based Day Trading System for Volatile Stocks
Overview
The Canuck Trading Traders Strategy is a custom, entropy-driven day trading system designed for high-volatility stocks like TSLA on short timeframes (e.g., 15m). At its core is CETP-Plus, a proprietary blended indicator that measures "order from chaos" in candle patterns using Shannon entropy, while embedding mathematical principles from EMA (recent weighting), RSI (momentum bias), ATR (volatility scaling), and ADX (trend strength) into a single score. This unique approach avoids layering multiple indicators, reducing complexity while improving timing for early trend detection and balanced long/short trades.
CETP-Plus calculates a score from weighted candle ratios (body, upper/lower wicks) binned into a 3D histogram for entropy (low entropy = strong pattern). The score is adjusted with momentum, volatility, and trend multipliers for robust signals. Entries occur when the score exceeds thresholds (positive for longs, negative for shorts), with exits on reversals or stops. The strategy is automatic—no manual bias needed—and optimized for margin accounts with equal long/short treatment.
Backtested on TSLA 15m (Jan 2015–Aug 2025), it targets +50,000% net profit (beating +1,478% buy-hold by 34x) with ~25,000 trades, 85-90% win rate, and <10% drawdown (with costs). Results vary by timeframe/period—test with your data and add slippage/commission for realism. Disclaimer: Past performance isn't indicative of future results; consult a financial advisor.
Key Features
CETP-Plus Indicator: Blends entropy with momentum/vol/trend for a single score, capturing bottoms/squeezes and trends without external tools.
Automatic Balance: Positive scores trigger longs in bull trends, negative scores trigger shorts in bear trends—no user input for direction.
Customizable Math: Tune weights and scales to adapt for different stocks (e.g., lower thresholds for NVDA's smoother trends).
Risk Controls: Stop-loss, trailing stops, and score strength filter to minimize drawdowns in volatile markets like TSLA.
Exit Debugging: Plots exit reasons ("Stop Loss", "Trail Stop", "CETP Exit") for analysis.
Input Settings and Purposes
All inputs are grouped in TradingView's Inputs tab for ease. Defaults are optimized for TSLA 15m day trading; adjust for other intervals or tickers (e.g., increase window for 1h, lower thresholds for NVDA).
CETP-Plus Settings
CETP Window (default: 5, min: 3, max: 20): Lookback bars for entropy/momentum. Short values (3-5) for fast sensitivity on short frames; longer (8-10) for stability on hourly+.
CETP Bins per Dimension (default: 3, min: 3, max: 10): Histogram granularity for entropy. Low (3) for speed/simple patterns; high (5+) for detail in complex markets.
Long Threshold (default: 0.15, min: 0.1, max: 0.8, step: 0.05): CETP score for long entries. Lower (0.1) for more longs in mild bull trends; higher (0.2) to filter noise.
Short Threshold (default: -0.05, min: -0.8, max: -0.1, step: 0.05): CETP score for short entries. Less negative (-0.05) for more shorts in mild bear trends; more negative (-0.2) for strong signals.
CETP Momentum Weight (default: 0.8, min: 0.1, max: 1.0, step: 0.1): Emphasizes momentum in score. High (0.9) for aggressive in fast moves; low (0.5) for entropy focus.
Momentum Scale (default: 1.6, min: 0.1, max: 2.0, step: 0.1): Amplifies momentum. High (2.0) for short intervals; low (1.0) for stability.
Body Ratio Weight (default: 1.2, min: 0.0, max: 2.0, step: 0.1): Weights candle body in entropy (trend focus). High (1.5) for strong trends; low (0.8) for wick emphasis.
Upper Wick Ratio Weight (default: 0.8, min: 0.0, max: 2.0, step: 0.1): Weights upper wick (reversal noise). Low (0.5) to reduce false ups.
Lower Wick Ratio Weight (default: 0.8, min: 0.0, max: 2.0, step=0.1): Weights lower wick. Low (0.5) to reduce false downs.
Trade Settings
Confirmation Bars (default: 0, min: 0, max: 5): Bars for sustained CETP signals. 0 for immediate entries (more trades); 1-2 for reliability (fewer but stronger).
Min CETP Score Strength (default: 0.04, min: 0.0, max: 0.5, step: 0.05): Min absolute score for entry. Low (0.04) for more trades; high (0.15) for quality.
Risk Management
Stop Loss (%) (default: 0.5, min: 0.1, max: 5.0, step: 0.1): % from entry for stop. Tight (0.4) for quick exits; wide (0.8) for trends.
ATR Multiplier (default: 1.5, min: 0.5, max: 3.0, step: 0.1): Scales ATR for stops/trails. Low (1.0) for tight; high (2.0) for room.
Trailing ATR Mult (default: 3.5, min: 0.5, max: 5.0, step: 0.1): ATR mult for trails. High (4.0) for longer holds; low (2.0) for profits.
Trail Start Offset (%) (default: 1.0, min: 0.5, max: 2.0, step: 0.1): % profit before trailing. Low (0.8) for early lock-in; high (1.5) for bigger moves.
These settings enable customization for intervals/tickers while CETP-Plus handles automatic balancing.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
StratNinjaTableAuthor’s Instructions for StratNinjaTable
Purpose:
This indicator is designed to provide traders with a clear and dynamic table displaying The Strat candle patterns across multiple timeframes of your choice.
Usage:
Use the input panel to select which timeframes you want to monitor in the table.
Choose the table position on the chart (top left, center, right, or bottom).
The table will update each bar, showing the candle type, direction arrow, and remaining time until the candle closes for each selected timeframe.
Hover over or inspect the table to understand current market structure per timeframe using The Strat methodology.
Notes:
The Strat pattern is displayed as "1", "2U", "2D", or "3" based on the relationship of current and previous candle highs and lows.
The timer updates in real-time and adapts to daily, weekly, monthly, and extended timeframes.
This script requires Pine Script version 6. Please use it on supported platforms.
MFI or other indicators are not included in this base version but can be integrated separately if desired.
Credits:
Developed and inspired by shayy110 — thanks for your foundational work on The Strat in Pine Script.
Disclaimer:
This script is for educational and informational purposes only. Always verify signals and manage risk accordingly.
Multi-Timeframe SFP + SMTImportant: Please Read First
This indicator is not a "one size fits all" solution. It is a professional and complex tool that requires you to learn how to use it, in addition to backtesting different settings to discover what works best for your specific trading style and the assets you trade. The default settings provided are my personal preferences for trading higher-timeframe setups, but you are encouraged to experiment and find your own optimal configuration.
Please note that while this initial version is solid, it may still contain small errors or bugs. I will be actively working on improving the indicator over time. Also, be aware that the script is not written for maximum efficiency and may be resource-intensive, but this should not pose a problem for most users.
The source code for this indicator is open. If you truly want to understand precisely how all the logic works, you can copy and paste the code into an AI assistant like Gemini or ChatGPT and ask it to explain any part of the script to you.
Author's Preferred Settings (Guideline)
As a starting point, here are the settings I personally use for my trading:
SFP Timeframe: 4-Hour (Strength: 5-5)
Max Lookback: 35 Bars
Raid Expiration: 1 Bar
SFP Lines Limit: 1
SMT Timeframe 1: 30-Minute (Strength: 2-2) with 3-Minute LTF Detection.
SMT Timeframe 2: 15-Minute (Strength: 3-3) with 3-Minute LTF Detection.
SMT Timeframe 3: 1-Hour (Strength: 1-1) with 3-Minute LTF Detection.
SMT Timeframe 4: 15-Minute (Strength: 1-1) with 3-Minute LTF Detection.
Multi-Timeframe SMT: An Overview
This indicator is a powerful tool designed to identify high-probability trading setups by combining two key institutional concepts: Swing Failure Patterns (SFP) on a higher timeframe and Smart Money Technique (SMT) divergences on a lower timeframe. A key feature is the ability to configure and run up to four independent SMT analyses simultaneously, allowing you to monitor for divergences across multiple timeframes (e.g., 15m, 1H, 4H) from a single indicator.
Its primary purpose is to generate automated signals through TradingView's alert system. By setting up alerts, the script runs server-side, monitoring the market for you. When a setup presents itself, it will send a push notification to your device, allowing you to personally evaluate the trade without being tied to your screen.
The Strategy: HTF Liquidity Sweeps into LTF SMT
The core strategy is built on a classic institutional trading model:
Wait for a liquidity sweep on a significant high timeframe (e.g., 4-hour, Daily).
Once liquidity is taken, look for a confirmation of a shift in market structure on a lower timeframe.
This indicator uses an SMT divergence as that confirmation signal, indicating that smart money may be stepping in to reverse the price.
How It Works: The Two-Step Process
The indicator's logic follows a precise two-step process to generate a signal:
Step 1: The Swing Failure Pattern (SFP)
First, the indicator identifies a high-timeframe liquidity sweep. This is configured in the "Swing Failure Pattern (SFP) Timeframe" settings.
It looks for a candle that wicks above a previous high (or below a previous low) but then closes back within the range of that pivot. This action is known as a "raid" or a "swing failure," suggesting the move failed to find genuine momentum.
Step 2: The SMT Divergence
The moment a valid SFP is confirmed, the indicator's multiple SMT engines activate.
Each engine begins monitoring the specific SMT timeframe you have configured (e.g., "SMT Timeframe 1," "SMT Timeframe 2," etc.) for a Smart Money Technique (SMT) divergence.
An SMT divergence occurs when two closely correlated assets fail to move in sync. For example, after a raid on a high, Asset A makes a new high, but Asset B fails to do so. This disagreement suggests weakness and a potential reversal.
When the script finds this divergence, it plots the SMT line and triggers an alert.
The Power of Alerts
The true strength of this indicator lies in its alert capabilities. You can create alerts for both unconfirmed and confirmed SMTs.
Enable Alerts LTF Detection: These alerts trigger when an unconfirmed, potential SMT is spotted on the lower "LTF Detection" timeframe. While not yet confirmed, these early alerts can notify you of a potential move before it fully happens, allowing you to be ahead of the curve and find the best possible trade entries.
Enable Alerts Confirmed SMT: These alerts trigger only when a permanent, confirmed SMT line is plotted on your chosen SMT timeframe. These signals are more reliable but occur later than the early detection alerts.
Key Concepts Explained
What is Pivot Strength?
Pivot Strength determines how significant a high or low needs to be to qualify as a valid structural point. A setting of 5-5, for example, means that for a candle's high to be considered a valid pivot high, its high must be higher than the highs of the 5 candles to its left and the 5 candles to its right.
Higher Strength (e.g., 5-5, 8-8): Creates fewer, but more significant, pivots. This is ideal for identifying major structural highs and lows on higher timeframes.
Lower Strength (e.g., 2-2, 3-3): Creates more pivots, making it suitable for identifying the smaller shifts in momentum on lower timeframes.
Raid Expiration & Validity
An SFP signal is not valid forever. The "Raid Expiration" setting determines how many SFP timeframe bars can pass after a raid before that signal is considered "stale" and can no longer be used to validate an SMT. This ensures your SMT divergences are always in response to recent liquidity sweeps.
Why You Must Be on the Right Chart Timeframe to See SMT Lines
Pine Script™ has a fundamental rule: an indicator running on a chart can only "see" the bars of that chart's timeframe or higher.
When the SMT logic is set to the 15-minute timeframe, it calculates its pivots based on 15-minute data. To accurately plot lines connecting these pivots, you must be on a 15-minute chart or lower (e.g., 5-minute, 1-minute).
If you are on a higher timeframe chart, like the 1-hour, the 15-minute bars do not exist on that chart, so the indicator has no bars to draw the lines on.
This is precisely why the alert system is so powerful. You can set your alert to run on the 15-minute timeframe, and TradingView's servers will monitor that timeframe for you, sending a notification regardless of what chart you are currently viewing.
Fisher Crossover StrategyThe Fisher Crossover Strategy is a popular technical trading method that uses the Fisher Transform indicator developed by John Ehlers. This indicator mathematically converts price data into a normal Gaussian distribution, making market turning points sharper and easier to identify. The strategy is based on two lines: the Fisher line, which is the main transformed price value, and the Trigger line, which is a one-period lag of the Fisher line. Traders use the crossover of these lines to determine buy and sell opportunities.
A buy signal is generated when the Fisher line crosses above the Trigger line, indicating that bullish momentum may be starting, while a sell signal occurs when the Fisher line crosses below the Trigger line, suggesting a possible bearish reversal. Signals that occur relative to the zero line are often considered stronger; for example, a buy signal below the zero line may indicate a deeper market reversal. The strategy is simple to follow and can be applied to various markets including stocks, forex, commodities, and cryptocurrencies.
However, like all crossover strategies, it can produce false signals during sideways or ranging markets. To reduce whipsaws, traders often combine the Fisher Crossover Strategy with other tools such as support and resistance levels, volume analysis, or moving averages. Proper risk management with stop-loss and take-profit levels is also essential. Overall, the Fisher Crossover Strategy is valued for its clear entry and exit rules and its ability to highlight potential market reversals earlier than many other indicators.
MA Crossover Detector
The Moving Average Crossover Detector is a custom indicator that visually shows buy and sell signals clearly on the chart. based on the crossing of two moving averages — a popular and beginner-friendly tool in technical analysis.
It plots two moving averages — One fast (short period) and one slow (long period) — and highlights crossover points:
✅ Buy Signal (Golden Cross) – When the fast MA crosses above the slow MA.
❌ Sell Signal (Death Cross) – When the fast MA crosses below the slow MA.
✅ Features
Visual: Clearly shows crossovers on the chart.
Customizable: Choose periods, types, styles, etc.
Alert-ready: You can set alerts for crossovers.
The Moving Average (MA) Crossover Strategy is one of the simplest and most widely used strategies in technical analysis for trading stocks, forex, crypto, and other markets. It relies on the interaction between two moving averages to generate buy and sell signals.
Core Components
Short-Term Moving Average (Fast MA) : Reacts quickly to price changes (e.g., 9-period or 20-period).
Long-Term Moving Average (Slow MA) : Reacts more slowly to price changes (e.g., 21-period or 200-period).
How the Strategy Works
Bullish Crossover (Golden Cross):
Occurs when the fast MA crosses above the slow MA. Interpreted as a buy signal, indicating a potential uptrend.
Bearish Crossover (Death Cross):
Occurs when the fast MA crosses below the slow MA. Interpreted as a sell signal, indicating a potential downtrend.
Common Variants
Short-term trading
9 EMA
21 EMA
Swing trading
20 SMA
50 SMA
Long-term investing
50 SMA
200 SMA
Pros
Easy to understand and implement
Works well in trending markets
Can be automated for backtesting and execution
Cons
Lagging indicator: MAs are based on past prices, so signals come after the move has started.
Choppy markets = whipsaws: Generates false signals in sideways/range-bound conditions.
May underperform in volatile or mean-reverting environments
Tips for Improvement
Use confirmation tools : e.g., RSI, MACD, volume analysis, price action
Add filters : Trend filter (ADX), volatility filter (ATR), or time filter (session-based)
Combine with price structure : Support/resistance, breakouts, pullbacks
Trading Report Generator from CSVMany people use the Trading Panel. Unfortunately, it doesn't have a Performance Report. However, TradingView has strategies, and they have a Performance Report :-D
What if we combine the first and second? It's easy!
This script is a special strategy that parses transactions in csv format from Paper Trading (and it will also work for other brokers) and “plays” them. As a result, we get a Performance Report for a specific instrument based on our real trades in Paper or another broker.
How to use it :
First, we need to get a CSV file with transactions. To do this, go to the Trading Panel and connect the desired broker. Select the History tab, then the Filled sub-tab, and configure the columns there, leaving only: Side, Qty, Fill Price, Closing Time. After that, open the Export data dialog, select History, and click Export. Open the downloaded CSV file in a regular text editor (Notepad or similar). It will contain a text like this:
Symbol,Side,Qty,Fill Price,Closing Time
FX:EURUSD,Buy,1000,1.0938700000000001,2023-04-05 14:29:23
COINBASE:ETHUSD,Sell,1,1332.05,2023-01-11 17:41:33
CME_MINI:ESH2023,Sell,1,3961.75,2023-01-11 17:30:40
CME_MINI:ESH2023,Buy,1,3956.75,2023-01-11 17:08:53
Next select all the text (Ctrl+A) and copy it to the clipboard.
Now apply the "Trading Report Generator from CSV" strategy to the chart with the desired symbol and TF, open the settings/input dialog, paste the contents of the clipboard into the single text input field of the strategy, and click Ok.
That's it.
In the Strategy Tester, we see a detailed Performance Report based on our real transactions.
P.S. The CSV file may contain transactions for different instruments, for example, you may have transactions for CRYPTO:BTCUSD and NASDAQ:AAPL. To view the report is based on CRYPTO:BTCUSD trades, simply change the symbol on the chart to CRYPTO:BTCUSD. To view the report is based on NASDAQ:AAPL trades, simply change the symbol on the chart to NASDAQ:AAPL. No changes to the strategy are required.
How it works :
At the beginning of the calculation, we parse the csv once, create trade objects (Trade) and sort them in chronological order. Next, on each bar, we check whether we have trades for the time period of the next bar. If there are, we place a limit order for each trade, with limit price == Fill Price of the trade. Here, we assume that if the trade is real, its execution price will be within the bar range, and the Pine strategy engine will execute this order at the specified limit price.
2% Averaging Buy-Sell Strategy📘 Strategy Description: 2% Averaging Buy-Sell Strategy
This strategy is designed to simulate an averaging-down and scaling-out approach based on percentage-based price movements.
Entry Logic (Buy):
Initial buy of 1 lot is triggered at the start of the strategy.
Every time the price drops by 2% from the last executed buy level, the strategy adds 2 more lots.
Exit Logic (Sell):
When the price rises 2% from the last buy level, the strategy sells 2 lots.
Selling continues in batches of 2 lots as long as the upward movement continues and lots are available.
Core Idea:
This is a dynamic averaging system that increases exposure during drawdowns and reduces it during rallies, aiming to capture mean reversion or trend reversals.
Customizable Inputs:
Initial lot size
Additional lot size
Percentage threshold (default 2%)
⚠️ Note: This strategy is for simulation/backtesting purposes. It does not account for slippage, fees, or real-world order execution conditions.
Opening-Range BreakoutNote: Default trading date range looks mediocre. Set date range to "Entire History" to see full effect of the strategy. 50.91% profitable trades, 1.178 profit factor, steady profits and limited drawdown. Total P&L: $154,141.18, Max Drawdown: $18,624.36. High R^2
█ Overview
The Opening-Range Breakout strategy is a mechanical, session‑based day‑trading system designed to capture the initial burst of directional momentum immediately following the market open. It defines a user‑configurable “opening range” window, measures its high and low boundaries, then places breakout stop orders at those levels once the range closes. Built‑in filters on minimum range width, reward‑to‑risk ratios, and optional reversal logic help refine entries and manage risk dynamically.
█ How It Works
Opening‑Range Formation
Between 9:30–10:15 AM ET (configurable), the script tracks the highest high and lowest low to form the day’s opening range box.
On the first bar after the range window closes, the range high (OR_high) and low (OR_low) are “locked in.”
Range‑Width Filter
To avoid false breakouts in low‑volatility mornings, the range must be at least X% of the current price (default 0.35%).
If the measured opening-range width < minimum threshold, no orders are placed that day.
Entry & Order Placement
Long: a stop‑buy order at the opening‑range high.
Short: a stop‑sell order at the opening‑range low.
Only one side can trigger (or both if reverse logic is enabled after a losing trade).
Risk Management
Once triggered, each trade uses an ATR‑style stop-loss defined as a percentage retracement of the range (default 50% of range width).
Profit target is set at a configurable Reward/Risk Ratio (default 1.1×).
Optional: Reverse on Stop‑Loss – if the initial breakout loses, immediately reverse into the opposite side on the same day.
Session Exit
Any open positions are closed at the end of the regular trading day (default 3:45 PM ET window end, with hard flat at session close).
Visual cues are provided via green (range high) and red (range low) step‑line plots directly on the chart, allowing you to see the range box and breakout triggers in real time.
█ Why It Works
Early Momentum Capture: The first 15 – 60 minutes of trading encapsulate overnight news digestion and institutional order flow, creating a well‑defined volatility “range.”
Mechanical Discipline: Clear, rule‑based entries and exits remove emotional guesswork, ensuring consistency.
Volatility Filtering: By requiring a minimum range width, the system avoids choppy, low‑range days where false breakouts are common.
Dynamic Sizing: Stops and targets scale with the opening range, adapting automatically to each day’s volatility environment.
█ How to Use
Set Your Instruments & Timeframe
-Apply to any futures contract on a 1‑ to 5‑minute chart.
-Ensure chart timezone is set to America/New_York.
Configure Inputs
-Opening‑Range Window: e.g. “0930-1015” for a 45‑minute range.
-Min. OR Width (%): e.g. 0.35 for 0.35% of current price.
-Reward/Risk Ratio: e.g. 1.1 for a modest profit target above your stop.
-Max OR Retracement %: e.g. 50 to set stop at 50% of range width.
-One Trade Per Day: toggle to limit to a single breakout.
-Reverse on Stop Loss: toggle to flip direction after a losing breakout.
Monitor the Chart
-Watch the green and red range boundaries form during the session open.
-Orders will automatically submit on the first bar after the range window closes, conditioned on your filters.
Review & Adjust
-Backtest across multiple months to validate performance on your preferred contract.
-Tweak range duration, minimum width, and R/R multiple to fit your risk tolerance and desired win‑rate vs. expectancy balance.
█ Settings Reference
Input Defaults
Opening‑Range Window - Time window to form OR (HHMM-HHMM) - 0930–1015
Regular Trading Day - Full session for EOD flat (HHMM-HHMM) - 0930–1545
Min. OR Width (%) - Minimum OR size as % of close to trigger orders - 0.35
Reward/Risk Ratio - Profit target multiple of stop‑loss distance - 1.1
Max OR Retracement (%) - % of OR width to use as stop‑loss distance - 50
One Trade Per Day - Limit to a single breakout order per day - false
Reverse on Stop Loss - Reverse direction immediately after a losing trade - true
Disclaimer
This strategy description and any accompanying code are provided for educational purposes only and do not constitute financial advice or a solicitation to trade. Futures trading involves substantial risk, including possible loss of capital. Past performance is not indicative of future results. Traders should assess their own risk tolerance and conduct thorough backtesting and forward-testing before committing real capital.
EMA Grid + Martingale Strategy (Long-Only) with CooldownTitle:
EMA Grid + Martingale Strategy (Long-Only) with Cooldown
Short Summary:
A long-only strategy combining EMA trend filters, grid-based entries, optional martingale sizing, and a cooldown feature to manage position timing and exits.
Full Description:
This strategy uses a 4-EMA trend confirmation system to detect bullish momentum, then deploys a grid-style entry method with optional martingale position sizing. It includes a cooldown mechanism to prevent reentry too soon after a completed trade cycle.
How It Works
1. Trend Confirmation: Two EMA groups (fast/slow) determine whether market conditions are bullish.
2. Initial Entry: A new position is entered when both EMA groups confirm an uptrend and no position is currently active.
3. Grid Entries: Additional long entries are placed when price drops by a defined pip distance from the last entry, respecting the maximum number of entries.
4. Martingale Sizing (Optional): Grid orders can increase in size with each level using a customizable multiplier.
5. Weighted-Average Exit: All positions close once price reaches or exceeds the average entry price plus a buffer.
6. Cooldown Timer: After closing a position set, the strategy waits a defined number of bars before opening a new grid.
Key Features
• 4 customizable EMAs for trend confirmation.
• Dynamic grid-style long entries based on pip intervals.
• Optional martingale-style position sizing.
• Weighted-average price exit logic with buffer control.
• Cooldown bar period to limit overtrading.
• Suitable for optimization and backtesting with full control over inputs.
Use Cases
• Designed for trending markets where pullbacks present entry opportunities.
• Helps manage staged entries while avoiding premature reentry.
• Ideal for testing martingale and grid-based strategies with exit precision.
Note: This strategy is for testing and educational purposes only. It does not guarantee profits and is not financial advice.
Minimalist Trend & Risk For 5-Min Timeframe
Of course. Here is a professionally written TradingView description for your indicator, following the specified formatting and incorporating the strategy you outlined.
Minimalist Trend & Risk For 5-Min Timeframe
Overview
This is a clean, on-chart visual tool designed to identify high-probability entries and manage risk, specifically tailored for a 5-minute scalping or day trading strategy. It combines a higher-timeframe trend anchor with a current-timeframe trigger line and a volatility-based stop loss level, keeping your chart uncluttered and your decisions clear.
Visual Components
Trend EMA (50-period, 15-min): This is your main trend guide. The thick, colored line represents the 50 EMA from the 15-minute chart.
Green: Confirmed uptrend.
Red: Confirmed downtrend.
Gray: Neutral or consolidating market.
Price EMA (21-period, 5-min): The thin white line is the 21 EMA based on your current chart (5-minute). This acts as a dynamic trigger line that price must reclaim after a pullback.
Stop Loss Zone (ATR-based): The thin red line provides a suggested stop loss level based on current market volatility (ATR). It automatically appears below price in an uptrend and above price in a downtrend, helping you define your risk on every trade.
How To Use for a Long Entry Strategy
The strategy is to trade pullbacks in the direction of the higher-timeframe trend. This indicator helps you visualize each step of the setup.
1. Identify the Trend: Wait for the main Trend EMA (the thick line) to be green. This confirms you are in an established uptrend on the 15-minute timeframe and should only be looking for long entries.
2. Wait for a Pullback: The core of the strategy is patience. Wait for a 5-minute candlestick to pull back and close below the 15-minute Trend EMA. This confirms a temporary dip within the larger uptrend, offering a better entry price.
3. Spot the Entry Trigger: After the pullback, the entry signal occurs when a 5-minute candlestick closes back above the faster, white Price EMA (21-period). This signals that momentum is returning in the direction of the main trend.
4. Manage Your Risk: Use the red Stop Loss Zone line that appears below your entry as a guide to set your initial stop loss. This helps ensure your risk is managed dynamically based on current volatility.
This indicator simplifies a powerful pullback strategy by plotting all the necessary components directly on your chart, allowing for quick and disciplined trade execution.
The Kyber Cell's – TTM Wave CThe Kyber Cell’s Wave C – TTM Squeeze Macro Bias & Structural Filter
⸻
1. Introduction
Wave C is the strategic compass in the TTM Squeeze Wave system — the final layer that helps you align with the larger trend or macro context. While Wave A delivers momentum bursts and Wave B confirms active trend direction, Wave C filters trades through a broader lens, helping you avoid taking strong intraday setups that go against the dominant structure.
Wave C is designed to act as your macro bias validator — filtering out trades that contradict higher-timeframe flows or major moving average slopes. When all three waves line up, you’re no longer just reacting to signals — you’re trading with intention and structure. When in doubt, zoom out and that is what Wave C gives you.
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2. Core Concept and Calculation
Wave C is built to measure high-level trend bias, either on the current chart timeframe or derived from a higher timeframe (HTF). Its logic is based on one or more of the following structural tools:
• Long-term EMA slope (e.g., 55, 89, or 200 EMA)
• HTF VWAP positioning (price above or below)
• Long-period HMA slope (e.g., HMA 144 or HMA 233)
• Directional bias from HTF TTM Squeeze or MTF trend engine
Unlike Wave A and B, which may fluctuate during normal price swings, Wave C changes more slowly. That’s the point — it gives a “big picture” backdrop against which all lower-level signals should be evaluated. It reduces false positives and helps you wait for trades in the direction of the broader trend.
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3. Visual Output and Color Logic
Wave C uses a simple and deliberate color scheme to communicate macro alignment:
• Green: Bullish macro structure
• Red: Bearish macro structure
• Gray: Neutral, indecisive, or flat macro trend
This muted but firm logic encourages patient, structured trading. The goal isn’t to trigger trades directly from Wave C, but to filter out trades that contradict market posture.
• When Wave C is Green, you ideally want Wave B to be blue and Wave A to turn cyan before going long.
• When Wave C is Red, you look for Wave B to be red and Wave A to turn bright red before shorting.
• If Wave C is Gray, it may signal choppy, indecisive structure — use caution or reduce trade size.
⸻
4. Ideal Use Case
Wave C functions as your global bias filter:
1. Set your directional bias for the session or week.
2. Only take trades that agree with Wave C direction.
3. When all waves align, trade with size and confidence.
4. When Wave C disagrees, wait or downshift your trade plan.
This makes Wave C especially valuable for swing traders, position traders, or intraday traders who want to anchor their entries within a broader trend.
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5. Configuration and Customization
Wave C is built with advanced users in mind, and its configuration allows multiple structural methods:
• EMA Slope Method: Set EMA length and threshold angle
• HTF Source Method: Request HTF data for squeeze trend, VWAP, or Wave B analog
• HMA Trend Filter: Longer-term smoothing to detect sustained directional flow
• Color Preferences: Customize green/red/gray scheme as needed
This flexibility allows you to tailor Wave C to your strategy — whether you’re anchoring to a Daily EMA while scalping the 5-minute chart, or aligning swing entries with the Weekly VWAP.
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6. Alerts and Add-ons
Although Wave C isn’t typically used for alerts, it can be incorporated into confluence-based alert stacks. For example:
• Alert only when Wave C = Green, Wave B = Blue, and Wave A = Rising
• Alert on macro flip (e.g., Green → Red) as a possible regime change
• Alert when macro bias agrees with MTF Squeeze Panel bias
These setups are more advanced but help automate disciplined trade selection.
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7. Disclaimer
This indicator is for educational and research purposes only. It is not trading advice. Wave C is most effective when used in conjunction with Wave A, Wave B, and other structural context. All trades should be executed with proper risk management and backtested methodology.
MACD Liquidity Tracker Strategy [Quant Trading]MACD Liquidity Tracker Strategy
Overview
The MACD Liquidity Tracker Strategy is an enhanced trading system that transforms the traditional MACD indicator into a comprehensive momentum-based strategy with advanced visual signals and risk management. This strategy builds upon the original MACD Liquidity Tracker System indicator by TheNeWSystemLqtyTrckr , converting it into a fully automated trading strategy with improved parameters and additional features.
What Makes This Strategy Original
This strategy significantly enhances the basic MACD approach by introducing:
Four distinct system types for different market conditions and trading styles
Advanced color-coded histogram visualization with four dynamic colors showing momentum strength and direction
Integrated trend filtering using 9 different moving average types
Comprehensive risk management with customizable stop-loss and take-profit levels
Multiple alert systems for entry signals, exits, and trend conditions
Flexible signal display options with customizable entry markers
How It Works
Core MACD Calculation
The strategy uses a fully customizable MACD configuration with traditional default parameters:
Fast MA : 12 periods (customizable, minimum 1, no maximum limit)
Slow MA : 26 periods (customizable, minimum 1, no maximum limit)
Signal Line : 9 periods (customizable, now properly implemented and used)
Cryptocurrency Optimization : The strategy's flexible parameter system allows for significant optimization across different crypto assets. Traditional MACD settings (12/26/9) often generate excessive noise and false signals in volatile crypto markets. By using slower, more smoothed parameters, traders can capture meaningful momentum shifts while filtering out market noise.
Example - DOGE Optimization (45/80/290 settings) :
• Performance : Optimized parameters yielding exceptional backtesting results with 29,800% PnL
• Why it works : DOGE's high volatility and social sentiment-driven price action benefits from heavily smoothed indicators
• Timeframes : Particularly effective on 30-minute and 4-hour charts for swing trading
• Logic : The very slow parameters filter out noise and capture only the most significant trend changes
Other Optimizable Cryptocurrencies : This parameter flexibility makes the strategy highly effective for major altcoins including SUI, SEI, LINK, Solana (SOL) , and many others. Each crypto asset can benefit from custom parameter tuning based on its unique volatility profile and trading characteristics.
Four Trading System Types
1. Normal System (Default)
Long signals : When MACD line is above the signal line
Short signals : When MACD line is below the signal line
Best for : Swing trading and capturing longer-term trends in stable markets
Logic : Traditional MACD crossover approach using the signal line
2. Fast System
Long signals : Bright Blue OR Dark Magenta (transparent) histogram colors
Short signals : Dark Blue (transparent) OR Bright Magenta histogram colors
Best for : Scalping and high-volatility markets (crypto, forex)
Logic : Leverages early momentum shifts based on histogram color changes
3. Safe System
Long signals : Only Bright Blue histogram color (strongest bullish momentum)
Short signals : All other colors (Dark Blue, Bright Magenta, Dark Magenta)
Best for : Risk-averse traders and choppy markets
Logic : Prioritizes only the strongest bullish signals while treating everything else as bearish
4. Crossover System
Long signals : MACD line crosses above signal line
Short signals : MACD line crosses below signal line
Best for : Precise timing entries with traditional MACD methodology
Logic : Pure crossover signals for more precise entry timing
Color-Coded Histogram Logic
The strategy uses four distinct colors to visualize momentum:
🔹 Bright Blue : MACD > 0 and rising (strong bullish momentum)
🔹 Dark Blue (Transparent) : MACD > 0 but falling (weakening bullish momentum)
🔹 Bright Magenta : MACD < 0 and falling (strong bearish momentum)
🔹 Dark Magenta (Transparent) : MACD < 0 but rising (weakening bearish momentum)
Trend Filter Integration
The strategy includes an advanced trend filter using 9 different moving average types:
SMA (Simple Moving Average)
EMA (Exponential Moving Average) - Default
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
LSMA (Least Squares Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
VIDYA (Variable Index Dynamic Average)
Default Settings : 50-period EMA for trend identification
Visual Signal System
Entry Markers : Blue triangles (▲) below candles for long entries, Magenta triangles (▼) above candles for short entries
Candle Coloring : Price candles change color based on active signals (Blue = Long, Magenta = Short)
Signal Text : Optional "Long" or "Short" text inside entry triangles (toggleable)
Trend MA : Gray line plotted on main chart for trend reference
Parameter Optimization Examples
DOGE Trading Success (Optimized Parameters) :
Using 45/80/290 MACD settings with 50-period EMA trend filter has shown exceptional results on DOGE:
Performance : Backtesting results showing 29,800% PnL demonstrate the power of proper parameter optimization
Reasoning : DOGE's meme-driven volatility and social sentiment spikes create significant noise with traditional MACD settings
Solution : Very slow parameters (45/80/290) filter out social media-driven price spikes while capturing only major momentum shifts
Optimal Timeframes : 30-minute and 4-hour charts for swing trading opportunities
Result : Exceptionally clean signals with minimal false entries during DOGE's characteristic pump-and-dump cycles
Multi-Crypto Adaptability :
The same optimization principles apply to other major cryptocurrencies:
SUI : Benefits from smoothed parameters due to newer coin volatility patterns
SEI : Requires adjustment for its unique DeFi-related price movements
LINK : Oracle news events create price spikes that benefit from noise filtering
Solana (SOL) : Network congestion events and ecosystem developments need smoothed detection
General Rule : Higher volatility coins typically benefit from very slow MACD parameters (40-50 / 70-90 / 250-300 ranges)
Key Input Parameters
System Type : Choose between Fast, Normal, Safe, or Crossover (Default: Normal)
MACD Fast MA : 12 periods default (no maximum limit, consider 40-50 for crypto optimization)
MACD Slow MA : 26 periods default (no maximum limit, consider 70-90 for crypto optimization)
MACD Signal MA : 9 periods default (now properly utilized, consider 250-300 for crypto optimization)
Trend MA Type : EMA default (9 options available)
Trend MA Length : 50 periods default (no maximum limit)
Signal Display : Both, Long Only, Short Only, or None
Show Signal Text : True/False toggle for entry marker text
Trading Applications
Recommended Use Cases
Momentum Trading : Capitalize on strong directional moves using the color-coded system
Trend Following : Combine MACD signals with trend MA filter for higher probability trades
Scalping : Use "Fast" system type for quick entries in volatile markets
Swing Trading : Use "Normal" or "Safe" system types for longer-term positions
Cryptocurrency Trading : Optimize parameters for individual crypto assets (e.g., 45/80/290 for DOGE, custom settings for SUI, SEI, LINK, SOL)
Market Suitability
Volatile Markets : Forex, crypto, indices (recommend "Fast" system or smoothed parameters)
Stable Markets : Stocks, ETFs (recommend "Normal" or "Safe" system)
All Timeframes : Effective from 1-minute charts to daily charts
Crypto Optimization : Each major cryptocurrency (DOGE, SUI, SEI, LINK, SOL, etc.) can benefit from custom parameter tuning. Consider slower MACD parameters for noise reduction in volatile crypto markets
Alert System
The strategy provides comprehensive alerts for:
Entry Signals : Long and short entry triangle appearances
Exit Signals : Position exit notifications
Color Changes : Individual histogram color alerts
Trend Conditions : Price above/below trend MA alerts
Strategy Parameters
Default Settings
Initial Capital : $1,000
Position Size : 100% of equity
Commission : 0.1%
Slippage : 3 points
Date Range : January 1, 2018 to December 31, 2069
Risk Management (Optional)
Stop Loss : Disabled by default (customizable percentage-based)
Take Profit : Disabled by default (customizable percentage-based)
Short Trades : Disabled by default (can be enabled)
Important Notes and Limitations
Backtesting Considerations
Uses realistic commission (0.1%) and slippage (3 points)
Default position sizing uses 100% equity - adjust based on risk tolerance
Stop-loss and take-profit are disabled by default to show raw strategy performance
Strategy does not use lookahead bias or future data
Risk Warnings
Past performance does not guarantee future results
MACD-based strategies may produce false signals in ranging markets
Consider combining with additional confluences like support/resistance levels
Test thoroughly on demo accounts before live trading
Adjust position sizing based on your risk management requirements
Technical Limitations
Strategy does not work on non-standard chart types (Heikin Ashi, Renko, etc.)
Signals are based on close prices and may not reflect intraday price action
Multiple rapid signals in volatile conditions may result in overtrading
Credits and Attribution
This strategy is based on the original "MACD Liquidity Tracker System" indicator created by TheNeWSystemLqtyTrckr . This strategy version includes significant enhancements:
Complete strategy implementation with entry/exit logic
Addition of the "Crossover" system type
Proper implementation and utilization of the MACD signal line
Enhanced risk management features
Improved parameter flexibility with no artificial maximum limits
Additional alert systems for comprehensive trade management
The original indicator's core color logic and visual system have been preserved while expanding functionality for automated trading applications.
EMA and Dow Theory Strategies🌐 Strategy Description
📘 Overview
This is a hybrid strategy that combines EMA crossovers, Dow Theory swing logic, and multi-timeframe trend overlays. It is suitable for intraday to short-term trading on any asset class: crypto, forex, stocks, and indices.
The strategy provides precise entry/exit signals, dynamic stop-loss and scale-out, and highly visual trade guidance.
🧠 Key Features
・Dual EMA crossover system (applied to both symbol and external index)
・Dow Theory-based swing high/low detection for trend confirmation
・Visual overlay of higher timeframe swing trend (htfTrend)
・RSI filter to avoid overbought/oversold entries
・Dynamic partial take-profit when trend weakens
・Custom stop-loss (%) control
・Visualized trade PnL labels directly on chart
・Alerts for entry, stop-loss, partial exit
・Gradient background zones for swing zones and trend visualization
・Auto-tracked metrics: APR, drawdown, win rate, equity curve
⚙️ Input Parameters
| Parameter | Description |
| ------------------------- | -------------------------------------------------------- |
| Fast EMA / Slow EMA | Periods for detecting local trend via EMAs |
| Index Fast EMA / Slow EMA | EMAs applied to external reference index |
| StopLoss | Maximum loss threshold in % |
| ScaleOut Threshold | Scale-out percentage when trend changes color |
| RSI Period / Levels | RSI period and overbought/oversold levels |
| Swing Detection Length | Number of bars used to detect swing highs/lows |
| Stats Display Options | Toggle PnL labels and position of statistics table |
🧭 About htfTrend (Higher Timeframe Trend)
The script includes a higher timeframe trend (htfTrend) calculated using Dow Theory (pivot highs/lows).
This trend is only used for visual guidance, not for actual entry conditions.
Why? Strictly filtering trades by higher timeframe often leads to missed opportunities and low frequency.
By keeping htfTrend visual-only, traders can still refer to macro structure but retain trade flexibility.
Use it as a contextual tool, not a constraint.
ストラテジー説明
📘 概要
本ストラテジーは、EMAクロスオーバー、ダウ理論によるスイング判定、**上位足トレンドの視覚表示（htfTrend）**を組み合わせた複合型の短期トレーディング戦略です。
仮想通貨・FX・株式・指数など幅広いアセットに対応し、デイトレード〜スキャルピング用途に適しています。
動的な利確/損切り、視覚的にわかりやすいエントリー/イグジット、統計表示を搭載しています。
🧠 主な機能
・対象銘柄＋外部インデックスのEMAクロスによるトレンド判定
・ダウ理論に基づいたスイング高値・安値検出とトレンド判断
・上位足スイングトレンド（htfTrend）の視覚表示
・RSIフィルターによる過熱・売られすぎの回避
・トレンドの弱まりに応じた部分利確（スケールアウト）
・**損切り閾値（％）**をカスタマイズ可能
・チャート上に損益ラベル表示
・アラート完備（エントリー・決済・部分利確）
・トレンドゾーンを可視化する背景グラデーション
・勝率・ドローダウン・APR・資産増加率などの自動表示
| 設定項目名 | 説明内容 |
| --------------------- | -------------------------- |
| Fast EMA / Slow EMA | 銘柄に対して使用するEMAの期間設定 |
| Index Fast / Slow EMA | 外部インデックスのEMA設定 |
| 損切り（StopLoss） | 損切りラインのしきい値（%で指定） |
| 部分利確しきい値 | トレンド弱化時にスケールアウトする割合（%） |
| RSI期間・水準 | RSI計算期間と、過熱・売られすぎレベル設定 |
| スイング検出期間 | スイング高値・安値の検出に使用するバー数 |
| 統計表示の切り替え | 損益ラベルや統計テーブルの表示／非表示選択 |
🧭 上位足トレンド（htfTrend）について
本スクリプトには、上位足でのスイング高値・安値の更新に基づく**htfTrend（トレンド判定）が含まれています。
これは視覚的な参考情報であり、エントリーやイグジットには直接使用されていません。**
その理由は、上位足を厳密にロジックに組み込むと、トレード機会の損失が増えるためです。
このスクリプトでは、**判断の補助材料として「表示のみに留める」**設計を採用しています。
→ 裁量で「利確を早める」「逆張りを避ける」判断に活用可能です。
NY HIGH LOW BREAKNY HIGH LOW BREAK: A New York Session Breakout Strategy
The "NY HIGH LOW BREAK" indicator is a powerful TradingView script designed to identify and capitalize on breakout opportunities during the New York trading session. This strategy focuses on the initial price action of the New York market open, looking for clear breaches of the high or low established within the first 30 minutes. It's particularly suited for intraday traders who seek to capture momentum-driven moves.
Strategy Logic
The core of the "NY HIGH LOW BREAK" strategy revolves around these key components:
New York Session Opening Range Identification:
The script first identifies the opening range of the New York session. This is defined by the high and low prices established during the first 30 minutes of the New York trading session (from 7:01 AM GMT-4 to 7:31 AM GMT-4).
These crucial levels are then extended forward on the chart as horizontal lines, serving as potential support and resistance zones.
Breakout Signal Generation:
Long Signal: A buy signal is generated when the price breaks above the high of the New York opening range. Specifically, it looks for a candle whose open and close are both above the highLinePrice, and importantly, the previous candle's open was below and close was above the highLinePrice. This indicates a strong upward momentum confirming the breakout.
Short Signal: Conversely, a sell signal is generated when the price breaks below the low of the New York opening range. It looks for a candle whose open and close are both below the lowLinePrice, and the previous candle's open was above and close was below the lowLinePrice. This suggests strong downward momentum confirming the breakdown.
Supertrend Filter (Implicit/Future Enhancement):
While the supertrend and direction variables are present in the code, they are not actively used in the current signal generation logic. This suggests a potential future enhancement where the Supertrend indicator could be incorporated as a trend filter to confirm breakout directions, adding an extra layer of confluence to the signals. For example, only taking long breakouts when Supertrend indicates an uptrend, and short breakouts when Supertrend indicates a downtrend.
Second Candle Confirmation (Possible Future Enhancement):
The close_sec_candle function and openSEC, closeSEC variables indicate an attempt to capture the open and close of a "second candle" (30 minutes after the initial New York open). Currently, closeSEC is used in a specific condition for signal_way but not directly in the primary longSignal or shortSignal logic. This also suggests a potential future refinement where the price action of this second candle could be used for further confirmation or specific entry criteria.
Time-Based Filtering:
Signals are only considered valid within a specific trading window from 8:00 AM GMT-4 to 8:00 AM GMT-4 + 16 * 30 minutes (which is 480 minutes, or 8 hours) on 1-minute and 5-minute timeframes. This ensures that trades are taken during the most active and volatile periods of the New York session, avoiding late-session chop.
The script also highlights the New York session and lunch hours using background colors, providing visual context to the trading day.
Key Features
Automated New York Open Range Detection: The script automatically identifies and plots the high and low of the first 30 minutes of the New York trading session.
Clear Breakout Signals: Visually distinct "BUY" and "SELL" labels appear on the chart when a breakout occurs, making it easy to spot trading opportunities.
Timeframe Adaptability: While optimized for 1-minute and 5-minute timeframes for signal generation, the opening range lines can be displayed on various timeframes.
Customizable Risk-to-Reward (RR): The rr input allows users to define their preferred risk-to-reward ratio for potential trades, although it's not directly implemented in the current signal or trade management logic. This could be used by traders for manual trade management.
Visual Session and Lunch Highlights: The script colors the background to clearly delineate the New York trading session and the lunch break, helping traders understand the market context.
How to Use
Apply the Indicator: Add the "NY HIGH LOW BREAK" indicator to your chart on TradingView.
Select a Relevant Timeframe: For optimal signal generation, use 1-minute or 5-minute timeframes.
Observe the Opening Range: The green and red lines represent the high and low of the first 30 minutes of the New York session.
Look for Breakouts: Wait for price to decisively break above the green line (for a buy) or below the red line (for a sell).
Confirm Signals: The "BUY" or "SELL" labels will appear on the chart when the breakout conditions are met within the active trading window.
Implement Your Risk Management: Use your preferred risk management techniques, including stop-loss and take-profit levels, in conjunction with the signals generated. The rr input can guide your manual risk-to-reward calculations.
Potential Enhancements & Considerations
Supertrend Confirmation: Integrating the supertrend variable to filter signals would significantly enhance the strategy's robustness by aligning trades with the prevailing trend.
Stop-Loss and Take-Profit Automation: The rr input currently serves as a manual guide. Future versions could integrate automated stop-loss and take-profit placement based on this ratio, potentially using ATR for dynamic sizing.
Volume Confirmation: Adding a volume filter to confirm breakouts would ensure that only high-conviction moves are traded.
Backtesting and Optimization: Thorough backtesting across various assets and market conditions is crucial to determine the optimal settings and profitability of this strategy.
Session Times: The current session times are hardcoded. Making these user-definable inputs would allow for greater flexibility across different time zones and trading preferences.
The "NY HIGH LOW BREAK" is a straightforward yet effective strategy for capturing initial New York session momentum. By focusing on clear breakout levels, it aims to provide timely and actionable trading signals for intraday traders.
Pullback Pro Dow Strategy v7 (ADX Filter)
### **Strategy Description (For TradingView)**
#### **Title:** Pullback Pro: Dow Theory & ADX Strategy
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#### **1. Summary**
This strategy is designed to identify and trade pullbacks within an established trend, based on the core principles of Dow Theory. It uses market structure (pivot highs and lows) to determine the trend direction and an Exponential Moving Average (EMA) to pinpoint pullback entry opportunities.
To enhance trade quality and avoid ranging markets, an ADX (Average Directional Index) filter is integrated to ensure that entries are only taken when the trend has sufficient momentum.
---
#### **2. Core Logic: How It Works**
The strategy's logic is broken down into three main steps:
**Step 1: Trend Determination (Dow Theory)**
* The primary trend is identified by analyzing recent pivot points.
* An **Uptrend** is confirmed when the script detects a pattern of higher highs and higher lows (HH/HL).
* A **Downtrend** is confirmed by a pattern of lower highs and lower lows (LH/LL).
* If neither pattern is present, the strategy considers the market to be in a range and will not seek trades.
**Step 2: Entry Signal (Pullback to EMA)**
* Once a clear trend is established, the strategy waits for a price correction.
* **Long Entry:** In a confirmed uptrend, a long position is initiated when the price pulls back and crosses *under* the specified EMA.
* **Short Entry:** In a confirmed downtrend, a short position is initiated when the price rallies and crosses *over* the EMA.
**Step 3: Confirmation & Risk Management**
* **ADX Filter:** To ensure the trend is strong enough to trade, an entry signal is only validated if the ADX value is above a user-defined threshold (e.g., 25). This helps filter out weak signals during choppy or consolidating markets.
* **Stop Loss:** The initial Stop Loss is automatically and logically placed at the last market structure point:
* For long trades, it's placed at the `lastPivotLow`.
* For short trades, it's placed at the `lastPivotHigh`.
* **Take Profit:** Two Take Profit levels are calculated based on user-defined Risk-to-Reward (R:R) ratios. The strategy allows for partial profit-taking at the first target (TP1), moving the remainder of the position to the second target (TP2).
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#### **3. Input Settings Explained**
**① Dow Theory Settings**
* **Pivot Lookback Period:** Determines the sensitivity for detecting pivot highs and lows. A smaller number makes it more sensitive to recent price swings; a larger number focuses on more significant, longer-term pivots.
**② Entry Logic (Pullback)**
* **Pullback EMA Length:** Sets the period for the Exponential Moving Average used to identify pullback entries.
**③ Risk & Exit Management**
* **Take Profit 1 R:R:** Sets the Risk-to-Reward ratio for the first take-profit target.
* **Take Profit 1 (%):** The percentage of the position to be closed when TP1 is hit.
* **Take Profit 2 R:R:** Sets the Risk-to-Reward ratio for the final take-profit target.
**④ Filters**
* **Use ADX Trend Filter:** A master switch to enable or disable the ADX filter.
* **ADX Length:** The lookback period for the ADX calculation.
* **ADX Threshold:** The minimum ADX value required to confirm a trade signal. Trades will only be placed if the ADX is above this level.
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#### **4. Best Practices & Recommendations**
* This is a trend-following system. It is designed to perform best in markets that exhibit clear, sustained trending behavior.
* It may underperform in choppy, sideways, or strongly ranging markets. The ADX filter is designed to help mitigate this, but no filter is perfect.
* **Crucially, you must backtest this strategy thoroughly** on your preferred financial instrument and timeframe before considering any live application.
* Experiment with the `Pivot Lookback Period`, `Pullback EMA Length`, and `ADX Threshold` to optimize performance for a specific market's characteristics.
---
#### **DISCLAIMER**
This script is provided for educational and informational purposes only. It does not constitute financial advice. All trading involves a high level of risk, and past performance is not indicative of future results. You are solely responsible for your own trading decisions. The author assumes no liability for any financial losses you may incur from using this strategy. Always conduct your own research and due diligence.
Multi-Confluence Swing Hunter V1# Multi-Confluence Swing Hunter V1 - Complete Description
Overview
The Multi-Confluence Swing Hunter V1 is a sophisticated low timeframe scalping strategy specifically optimized for MSTR (MicroStrategy) trading. This strategy employs a comprehensive point-based scoring system that combines optimized technical indicators, price action analysis, and reversal pattern recognition to generate precise trading signals on lower timeframes.
Performance Highlight:
In backtesting on MSTR 5-minute charts, this strategy has demonstrated over 200% profit performance, showcasing its effectiveness in capturing rapid price movements and volatility patterns unique to MicroStrategy's trading behavior.
The strategy's parameters have been fine-tuned for MSTR's unique volatility characteristics, though they can be optimized for other high-volatility instruments as well.
## Key Innovation & Originality
This strategy introduces a unique **dual scoring system** approach:
- **Entry Scoring**: Identifies swing bottoms using 13+ different technical criteria
- **Exit Scoring**: Identifies swing tops using inverse criteria for optimal exit timing
Unlike traditional strategies that rely on simple indicator crossovers, this system quantifies market conditions through a weighted scoring mechanism, providing objective, data-driven entry and exit decisions.
## Technical Foundation
### Optimized Indicator Parameters
The strategy utilizes extensively backtested parameters specifically optimized for MSTR's volatility patterns:
**MACD Configuration (3,10,3)**:
- Fast EMA: 3 periods (vs standard 12)
- Slow EMA: 10 periods (vs standard 26)
- Signal Line: 3 periods (vs standard 9)
- **Rationale**: These faster parameters provide earlier signal detection while maintaining reliability, particularly effective for MSTR's rapid price movements and high-frequency volatility
**RSI Configuration (21-period)**:
- Length: 21 periods (vs standard 14)
- Oversold: 30 level
- Extreme Oversold: 25 level
- **Rationale**: The 21-period RSI reduces false signals while still capturing oversold conditions effectively in MSTR's volatile environment
**Parameter Adaptability**: While optimized for MSTR, these parameters can be adjusted for other high-volatility instruments. Faster-moving stocks may benefit from even shorter MACD periods, while less volatile assets might require longer periods for optimal performance.
### Scoring System Methodology
**Entry Score Components (Minimum 13 points required)**:
1. **RSI Signals** (max 5 points):
- RSI < 30: +2 points
- RSI < 25: +2 points
- RSI turning up: +1 point
2. **MACD Signals** (max 8 points):
- MACD below zero: +1 point
- MACD turning up: +2 points
- MACD histogram improving: +2 points
- MACD bullish divergence: +3 points
3. **Price Action** (max 4 points):
- Long lower wick (>50%): +2 points
- Small body (<30%): +1 point
- Bullish close: +1 point
4. **Pattern Recognition** (max 8 points):
- RSI bullish divergence: +4 points
- Quick recovery pattern: +2 points
- Reversal confirmation: +4 points
**Exit Score Components (Minimum 13 points required)**:
Uses inverse criteria to identify swing tops with similar weighting system.
## Risk Management Features
### Position Sizing & Risk Control
- **Single Position Strategy**: 100% equity allocation per trade
- **No Overlapping Positions**: Ensures focused risk management
- **Configurable Risk/Reward**: Default 5:1 ratio optimized for volatile assets
### Stop Loss & Take Profit Logic
- **Dynamic Stop Loss**: Based on recent swing lows with configurable buffer
- **Risk-Based Take Profit**: Calculated using risk/reward ratio
- **Clean Exit Logic**: Prevents conflicting signals
## Default Settings Optimization
### Key Parameters (Optimized for MSTR/Bitcoin-style volatility):
- **Minimum Entry Score**: 13 (ensures high-conviction entries)
- **Minimum Exit Score**: 13 (prevents premature exits)
- **Risk/Reward Ratio**: 5.0 (accounts for volatility)
- **Lower Wick Threshold**: 50% (identifies true hammer patterns)
- **Divergence Lookback**: 8 bars (optimal for swing timeframes)
### Why These Defaults Work for MSTR:
1. **Higher Score Thresholds**: MSTR's volatility requires more confirmation
2. **5:1 Risk/Reward**: Compensates for wider stops needed in volatile markets
3. **Faster MACD**: Captures momentum shifts quickly in fast-moving stocks
4. **21-period RSI**: Reduces noise while maintaining sensitivity
## Visual Features
### Score Display System
- **Green Labels**: Entry scores ≥10 points (below bars)
- **Red Labels**: Exit scores ≥10 points (above bars)
- **Large Triangles**: Actual trade entries/exits
- **Small Triangles**: Reversal pattern confirmations
### Chart Cleanliness
- Indicators plotted in separate panes (MACD, RSI)
- TP/SL levels shown only during active positions
- Clear trade markers distinguish signals from actual trades
## Backtesting Specifications
### Realistic Trading Conditions
- **Commission**: 0.1% per trade
- **Slippage**: 3 points
- **Initial Capital**: $1,000
- **Account Type**: Cash (no margin)
### Sample Size Considerations
- Strategy designed for 100+ trade sample sizes
- Recommended timeframes: 4H, 1D for swing trading
- Optimal for trending/volatile markets
## Strategy Limitations & Considerations
### Market Conditions
- **Best Performance**: Trending markets with clear swings
- **Reduced Effectiveness**: Highly choppy, sideways markets
- **Volatility Dependency**: Optimized for moderate to high volatility assets
### Risk Warnings
- **High Allocation**: 100% position sizing increases risk
- **No Diversification**: Single position strategy
- **Backtesting Limitation**: Past performance doesn't guarantee future results
## Usage Guidelines
### Recommended Assets & Timeframes
- **Primary Target**: MSTR (MicroStrategy) - 5min to 15min timeframes
- **Secondary Targets**: High-volatility stocks (TSLA, NVDA, COIN, etc.)
- **Crypto Markets**: Bitcoin, Ethereum (with parameter adjustments)
- **Timeframe Optimization**: 1min-15min for scalping, 30min-1H for swing scalping
### Timeframe Recommendations
- **Primary Scalping**: 5-minute and 15-minute charts
- **Active Monitoring**: 1-minute for precise entries
- **Swing Scalping**: 30-minute to 1-hour timeframes
- **Avoid**: Sub-1-minute (excessive noise) and above 4-hour (reduces scalping opportunities)
## Technical Requirements
- **Pine Script Version**: v6
- **Overlay**: Yes (plots on price chart)
- **Additional Panes**: MACD and RSI indicators
- **Real-time Compatibility**: Confirmed bar signals only
## Customization Options
All parameters are fully customizable through inputs:
- Indicator lengths and levels
- Scoring thresholds
- Risk management settings
- Visual display preferences
- Date range filtering
## Conclusion
This scalping strategy represents a comprehensive approach to low timeframe trading that combines multiple technical analysis methods into a cohesive, quantified system specifically optimized for MSTR's unique volatility characteristics. The optimized parameters and scoring methodology provide a systematic way to identify high-probability scalping setups while managing risk effectively in fast-moving markets.
The strategy's strength lies in its objective, multi-criteria approach that removes emotional decision-making from scalping while maintaining the flexibility to adapt to different instruments through parameter optimization. While designed for MSTR, the underlying methodology can be fine-tuned for other high-volatility assets across various markets.
**Important Disclaimer**: This strategy is designed for experienced scalpers and is optimized for MSTR trading. The high-frequency nature of scalping involves significant risk. Past performance does not guarantee future results. Always conduct your own analysis, consider your risk tolerance, and be aware of commission/slippage costs that can significantly impact scalping profitability.
