Dskyz (DAFE) AI Adaptive Regime - Beginners VersionDskyz (DAFE) AI Adaptive Regime - Pro: Revolutionizing Trading for All
Introduction
In the fast-paced world of financial markets, traders need tools that can keep up with ever-changing conditions while remaining accessible. The Dskyz (DAFE) AI Adaptive Regime - Pro is a groundbreaking TradingView strategy that delivers advanced, AI-driven trading capabilities to everyday traders. Available on TradingView (TradingView Scripts), this Pine Script strategy combines sophisticated market analysis with user-friendly features, making it a standout choice for both novice and experienced traders.
Core Functionality
The strategy is built to adapt to different market regimes—trending, ranging, volatile, or quiet—using a robust set of technical indicators, including:
Moving Averages (MA): Fast and slow EMAs to detect trend direction.
Average True Range (ATR): For dynamic stop-loss and volatility assessment.
Relative Strength Index (RSI) and MACD: Multi-timeframe confirmation of momentum and trend.
Average Directional Index (ADX): To identify trending markets.
Bollinger Bands: For assessing volatility and range conditions.
Candlestick Patterns: Recognizes patterns like bullish engulfing, hammer, and double bottoms, confirmed by volume spikes.
It generates buy and sell signals based on a scoring system that weighs these indicators, ensuring trades align with the current market environment. The strategy also includes dynamic risk management with ATR-based stops and trailing stops, as well as performance tracking to optimize future trades.
What Sets It Apart
The Dskyz (DAFE) AI Adaptive Regime - Pro distinguishes itself from other TradingView strategies through several unique features, which we compare to common alternatives below:
| Feature | Dskyz (DAFE) | Typical TradingView Strategies|
|---------|-------------|------------------------------------------------------------|
| Regime Detection | Automatically identifies and adapts to **four** market regimes | Often static or limited to trend/range detection |
| Multi‑Timeframe Analysis | Uses higher‑timeframe RSI/MACD for confirmation | Rarely incorporates multi‑timeframe data |
| Pattern Recognition | Detects candlestick patterns **with volume confirmation** | Limited or no pattern recognition |
| Dynamic Risk Management | ATR‑based stops and trailing stops | Often uses fixed stops or basic risk rules |
| Performance Tracking | Adjusts thresholds based on past performance | Typically static parameters |
| Beginner‑Friendly Presets | Aggressive, Conservative, Optimized profiles | Requires manual parameter tuning |
| Visual Cues | Color‑coded backgrounds for regimes | Basic or no visual aids |
The Dskyz strategy’s ability to integrate regime detection, multi-timeframe analysis, and user-friendly presets makes it uniquely versatile and accessible, addressing the needs of everyday traders who want professional-grade tools without the complexity.
-Key Features and Benefits
[Why It’s Ideal for Everyday Traders
⚡The Dskyz (DAFE) AI Adaptive Regime - Pro democratizes advanced trading by offering professional-grade tools in an accessible package. Unlike many TradingView strategies that require deep technical knowledge or fail in changing market conditions, this strategy simplifies complex analysis while maintaining robustness. Its presets and visual aids make it easy for beginners to start, while its adaptive features and performance tracking appeal to advanced traders seeking an edge.
🔄Limitations and Considerations
Market Dependency: Performance varies by market and timeframe. Backtesting is essential to ensure compatibility with your trading style.
Learning Curve: While presets simplify use, understanding regimes and indicators enhances effectiveness.
No Guaranteed Profits: Like all strategies, success depends on market conditions and proper execution. The Reddit discussion highlights skepticism about TradingView strategies’ universal success (Reddit Discussion).
Instrument Specificity: Optimized for futures (e.g., ES, NQ) due to fixed tick values. Test on other instruments like stocks or forex to verify compatibility.
📌Conclusion
The Dskyz (DAFE) AI Adaptive Regime - Pro is a revolutionary TradingView strategy that empowers everyday traders with advanced, AI-driven tools. Its ability to adapt to market regimes, confirm signals across timeframes, and manage risk dynamically. sets it apart from typical strategies. By offering beginner-friendly presets and visual cues, it makes sophisticated trading accessible without sacrificing power. Whether you’re a novice looking to trade smarter or a pro seeking a competitive edge, this strategy is your ticket to mastering the markets. Add it to your chart, backtest it, and join the elite traders leveraging AI to dominate. Trade like a boss today! 🚀
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
-Dskyz
Recherche dans les scripts pour "the strat"
Daily Bollinger Band StrategyOverview of the Daily Bollinger Band Strategy
1. Strategy Overview and Features
This strategy is a tool for backtesting a trading method that uses Bollinger Bands. It is *not* a tool for automated trading.
1-1. Main Display Items
The main chart displays the Bollinger Bands and the 200-day moving average.
It also shows the entry and exit points along with the position size (in units of 100 shares).
1-2. Summary of Trading Rules
For long (buy) strategies, the trade enters when the price crosses above the +1σ line of the Bollinger Bands, aiming to ride an upward trend. The position is exited when the price crosses below the middle band.
For short (sell) strategies, the trade enters when the price crosses below the -1σ line of the Bollinger Bands, aiming to ride a downward trend. The position is exited when the price crosses above the middle band.
1-3. Strategic Enhancements
The strategy uses the slope of the 200-day moving average to determine the trend direction and enter trades accordingly. This improves the win rate and payoff ratio.
Additionally, to reduce the probability of ruin, the risk per trade is limited to 1.0% of capital, and position sizing is adjusted using ATR (a volatility indicator).
2. Trading Rules
2-1. Chart Type
Only daily charts are used.
2-2. Indicators Used
(1) Bollinger Bands** (used for entry and exit signals)
- Period: Fixed at 80 days
- Upper and lower bands: Fixed at ±1σ
(2) Moving Average** (used to determine trend direction)
- Period: Fixed at 200 days
- Trend direction is judged based on whether the difference from the previous day is positive (upward) or negative (downward)
2-3. Buy Rules
Setup:
- Price crosses above the +1σ line from below
- Both the middle band and 200-day moving average are upward sloping
Entry:
- Buy at the next day’s market open using a market order
Exit:
- If the price crosses below the middle band, sell at the next day’s open using a market order
2-4. Sell Rules
Setup:
- Price crosses below the -1σ line from above
- Both the middle band and 200-day moving average are downward sloping
Entry:
- Sell at the next day’s market open using a market order
Exit:
- If the price crosses above the middle band, buy back at the next day’s open using a market order
2-5. Risk Management Rules
- Risk per trade: 1.0% of total capital (acceptable loss = capital × 1.0%)
- Position size: Acceptable loss ÷ 2ATR (rounded down to the nearest unit of 100 shares)
2-6. Other Notes
- No brokerage fees
- No pyramiding
- No partial exits
- No reverse positions (no “stop-and-reverse” trades)
3. Strategy Parameters
The following settings can be specified:
3-1. Period Settings
- Start date: Set the start date for the backtest period
- Stop date: Set the end date for the backtest period
3-2. Display of Trend and Signals
- Show trend: When checked, the background color of the bars is light red for an uptrend and light blue for a downtrend
- Show signal: When checked, entry and exit signals are displayed (note: signals are executed at the next day’s open, so there is a one-day lag in the display)
3-3. Capital Management Settings
- Funds: Capital available for trading (in JPY)
- Risk rate: Specify what percentage of the capital to risk per trade
Settings in the “Properties” tab are not used in this strategy.
4. Backtest Results (Example)
Here are the backtest results conducted by the author:
- Target Stocks: All components of the Nikkei 225
- Test Period: January 4, 2000 – December 30, 2024
- Data Points: 12,886
- Win Rate: 33.45%
- Net Profit: ¥82,132,380
- Payoff Ratio: 2.450
- Expected Value: ¥6,373.8
- Risk Rate: 1.0%
- Probability of Ruin: 0.00%
---
デイリー・ボリンジャーバンド・ストラテジーの概要
1. ストラテジーの概要と特徴
このストラテジーは、ボリンジャーバンドを使ったトレード手法のバックテストを行うツールです。自動売買を行うツールではありません。
1-1. 主な表示項目
メインチャートにボリンジャーバンドと 200日移動平均線を表示します。
また、エントリーと手仕舞いのタイミングと数量（100株単位）も表示されます。
1-2. トレードルールの概要
買い戦略の場合、ボリンジャーバンドの +1σ 超えでエントリーして上昇トレンドに乗り、ミドルバンドを割ったら決済します。
売り戦略の場合、ボリンジャーバンドの -1σ 割りでエントリーして下降トレンドに乗り、ミドルバンドを上抜けたら決済します。
1-3. ストラテジーの工夫点
200日移動平均線の傾きを見てトレンド方向にエントリーをしています。こうして勝率とペイオフレシオの成績を向上しています。
また、破産確率を抑えるために、リスク資金比率を 1.0% にして、ATR（ボラティリティ指標） を使って注文数を調整しています。
2. 売買ルール
2-1. 使用するチャート
日足チャートに限定します
2-2. 使用する指標
(1) ボリンジャーバンド（仕掛けと手仕舞いのシグナルに使用）
期間は80日に固定
上下バンドは ±1σ に固定
(2) 移動平均線（トレンドの方向を見るために使用）
期間は200日に固定
移動平均の値の前日との差がプラスのとき上向き、マイナスのとき下向きと判断
2-3. 買いのルール
セットアップ：ボリンジャーバンドの +1σ を価格が下から上に交差 かつ ミドルバンドと 200日移動平均線が上向き
仕掛け：翌日の寄り付きに成行で買う
手仕舞い：ボリンジャーバンドのミドルバンドを価格が上から下に交差したら、翌日の寄り付きに成行で売る
2-4. 売りのルール
セットアップ：ボリンジャーバンドの -1σ を価格が上から下に交差 かつ ミドルバンドと 200日移動平均線が下向き
仕掛け：翌日の寄り付きに成行で売る
手仕舞い：ボリンジャーバンドのミドルバンドを価格が下から上に交差したら、翌日の寄り付きに成行で買い戻す
2-5. 資金管理のルール
リスク資金比率：資産の 1.0%（許容損失 = 資産 × 1.0%）
注文数：許容損失 ÷ 2ATR（単元株数未満は切り捨て）
2-6. その他
仲介手数料：なし
ピラミッディング：なし
分割決済：なし
ドテン：しない
3. ストラテジーのパラメーター
次の項目が指定できます。
3-1. 期間の設定
Staer date : バックテストの検証期間の開始日を指定します
Stop date : バックテストの検証期間の終了日を指定します
3-2. トレンドとシグナルの表示
Show trend : チェックを入れると、バーの背景色が、トレンドが上昇のときは薄い赤で、下落のときは薄い青で表示されます
Show signal : チェックを入れると、エントリーと手仕舞いのシグナルを表示します（シグナルの出た翌日の寄り付きに売買をするので表示に1日のずれがあります）
3-3. 資金管理用の設定
Funds : トレード用の資金(円)
Risk rate : 許容損失を資金の何%にするかで指定します
「プロパティタブ」で設定する値は、このストラテジーでは有効ではありません。
4. バックテストの結果（例）
作者がバックテストを実施した結果をお知らせします。
対象銘柄：日経225構成銘柄すべて
対象期間：2000年1月4日～2024年12月30日
データ件数：12,886
勝率：33.45%
純利益：82,132,380
ペイオフレシオ：2.450
期待値：6,373.8
リスク資金比率：1.0%
破産確率：0.00%
QuantJazz Turbine Trader BETA v1.17QuantJazz Turbine Trader BETA v1.17 - Strategy Introduction and User Guide
Strategy Introduction
Welcome to the QuantJazz Turbine Trader BETA v1.17, a comprehensive trading strategy designed for TradingView. This strategy is built upon oscillator principles, drawing inspiration from the Turbo Oscillator by RedRox, and incorporates multiple technical analysis concepts including RSI, MFI, Stochastic oscillators, divergence detection, and an optional FRAMA (Fractal Adaptive Moving Average) filter.
The Turbine Trader aims to provide traders with a flexible toolkit for identifying potential entry and exit points in the market. It presents information through a main signal line oscillator, a histogram, and various visual cues like dots, triangles, and divergence lines directly on the indicator panel. The strategy component allows users to define specific conditions based on these visual signals to trigger automated long or short trades within the TradingView environment.
This guide provides an overview of the strategy's components, settings, and usage. Please remember that this is a BETA version (v1.17). While developed with care, it may contain bugs or behave unexpectedly.
LEGAL DISCLAIMER: QuantJazz makes no claims about the fitness or profitability of this tool. Trading involves significant risk, and you may lose all of your invested capital. All trading decisions made using this strategy are solely at the user's discretion and responsibility. Past performance is not indicative of future results. Always conduct thorough backtesting and risk assessment before deploying any trading strategy with real capital.
This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International.
Core Concepts and Visual Elements
The Turbine Trader indicator displays several components in its own panel below the main price chart:
1. Signal Line (Avg & Avg2): This is the primary oscillator. It's a composite indicator derived from RSI, MFI (Money Flow Index), and Stochastic calculations, smoothed using an EMA (Exponential Moving Average).
Avg: The faster smoothed signal line.
Avg2: The slower smoothed signal line.
Color Coding: The space between Avg and Avg2 is filled. The color (Neon Blue/gColor or Neon Purple/rColor) indicates the trend based on the relationship between Avg and Avg2. Blue suggests bullish momentum (Avg > Avg2), while Purple suggests bearish momentum (Avg2 > Avg).
Zero Line Crosses: Crossovers of the Avg line with the zero level can indicate shifts in momentum.
2. Histogram (resMfi): This histogram is based on smoothed and transformed MFI calculations (Fast MFI and Slow MFI).
Color Coding: Bars are colored Neon Blue (histColorUp) when above zero, suggesting bullish pressure, and Neon Purple (histColorDn) when below zero, suggesting bearish pressure. Transparency is applied.
Zero Line Crosses: Crossovers of the histogram with the zero level can signal potential shifts in money flow.
3. Reversal Points (Dots): Dots appear on the Signal Line (specifically on Avg2) when the color changes (i.e., Avg crosses Avg2).
Small Dots: Appear when a reversal occurs while the oscillator is in an "extreme" zone (below -60 for bullish reversals, above +60 for bearish reversals).
Large Dots: Appear when a reversal occurs outside of these extreme zones.
Colors: Blue (gRdColor) for bullish reversals (Avg crossing above Avg2), Purple (rRdColor) for bearish reversals (Avg crossing below Avg2).
4. Take Profit (TP) Signals (Triangles): Small triangles appear above (+120) or below (-120) the zero line.
Bearish Triangle (Down, Purple rTpColor): Suggests a potential exit point for long positions or an entry point for short positions, based on the oscillator losing upward momentum above the 50 level.
Bullish Triangle (Up, Blue gTpColor): Suggests a potential exit point for short positions or an entry point for long positions, based on the oscillator losing downward momentum below the -50 level.
5. Divergence Lines: The strategy automatically detects and draws potential regular and hidden divergences between the price action (highs/lows) and the Signal Line (Avg).
Regular Bullish Divergence (White bullDivColor line, ⊚︎ label): Price makes a lower low, but the oscillator makes a higher low. Suggests potential bottoming.
Regular Bearish Divergence (White bearDivColor line, ⊚︎ label): Price makes a higher high, but the oscillator makes a lower high. Suggests potential topping.
Hidden Bullish Divergence (bullHidDivColor line, ⊚︎ label): Price makes a higher low, but the oscillator makes a lower low. Suggests potential continuation of an uptrend.
Hidden Bearish Divergence (bearHidDivColor line, ⊚︎ label): Price makes a lower high, but the oscillator makes a higher high. Suggests potential continuation of a downtrend.
Delete Broken Divergence Lines: If enabled, newer divergence lines originating from a similar point will replace older ones.
6. Status Line: A visual bar at the top (95 to 105) and bottom (-95 to -105) of the indicator panel. Its color intensity reflects the confluence of signals:
Score Calculation: +1 if Avg > Avg2, +1 if Avg > 0, +1 if Histogram > 0.
Top Bar (Bullish): Bright Blue (gStatColor) if score is 3, Faded Blue if score is 2, Black otherwise.
Bottom Bar (Bearish): Bright Purple (rStatColor) if score is 0, Faded Purple if score is 1, Black otherwise.
Strategy Settings Explained
The strategy's behavior is controlled via the settings panel (gear icon).
1. Date Range:
Start Date, End Date: Define the period for backtesting. Trades will only occur within this range.
2. Optional Webhook Configuration: (For Automation)
3C Email Token, 3C Bot ID: Enter your 3Commas API credentials if you plan to automate trading using webhooks. The strategy generates JSON alert messages compatible with 3Commas. You can go ahead and just leave the text field as defaulted, "TOKEN HERE" / "BOT ID HERE" if not using any bot automations at this time. You can always come back later and automate it. More info can be made available from QuantJazz should you need automation assistance with custom indicators and trading strategies.
3. 🚀 Signal Line:
Turn On/Off: Show or hide the main signal lines (Avg, Avg2).
gColor, rColor: Set the colors for bullish and bearish signal line states.
Length (RSI): The lookback period for the internal RSI calculation. Default is 2.
Smooth (EMA): The smoothing period for the EMAs applied to the composite signal. Default is 9.
RSI Source: The price source used for RSI calculation (default: close).
4. 📊 Histogram:
Turn On/Off: Show or hide the histogram.
histColorUp, histColorDn: Set the colors for positive and negative histogram bars.
Length (MFI): The base lookback period for MFI calculations. Default is 5. Fast and Slow MFI lengths are derived from this.
Smooth: Smoothing period for the final histogram output. Default is 1 (minimal smoothing).
5.💡 Other:
Show Divergence Line: Toggle visibility of regular divergence lines.
bullDivColor, bearDivColor: Colors for regular divergence lines.
Show Hidden Divergence: Toggle visibility of hidden divergence lines.
bullHidDivColor, bearHidDivColor: Colors for hidden divergence lines.
Show Status Line: Toggle visibility of the top/bottom status bars.
gStatColor, rStatColor: Colors for the status line bars.
Show TP Signal: Toggle visibility of the TP triangles.
gTpColor, rTpColor: Colors for the TP triangles.
Show Reversal points: Toggle visibility of the small/large dots on the signal line.
gRdColor, rRdColor: Colors for the reversal dots.
Delete Broken Divergence Lines: Enable/disable automatic cleanup of older divergence lines.
6. ⚙️ Strategy Inputs: (CRITICAL for Trade Logic)
This section defines which visual signals trigger trades. Each signal (Small/Large Dots, TP Triangles, Bright Bars, Signal/Histogram Crosses, Signal/Histogram Max/Min, Divergences) has a dropdown menu:
Long: This signal can trigger a long entry.
Short: This signal can trigger a short entry.
Disabled: This signal will not trigger any entry.
Must Be True Checkbox: If checked for a specific signal, that signal's condition must be met for any trade (long or short, depending on the dropdown selection for that signal) to be considered. Multiple "Must Be True" conditions act as AND logic – all must be true simultaneously.
How it Works:
The strategy first checks if all conditions marked as "Must Be True" (for the relevant trade direction - long or short) are met.
If all "Must Be True" conditions are met, it then checks if at least one of the conditions not marked as "Must Be True" (and set to "Long" or "Short" respectively) is also met.
If both steps pass, and other filters (like Date Range, FRAMA) allow, an entry order is placed.
Example: If "Large Bullish Dot" is set to "Long" and "Must Be True" is checked, AND "Bullish Divergence" is set to "Long" but "Must Be True" is not checked: A long entry requires BOTH the Large Bullish Dot AND the Bullish Divergence to occur simultaneously. If "Large Bullish Dot" was "Long" but not "Must Be True", then EITHER a Large Bullish Dot OR a Bullish Divergence could trigger a long entry (assuming no other "Must Be True" conditions are active).
Note: By default, the strategy is configured for long-only trades (strategy.risk.allow_entry_in(strategy.direction.long)). To enable short trades, you would need to comment out or remove this line in the Pine Script code and configure the "Strategy Inputs" accordingly.
7. 💰 Take Profit Settings:
Take Profit 1/2/3 (%): The percentage above the entry price (for longs) or below (for shorts) where each TP level is set. (e.g., 1.0 means 1% profit).
TP1/2/3 Percentage: The percentage of the currently open position to close when the corresponding TP level is hit. The percentages should ideally sum to 100% if you intend to close the entire position across the TPs.
Trailing Stop (%): The percentage below the highest high (for longs) or above the lowest low (for shorts) reached after the activation threshold, where the stop loss will trail.
Trailing Stop Activation (%): The minimum profit percentage the trade must reach before the trailing stop becomes active.
Re-entry Delay (Bars): The minimum number of bars to wait after a TP is hit before considering a re-entry. Default is 1 (allows immediate re-entry on the next bar if conditions met).
Re-entry Price Offset (%): The percentage the price must move beyond the previous TP level before a re-entry is allowed. This prevents immediate re-entry if the price hovers around the TP level.
8. 📈 FRAMA Filter: (Optional Trend Filter)
Use FRAMA Filter: Enable or disable the filter.
FRAMA Source, FRAMA Period, FRAMA Fast MA, FRAMA Slow MA: Parameters for the FRAMA calculation. Defaults provided are common starting points.
FRAMA Filter Type:
FRAMA > previous bars: Allows trades only if FRAMA is significantly above its recent average (defined by FRAMA Percentage and FRAMA Lookback). Typically used to confirm strong upward trends for longs.
FRAMA < price: Allows trades only if FRAMA is below the current price (framaSource). Can act as a baseline trend filter.
FRAMA Percentage (X), FRAMA Lookback (Y): Used only for the FRAMA > previous bars filter type.
How it Affects Trades: If Use FRAMA Filter is enabled:
Long entries require the FRAMA filter condition to be true.
Short entries require the FRAMA filter condition to be false (as currently coded, this acts as an inverse filter for shorts if enabled).
How to Use the Strategy
1. Apply to Chart: Open your desired chart on TradingView. Click "Indicators", find "QuantJazz Turbine Trader BETA v1.17" (you might need to add it via Invite-only scripts or if published publicly), and add it to your chart. The oscillator appears below the price chart, and the strategy tester panel opens at the bottom.
2. Configure Strategy Properties: In the Pine Script code itself (or potentially via the UI if supported), adjust the strategy() function parameters like initial_capital, default_qty_value, commission_value, slippage, etc., to match your account, broker fees, and risk settings. The user preferences provided (e.g., 1000 initial capital, 0.1% commission) are examples. Remember use_bar_magnifier is false by default in v1.17.
3. Configure Inputs (Settings Panel):
Set the Date Range for backtesting.
Crucially, configure the ⚙️ Strategy Inputs. Decide which signals should trigger entries and whether they are mandatory ("Must Be True"). Start simply, perhaps enabling only one or two signals initially, and test thoroughly. Remember the default long-only setting unless you modify the code.
Set up your 💰 Take Profit Settings, including TP levels, position size percentages for each TP, and the trailing stop parameters. Decide if you want to use the re-entry feature.
Decide whether to use the 📈 FRAMA Filter and configure its parameters if enabled.
Adjust visual elements (🚀 Signal Line, 📊 Histogram, 💡 Other) as needed for clarity.
4. Backtest: Use the Strategy Tester panel in TradingView. Analyze the performance metrics (Net Profit, Max Drawdown, Profit Factor, Win Rate, Trade List) across different assets, timeframes, and setting configurations. Pay close attention to how different "Strategy Inputs" combinations perform.
5. Refine: Based on backtesting results, adjust the input settings, TP/SL strategy, and signal combinations to optimize performance for your chosen market and timeframe, while being mindful of overfitting.
6. Automation (Optional): If using 3Commas or a similar platform:
Enter your 3C Email Token and 3C Bot ID in the settings.
Create alerts in TradingView (right-click on the chart or use the Alert panel).
Set the Condition to "QuantJazz Turbine Trader BETA v1.17".
In the "Message" box, paste the corresponding placeholder, which will pass the message in JSON from our custom code to TradingView to pass through your webhook: {{strategy.order.alert_message}}.
In the next tab, configure the Webhook URL provided by your automation platform. Put a Whale sound, while you're at it! 🐳
When an alert triggers, TradingView will send the pre-formatted JSON message from the strategy code to your webhook URL.
Final Notes
The QuantJazz Turbine Trader BETA v1.17 offers a wide range of customizable signals and strategy logic. Its effectiveness heavily depends on proper configuration and thorough backtesting specific to the traded asset and timeframe. Start with the default settings, understand each component, and methodically test different combinations of signals and parameters. Remember the inherent risks of trading and never invest capital you cannot afford to lose.
Multi-Timeframe Parabolic SAR Strategy ver 1.0Multi-Timeframe Parabolic SAR Strategy (MTF PSAR) - Enhanced Trend Trading
This strategy leverages the power of the Parabolic SAR (Stop and Reverse) indicator across multiple timeframes to provide robust trend identification, precise entry/exit signals, and dynamic trailing stop management. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trading accuracy, reduce risk, and capture more significant market moves.
Key Features:
Dual Timeframe Analysis: Simultaneously analyzes the Parabolic SAR on the current chart and a higher timeframe (e.g., Daily PSAR on a 1-hour chart). This allows you to align your trades with the dominant trend and filter out noise from lower timeframes.
Configurable PSAR: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values to optimize sensitivity for your trading style and the asset's volatility.
Independent Timeframe Control: Choose to display and trade based on either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the most relevant information for your analysis.
Clear Visual Signals: Distinct colors for the current and higher timeframe PSAR dots provide a clear visual representation of potential entry and exit points.
Multiple Entry Strategies: The strategy offers flexible entry conditions, allowing you to trade based on:
Confirmation: Both current and higher timeframe PSAR signals agree and the current timeframe PSAR has just flipped direction. (Most conservative)
Current Timeframe Only: Trades based solely on the current timeframe PSAR, ideal for when the higher timeframe is less relevant or disabled.
Higher Timeframe Only: Trades based solely on the higher timeframe PSAR.
Dynamic Trailing Stop (PSAR-Based): Implements a trailing stop-loss based on the current timeframe's Parabolic SAR. This helps protect profits by automatically adjusting the stop-loss as the price moves in your favor. Exits are triggered when either the current or HTF PSAR flips.
No Repainting: Uses lookahead=barmerge.lookahead_off in the security() function to ensure that the higher timeframe data is accessed without any data leakage, preventing repainting issues.
Fully Configurable: All parameters (PSAR settings, higher timeframe, visibility, colors) are adjustable through the strategy's settings panel, allowing for extensive customization and optimization.
Suitable for Various Trading Styles: Applicable to swing trading, day trading, and trend-following strategies across various markets (stocks, forex, cryptocurrencies, etc.).
How it Works:
PSAR Calculation: The strategy calculates the standard Parabolic SAR for both the current chart's timeframe and the selected higher timeframe.
Trend Identification: The direction of the PSAR (dots below price = uptrend, dots above price = downtrend) determines the current trend for each timeframe.
Entry Signals: The strategy generates buy/sell signals based on the chosen entry strategy (Confirmation, Current Timeframe Only, or Higher Timeframe Only). The Confirmation strategy offers the highest probability signals by requiring agreement between both timeframes.
Trailing Stop Exit: Once a position is entered, the strategy uses the current timeframe PSAR as a dynamic trailing stop. The stop-loss is automatically adjusted as the PSAR dots move, helping to lock in profits and limit losses. The strategy exits when either the Current or HTF PSAR changes direction.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to evaluate its performance and optimize the settings for different assets and timeframes.
Example Use Cases:
Trend Confirmation: A trader on a 1-hour chart observes a bullish PSAR flip on the current timeframe. They check the MTF PSAR strategy and see that the Daily PSAR is also bullish, confirming the strength of the uptrend and providing a high-probability long entry signal.
Filtering Noise: A trader on a 5-minute chart wants to avoid whipsaws caused by short-term price fluctuations. They use the strategy with a 1-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and uses the current timeframe PSAR as a trailing stop. As the price rises, the PSAR dots move upwards, automatically raising the stop-loss and protecting profits. The trade is exited when the current (or HTF) PSAR flips to bearish.
Disclaimer:
The Parabolic SAR is a lagging indicator and can produce false signals, particularly in ranging or choppy markets. This strategy is intended for educational and informational purposes only and should not be considered financial advice. It is essential to backtest and optimize the strategy thoroughly, use it in conjunction with other technical analysis tools, and implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Always conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Divergence IQ [TradingIQ]Hello Traders!
Introducing "Divergence IQ"
Divergence IQ lets traders identify divergences between price action and almost ANY TradingView technical indicator. This tool is designed to help you spot potential trend reversals and continuation patterns with a range of configurable features.
Features
Divergence Detection
Detects both regular and hidden divergences for bullish and bearish setups by comparing price movements with changes in the indicator.
Offers two detection methods: one based on classic pivot point analysis and another that provides immediate divergence signals.
Option to use closing prices for divergence detection, allowing you to choose the data that best fits your strategy.
Normalization Options:
Includes multiple normalization techniques such as robust scaling, rolling Z-score, rolling min-max, or no normalization at all.
Adjustable normalization window lets you customize the indicator to suit various market conditions.
Option to display the normalized indicator on the chart for clearer visual comparison.
Allows traders to take indicators that aren't oscillators, and convert them into an oscillator - allowing for better divergence detection.
Simulated Trade Management:
Integrates simulated trade entries and exits based on divergence signals to demonstrate potential trading outcomes.
Customizable exit strategies with options for ATR-based or percentage-based stop loss and profit target settings.
Automatically calculates key trade metrics such as profit percentage, win rate, profit factor, and total trade count.
Visual Enhancements and On-Chart Displays:
Color-coded signals differentiate between bullish, bearish, hidden bullish, and hidden bearish divergence setups.
On-chart labels, lines, and gradient flow visualizations clearly mark divergence signals, entry points, and exit levels.
Configurable settings let you choose whether to display divergence signals on the price chart or in a separate pane.
Performance Metrics Table:
A performance table dynamically displays important statistics like profit, win rate, profit factor, and number of trades.
This feature offers an at-a-glance assessment of how the divergence-based strategy is performing.
The image above shows Divergence IQ successfully identifying and trading a bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a bearish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bearish divergence between an indicator and price action!
The performance table is designed to provide a clear summary of simulated trade results based on divergence setups. You can easily review key metrics to assess the strategy’s effectiveness over different time periods.
Customization and Adaptability
Divergence IQ offers a wide range of configurable settings to tailor the indicator to your personal trading approach. You can adjust the lookback and lookahead periods for pivot detection, select your preferred method for normalization, and modify trade exit parameters to manage risk according to your strategy. The tool’s clear visual elements and comprehensive performance metrics make it a useful addition to your technical analysis toolbox.
The image above shows Divergence IQ identifying divergences between price action and OBV with no normalization technique applied.
While traders can look for divergences between OBV and price, OBV doesn't naturally behave like an oscillator, with no definable upper and lower threshold, OBV can infinitely increase or decrease.
With Divergence IQ's ability to normalize any indicator, traders can normalize non-oscillator technical indicators such as OBV, CVD, MACD, or even a moving average.
In the image above, the "Robust Scaling" normalization technique is selected. Consequently, the output of OBV has changed and is now behaving similar to an oscillator-like technical indicator. This makes spotting divergences between the indicator and price easier and more appropriate.
The three normalization techniques included will change the indicator's final output to be more compatible with divergence detection.
This feature can be used with almost any technical indicator.
Stop Type
Traders can select between ATR based profit targets and stop losses, or percentage based profit targets and stop losses.
The image above shows options for the feature.
Divergence Detection Method
A natural pitfall of divergence trading is that it generally takes several bars to "confirm" a divergence. This makes trading the divergence complicated, because the entry at time of the divergence might look great; however, the divergence wasn't actually signaled until several bars later.
To circumvent this issue, Divergence IQ offers two divergence detection mechanisms.
Pivot Detection
Pivot detection mode is the same as almost every divergence indicator on TradingView. The Pivots High Low indicator is used to detect market/indicator highs and lows and, consequently, divergences.
This method generally finds the "best looking" divergences, but will always take additional time to confirm the divergence.
Immediate Detection
Immediate detection mode attempts to reduce lag between the divergence and its confirmation to as little as possible while avoiding repainting.
Immediate detection mode still uses the Pivots Detection model to find the first high/low of a divergence. However, the most recent high/low does not utilize the Pivot Detection model, and instead immediately looks for a divergence between price and an indicator.
Immediate Detection Mode will always signal a divergence one bar after it's occurred, and traders can set alerts in this mode to be alerted as soon as the divergence occurs.
TradingView Backtester Integration
Divergence IQ is fully compatible with the TradingView backtester!
Divergence IQ isn’t designed to be a “profitable strategy” for users to trade. Instead, the intention of including the backtester is to let users backtest divergence-based trading strategies between the asset on their chart and almost any technical indicator, and to see if divergences have any predictive utility in that market.
So while the backtester is available in Divergence IQ, it’s for users to personally figure out if they should consider a divergence an actionable insight, and not a solicitation that Divergence IQ is a profitable trading strategy. Divergence IQ should be thought of as a Divergence backtesting toolkit, not a full-feature trading strategy.
Strategy Properties Used For Backtest
Initial Capital: $1000 - a realistic amount of starting capital that will resonate with many traders
Amount Per Trade: 5% of equity - a realistic amount of capital to invest relative to portfolio size
Commission: 0.02% - a conservative amount of commission to pay for trade that is standard in crypto trading, and very high for other markets.
Slippage: 1 tick - appropriate for liquid markets, but must be increased in markets with low activity.
Once more, the backtester is meant for traders to personally figure out if divergences are actionable trading signals on the market they wish to trade with the indicator they wish to use.
And that's all!
If you have any cool features you think can benefit Divergence IQ - please feel free to share them!
Thank you so much TradingView community!
[3Commas] Turtle StrategyTurtle Strategy
🔷 What it does: This indicator implements a modernized version of the Turtle Trading Strategy, designed for trend-following and automated trading with webhook integration. It identifies breakout opportunities using Donchian channels, providing entry and exit signals.
Channel 1: Detects short-term breakouts using the highest highs and lowest lows over a set period (default 20).
Channel 2: Acts as a confirmation filter by applying an offset to the same period, reducing false signals.
Exit Channel: Functions as a dynamic stop-loss (wait for candle close), adjusting based on market structure (default 10 periods).
Additionally, traders can enable a fixed Take Profit level, ensuring a systematic approach to profit-taking.
🔷 Who is it for:
Trend Traders: Those looking to capture long-term market moves.
Bot Users: Traders seeking to automate entries and exits with bot integration.
Rule-Based Traders: Operators who prefer a structured, systematic trading approach.
🔷 How does it work: The strategy generates buy and sell signals using a dual-channel confirmation system.
Long Entry: A buy signal is generated when the close price crosses above the previous high of Channel 1 and is confirmed by Channel 2.
Short Entry: A sell signal occurs when the close price falls below the previous low of Channel 1, with confirmation from Channel 2.
Exit Management: The Exit Channel acts as a trailing stop, dynamically adjusting to price movements. To exit the trade, wait for a full bar close.
Optional Take Profit (%): Closes trades at a predefined %.
🔷 Why it’s unique:
Modern Adaptation: Updates the classic Turtle Trading Strategy, with the possibility of using a second channel with an offset to filter the signals.
Dynamic Risk Management: Utilizes a trailing Exit Channel to help protect gains as trades move favorably.
Bot Integration: Automates trade execution through direct JSON signal communication with your DCA Bots.
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Best suited for trending markets; higher timeframes (e.g., H4, D1) are recommended to minimize noise.
Sideways Markets: In choppy conditions, breakouts may lead to false signals—consider using additional filters.
Backtesting & Demo Testing: It is crucial to thoroughly backtest the strategy and run it on a demo account before risking real capital.
Parameter Adjustments: Ensure that commissions, slippage, and position sizes are set accurately to reflect real trading conditions.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:ETHUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
Period Channel 1: 20.
Period Channel 2: 20.
Period Channel 2 Offset: 20.
Period Exit: 10.
Take Profit %: Disable.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +516.87 USDT (+5.17%).
Max Drawdown: -100.28 USDT (-0.95%).
Total Closed Trades: 281.
Percent Profitable: 40.21%.
Profit Factor: 1.704.
Average Trade: +1.84 USDT (+1.80%).
Average # Bars in Trades: 29.
🔷 How to Use It:
🔸 Adjust Settings:
Select your asset and timeframe suited for trend trading.
Adjust the periods for Channel 1, Channel 2, and the Exit Channel to align with the asset’s historical behavior. You can visualize these channels by going to the Style tab and enabling them.
For example, if you set Channel 2 to 40 with an offset of 40, signals will take longer to appear but will aim for a more defined trend.
Experiment with different values, a possible exit configuration is using 20 as well. Compare the results and adjust accordingly.
Enable the Take Profit (%) option if needed.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable the option to receive long or short signals (Entry | TP | SL), copy and paste the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only".
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
Period Channel 1: Period of highs and lows to trigger signals
Period Channel 2: Period of highs and lows to filter signals
Offset: Move Channel 2 to the right x bars to try to filter out the favorable signals.
Period Exit: It is the period of the Donchian channel that is used as trailing for the exits.
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Check Messages: Enable this option to review the messages that will be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit: Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
---
### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
---
### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
---
### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
---
### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
---
### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
---
### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
---
### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
XAU-USD - OANDA - Updated Jan 2025 - by PB ver 5Script Title: XAU-USD - OANDA - Updated Jan 2025 - by PB ver 5
Description:
This strategy is designed for trading XAU/USD (Gold) on the OANDA platform, optimized with a session-based filter and Renko bar indicators for enhanced price action analysis. The script utilizes trailing stop loss functionality to manage risk effectively and allows flexibility for both long and short trades.
Key Features:
Date Filter: This strategy includes a time filter to backtest the performance from January 1st, 2025 to December 31st, 2025. Users can enable or disable the filter based on their preference.
Session Filter: Customizable session inputs allow the user to define the active trading session using a time range (default is 09:20-15:16) and the days of the week (default is all days, 1-7). The strategy will only enter trades during the active session, ensuring more controlled and focused trading.
Renko Bar Strategy: This strategy uses Renko charts, a popular price action tool, to detect buy and sell signals based on the crossover of Renko close and open prices. Users can adjust the Renko block size and the Renko value used for detecting price action shifts.
Trailing Stops: The script applies a trailing stop loss mechanism for both long and short trades. The trailing stop is dynamically updated to follow the market as prices move in favor of the trade. It uses a 5000-point trailing stop (adjustable by the user).
Flexible Trade Settings: Users can enable or disable long and short positions through simple toggle switches. The strategy allows for full control over trade entry and exit.
How It Works:
Long Trades: A long position is entered when the Renko close crosses above the Renko open. The position will be exited using a trailing stop, which follows the price in the market.
Short Trades: A short position is entered when the Renko close crosses below the Renko open. The position will also exit using a trailing stop.
The strategy will automatically close positions if the session ends or if the user manually exits the trades.
Customization Options:
Backtest Date Range: Set the start and end dates to backtest the strategy over a specific time period.
Session and Days: Adjust the session time and which days of the week the strategy is active.
Renko Block Size: Customize the Renko block size for finer control over price action signals.
Trailing Stop Distance: Adjust the trailing stop loss to your preferred risk levels.
Limitations and Considerations:
Renko Charting: Renko charts may not suit every trading style, as they are based on price movement rather than time. This strategy is designed for traders who prefer this style of charting.
Backtest Results: Always review the strategy's backtest results with realistic parameters. The strategy uses historical data, and past performance is not indicative of future results. Be aware of slippage and commission costs in real-world trading scenarios.
Manual Intervention: Users should monitor active trades and intervene manually if required.
Ideal Usage:
This strategy is suited for traders looking to use price action-based strategies with Renko charts for XAU/USD on the OANDA platform.
Ideal for those who want to automate their entry and exit points with trailing stop mechanisms while having control over the session time and backtesting period.
Disclaimer:
Past performance does not guarantee future results. Always use caution when using trading strategies and adjust parameters based on market conditions. The strategy is provided for educational purposes and should be tested on paper before live trading.
[3Commas] Alligator StrategyThe Alligator Strategy
🔷 What it does: This script implements the Alligator Strategy, a trend-following method created by Bill Williams. It uses three customizable moving averages (SMMAs or RMAs) "Jaws," "Teeth," and "Lips" to identify market trends and potential trade opportunities. Additionally, it includes built-in stop-loss and take-profit options for enhanced risk management.
🔷 Who is it for:
Trend Traders: Those who prefer trading in markets with clear directional movement.
Advanced Users: Traders who require customizable tools and dynamic risk management features.
Beginners: Accessible to those new to trading, thanks to its intuitive visual representation of trends and pre-configured settings.
Bot Users: Supports direct signal integration for bot automation, including entries, take-profits, and stop-losses.
🔷 How does it work: The Alligator Jaws, Teeth, and Lips are smoothed moving averages (SMA, EMA, RMA, or WMA) calculated based on the selected source price ( hl2 = (high+low)/2 by default). Their lengths and offsets are customizable:
Jaws: Length 21 , offset 13.
Teeth: Length 13, offset 8.
Lips: Length 8 , offset 5.
When the lines align and spread apart (e.g., Lips > Teeth > Jaws for an uptrend), the strategy identifies a trending market.
Entry Conditions:
Long Trades: Triggered when Close > Lips > Teeth > Jaws.
Short Trades: Triggered when Close < Lips < Teeth < Jaws.
🔷 Why it’s unique:
Customization: Flexible settings for moving average types and lengths to adapt to different market conditions and strategy tester configurations.
Built-in Filters: Trend filters that can reduce false signals in certain scenarios, making it more reliable for trending markets.
Take Profit and Stop Loss:
Configurable as either percentage-based or dynamic.
Stop-loss levels adjust dynamically using the Alligator lines.
Fast exit logic moves the stop-loss closer to the price when trades are in profit.
3Commas Bot Compatibility: Designed for automated trading, allowing traders to configure and execute the strategy seamlessly.
🔷 Considerations Before Using the Indicator
🔸Why the Forward Offset: By shifting the averages forward, the Alligator helps traders focus on established trends while filtering out short-term market noise.
The standard configurations of 13-8, 8-5, and 5-3 were selected based on Bill Williams’ studies of market behavior. However, these values can be adjusted to suit different market conditions:
Volatile Markets: Faster settings (e.g., 10-6, 6-4, 3-2) may provide earlier signals.
Less Volatile Markets: Slower settings (e.g., 21-13, 13-8, 8-5) can help avoid noise and reduce false signals.
🔸Best Timeframes to Use: The Alligator can be applied across all timeframes, but certain timeframes offer better reliability.
Higher Timeframes (H4, D1, W1): Ideal for identifying significant trends and for swing or position trading.
Lower Timeframes: Not recommended due to increased noise but may work for scalping with additional confirmation tools.
🔸Disadvantages of the Alligator Strategy:
Exhausted Entry Levels: High buying levels or low selling levels can lead to momentum exhaustion and potential pullbacks.
False Signals in Ranges: Consolidating markets can produce unreliable signals.
Lagging Indicator: As it is based on moving averages, it may delay reacting to sudden price changes.
🔸Advantages of the Alligator Strategy:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Forward shifts and smoothed averages help filter out short-term price fluctuations.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸Important Considerations:
While the Alligator Strategy provides a systematic way to analyze markets, it does not guarantee successful outcomes. Results in trading depend on multiple factors, including market conditions, trader discipline, and risk management. Past performance of the strategy does not ensure future success, and traders should always approach the market with caution.
Risk Management: Define stop-loss levels, position size, and profit targets before entering any trade. Be prepared for the possibility of losses and ensure that your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 1D (Daily Timeframe).
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
Alligator: Source hl2 | Calculation RMA | Jaw 21-13, Teeth 13-8, Lips 8-5.
Strategy: Long & Short.
Max Stop Loss per Trade: 10% of Trade Size.
Exit trades on opposite signal: Enable.
Alligator Stop Loss: Enable.
Alligator Fast Exit: Enable.
🔷 STRATEGY RESULTS
⚠️ Remember, past results do not guarantee future performance.
Net Profit: +355.68 USDT (+3.56%).
Total Closed Trades: 103.
Percent Profitable: 47.57%.
Profit Factor: 1.927.
Max Drawdown: -57.99 USDT (-0.56%).
Average Trade: +3.45 USDT (+3.41%).
Average # Bars in Trades: 16.
🔷 HOW TO USE
🔸Adjust the Alligator Settings:
The default values generally work well: Source hl2 | Calculation RMA | Jaw 21-13, Teeth 13-8, Lips 8-5. However, if you want to use it on timeframes smaller than 4H (4 hours), consider increasing the values to better filter market noise.
Please review the "Indicator Settings" section for configuration.
🔸Choose a Symbol that Typically Trends:
Select an asset that tends to create trends. However, the Strategy Tester results may display poor performance, making it less suitable for sending signals to bots.
🔸Add Trend Filters:
You can enable trend filters like MA and SuperTrend. By default, these are disabled as they are often unnecessary, but you can experiment with their configuration to see if they optimize the strategy's results.
Please review the "Indicator Settings" section for configuration.
🔸Enable Stop Loss Levels:
Activate Stop Loss features, such as Stop Loss % or Alligator Stop Loss. If both are enabled, the one closest to the price during the trade will be applied.
Please review the "Indicator Settings" section for configuration.
🔸Enable Take Profit Levels:
Activate Take Profit options, such as Take Profit % or Alligator Fast Exit. If both are enabled, the one that triggers first will be executed.
Please review the "Indicator Settings" section for configuration.
This is an example with the default settings and how Alligator Stop Loss and Alligator Fast Exit are activated:
In this example, we additionally enable the Take Profit at 10%. We can observe that the Alligator Stop Loss is the active one since it is closer to the price. When the price moves 10% in favor or against the trade, the position is closed. Although the Alligator Fast Exit is enabled, it does not activate because the trades are closed beforehand.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured in 3Commas.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL from 3Commas.
For more details, refer to the 3Commas section: "How to use TradingView Custom Signals.
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format to 3Commas.
🔷 INDICATOR SETTINGS
🔸Alligator Settings
MA's source: Source price for Alligator moving averages.
MA's Type: Type of calculation for MA's.
Jaw and Offset: Jaw length and offset to the right.
Teeth and Offset: Teethlength and offset to the right.
Lips and Offset: Lips length and offset to the right.
🔸Alligator Style
Plot Alligator: Show Alligator Ribbon.
Plot MA's: Show Alligator MA's.
Colors: Main and Gradient Colors for Bullish Alligator, Berish Alligator, Neutral Alligator. For gradient colors it is recommended to use an opacity of 15.
🔸MA & SuperTrend Filters
MA & Plot: Activate MA Filter and Plot MA on the chart.
Long Entries: When activated, it will only execute entries if the price is above the MA
Short Entries: When activated, it will only execute entries if the price is below the MA.
Source: Source price for moving average calculations.
Length: Candles to be used by the MA calculations.
Type: Type of calculation for MA.
Timeframe: Here you can select a larger timeframe for the filter.
ST & Plot: Activate SuperTrend Filter and Plot SuperTrend on the chart.
Long Entries: When activated, it will only execute entries if the price is above the SuperTrend.
Short Entries: When activated, it will only execute entries if the price is below the SuperTrend.
Source: Source price for SuperTrend calculations.
Length: Candles to be used by the SuperTrend calculations.
Factor: ATR multiplier of the SuperTrend.
Timeframe: Here you can select a larger timeframe for the filter.
🔸Strategy Tester
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
Stop Loss %: When activated, the entered value will be used as the Stop Loss in percentage from the entry price level. If Alligator Stop Loss is activated, the closest one to the price will be used.
Exit trades on opposite signal: This option closes the trade if the opposite condition is met. For instance, if we are in a long position and a sell signal is triggered, the long position will be closed, and a short position will be opened. The same applies inversely.
Alligator Stop Loss: In a long trade, the lower part of the Alligator indicator will be used as a dynamic stop loss. Similarly, in a short trade, the upper part of the indicator will be used.
Alligator Fast Exit: Its purpose is to attempt to protect movements in favor of the trade's direction. In the case of long trades, once the price and the upper part of the Alligator indicator are above the trade's entry price, the stop loss will be moved to the upper part. For short trades, once the price and the lower part of the Alligator indicator are below the trade's entry price, the stop loss will be moved to the lower part of the Alligator indicator.
Alligator Squeeze Entry: When activated, entries will only be executed if they meet the condition after a neutral zone of the Alligator indicator.
Alligator Squeeze Exit: When this option is activated, any open trades will be closed when the Alligator indicator enters a neutral mode.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
🔸3Commas DCA Bot Signals
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals to 3Commas.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot you created in 3Commas. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the 3Commas bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the 3Commas format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
🔷 CONCLUSION
The Alligator Strategy is a valuable tool for identifying potential trends and improving decision-making. However, no trading strategy is foolproof. Careful consideration of market conditions, proper risk management, and personal trading goals are essential. Use the Alligator as part of a broader trading system, and remember that consistent learning and discipline are key to success in trading.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Smart DCA Invest LiteEnglish description:
📊 Smart DCA Invest – Features Overview
✅ Automated DCA strategy with dynamic profit targets, optimized risk management.
⚙️ Functionality:
🕒 Time Interval Settings
• 📅 Start Date and Time: The strategy activates only after the specified start time.
• 🔄 Auto Restart: Automatically restarts the strategy after a position is closed.
💵 Investment Amounts
• 🟢 Initial Investment Amount: The amount invested when the first position is opened.
• 🔄 Recurring Investment Amount: The amount invested periodically for subsequent purchases.
📊 Purchase Frequency
• ⏱ Interval Between Purchases: Specifies the minimum number of candles between two purchases to avoid overly frequent position expansions.
🛡️ Risk Management
• 📉 Loss Limit: The strategy halts additional purchases if the price does not drop below a predefined loss level, optimizing the average cost reduction.
• 🎯 Take Profit: A predefined profit target percentage, triggering position closure upon reaching it.
📈 Dynamic Take Profit (TP) Settings
• ⏳ TP Increase Frequency: The interval in days for dynamic TP growth.
• 📊 TP Growth Rate: The percentage by which the TP level increases at the end of each interval.
• ⚙️ Enable Dynamic TP: Allows the TP level to increase dynamically over time based on holding duration.
• 🧠 Smart Invest: Accumulates skipped purchases above the average entry or loss limit price and invests them when the price drops below the loss limit.
🎨 Visual Representation
• 📏 Average Price Line: Displays the average entry price in yellow.
• 🛑 Stop Limit Line: Displays the loss limit in red.
• ✅ Take Profit Line: Displays the dynamically updated profit target in green.
🎨 Visual Elements
• 📏 Average Price Line: Visualizes the average cost on the chart.
• 🛑 Stop Limit Line: Visualizes the loss limit level.
• ✅ Take Profit Line: Displays the TP level graphically.
• 📊 Statistics Table: Detailed data summary presented in a table at the end of the strategy.
📊 Statistics Table
• 📈 Average Price: The average entry price of the current position.
• 🛑 Stop Limit: The loss limit value.
• ✅ Take Profit: The profit target value.
• 📦 Position Size: The size of the current position.
• 💵 Max Invested Amount: The highest amount invested.
• ⏳ Longest DCA Period: The longest duration a DCA position was open.
• 💼 Current Investment: The amount currently invested.
• 🔄 Multiplier: Purchase multiplier value.
• 📊 Dynamically Adjusted TP %: The current dynamic Take Profit percentage.
- Recommended for retesting
Hungarian description:
📊 Smart DCA Invest – Funkciók Leírása
✅ Automatizált DCA stratégia dinamikus profitcélokkal, optimalizált kockázatkezeléssel.
⚙️ Működés:
🕒 Időintervallum Beállítások
• 📅 Kezdési dátum és idő: A stratégia csak a meghatározott kezdési időpont után aktiválódik.
• ⏳ Befejezési dátum és idő: A stratégia a meghatározott időpontig működik.
• 🔄 Automatikus újraindítás: Pozíciózárás után a stratégia automatikusan újraindulhat.
💵 Befektetési Összegek
• 🟢 Első befektetési összeg: Az első pozíció nyitásakor befektetett összeg.
• 🔄 Napi vásárlási összeg: Ismételt periódusonkénti vásárlások összege.
📊 Vásárlási Gyakoriság
• ⏱ Intervallum két vásárlás között: Meghatározza a minimális gyertya intervallumot két vásárlás között, elkerülve a túl gyakori pozícióbővítéseket.
🛡️ Kockázatkezelés
• 📉 Loss Limit: Ha az ár nem csökken egy meghatározott veszteségi szint alá, a stratégia nem vásárol tovább, hogy hatékonyabban csökkentse az átlagárat.
• 🎯 Take Profit: Előre meghatározott profitcél százalékos értéke, amely elérésekor a pozíció lezárul.
📈 Dinamikus Take Profit (TP) Beállítások
• ⏳ TP növelési gyakoriság: A dinamikus TP növekedésének időszaka napokban.
• 📊 TP növekedés mértéke: A TP szint százalékos növekedése az intervallum végén.
• ⚙️ Dinamikus TP engedélyezése: A TP szint dinamikusan növekszik a tartási idő függvényében.
• 🧠 Smart Invest: Kihagyott vásárlások felhalmozása (átlagos bekerülési vagy „Loss limit” feletti árfolyamnál), amelyek a „Loss limit” árszint alatt befektetésre kerülnek.
🎨 Vizuális Megjelenítés
• 📏 Átlagár vonal: Sárga színnel jelzi az átlagárat.
• 🛑 Stop Limit vonal: Piros színnel jelzi a veszteségi korlátot.
• ✅ Take Profit vonal: Zöld színnel jelzi a dinamikusan frissülő profitcélt.
🎨 Vizuális Elemek
• 📏 Átlagár vonal: Az átlagár megjelenítése a grafikonon.
• 🛑 Stop Limit vonal: A veszteségkorlátozási szint megjelenítése.
• ✅ Take Profit vonal: A Take Profit szint grafikai megjelenítése.
• 📊 Statisztikai táblázat megjelenítése: A stratégia végén részletes adatok jelennek meg egy táblázatban.
📊 Statisztikai Táblázat
• 📈 Átlagár: Az aktuális pozíció átlagos bekerülési ára.
• 🛑 Stop Limit: A veszteségkorlátozási szint értéke.
• ✅ Take Profit: A profitcél értéke.
• 📦 Pozícióméret: Az aktuális pozíció nagysága.
• 💵 Maximális befektetett összeg: A legnagyobb befektetett érték.
• ⏳ Leghosszabb DCA időszak: A leghosszabb időtartam, amíg egy DCA pozíció nyitva maradt.
• 💼 Aktuális befektetés: Az aktuálisan befektetett összeg.
• 🔄 Multiplikátor: Vásárlási szorzó érték.
• 📊 Dinamikusan beállított TP %: Az aktuálisan érvényes Take Profit százalékos értéke.
Bullish Reversal Bar Strategy [Skyrexio]Overview
Bullish Reversal Bar Strategy leverages the combination of candlestick pattern Bullish Reversal Bar (description in Methodology and Justification of Methodology), Williams Alligator indicator and Williams Fractals to create the high probability setups. Candlestick pattern is used for the entering into trade, while the combination of Williams Alligator and Fractals is used for the trend approximation as close condition. Strategy uses only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator or the candlestick pattern invalidation to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Trend Trade Filter: strategy uses Alligator and Fractal combination as high probability trend filter.
Methodology
The strategy opens long trade when the following price met the conditions:
1.Current candle's high shall be below the Williams Alligator's lines (Jaw, Lips, Teeth)(all details in "Justification of Methodology" paragraph)
2.Price shall create the candlestick pattern "Bullish Reversal Bar". Optionally if MFI and AO filters are enabled current candle shall have the decreasing AO and at least one of three recent bars shall have the squat state on the MFI (all details in "Justification of Methodology" paragraph)
3.If price breaks through the high of the candle marked as the "Bullish Reversal Bar" the long trade is open at the price one tick above the candle's high
4.Initial stop loss is placed at the Bullish Reversal Bar's candle's low
5.If price hit the Bullish Reversal Bar's low before hitting the entry price potential trade is cancelled
6.If trade is active and initial stop loss has not been hit, trade is closed when the combination of Alligator and Williams Fractals shall consider current trend change from upward to downward.
Strategy settings
In the inputs window user can setup strategy setting:
Enable MFI (if true trades are filtered using Market Facilitation Index (MFI) condition all details in "Justification of Methodology" paragraph), by default = false)
Enable AO (if true trades are filtered using Awesome Oscillator (AO) condition all details in "Justification of Methodology" paragraph), by default = false)
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. The first and key concept is the Bullish Reversal Bar candlestick pattern. This is just the single bar pattern. The rules are simple:
Candle shall be closed in it's upper half
High of this candle shall be below all three Alligator's lines (Jaw, Lips, Teeth)
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
How we can use all these indicators in this strategy? This strategy is a counter trend one. Candle's high shall be below all Alligator's lines. During this market stage the bullish reversal bar candlestick pattern shall be printed. This bar during the downtrend is a high probability setup for the potential reversal to the upside: bulls were able to close the price in the upper half of a candle. The breaking of its high is a high probability signal that trend change is confirmed and script opens long trade. If market continues going down and break down the bullish reversal bar's low potential trend change has been invalidated and strategy close long trade.
If market really reversed and started moving to the upside strategy waits for the trend change form the downtrend to the uptrend according to approximation of Alligator and Fractals combination. If this change happens strategy close the trade. This approach helps to stay in the long trade while the uptrend continuation is likely and close it if there is a high probability of the uptrend finish.
Optionally users can enable MFI and AO filters. First of all, let's briefly explain what are these two indicators. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
This indicator is filtering signals in the following way: if current AO bar is decreasing this candle can be interpreted as a bullish reversal bar. This logic is applicable because initially this strategy is a trend reversal, it is searching for the high probability setup against the current trend. Decreasing AO is the additional high probability filter of a downtrend.
Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -5.29%
Maximum Single Profit: +29.99%
Net Profit: +5472.66 USDT (+54.73%)
Total Trades: 103 (33.98% win rate)
Profit Factor: 1.634
Maximum Accumulated Loss: 1231.15 USDT (-8.32%)
Average Profit per Trade: 53.13 USDT (+0.94%)
Average Trade Duration: 76 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h ETH/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
XT Alert Builder - [CrossTrade]The XT Alert Builder is designed to work with CrossTrade and provide an easy way to create strategy entries from Indicator signal sources.
The {{strategy.order.alert_message}} variable along with your Secret Key will send CrossTrade compatible payloads for automated order execution in NinjaTrader 8.
SIGNAL SETTINGS
1. Determine your Entry Signal Source (indicator or OHLC) for both buy and sell signals independently. You can also elect to make the strategy unidirectional by unchecking one of the signal boxes.
2. Determine your Exit Signal Type. The default is Custom which means you're using some kind of input for this like an indicator. Optionally, you can select 'Session End' which will delay the strategy exit until the last bar of the session based n the Trading End Hour/Minute you set in your Trading Hours section.
3. Determine you Exit Sources for Buy and Sells. You can mix and match these inputs for ultimate customization of entries and exits - have fun!
The strategy will by default send a CLOSEPOSITION command to the instrument and account specified based on your Exit settings and time.
TRADING HOURS
Users can specify a trading session or time window to ensure signals only occur during desired hours. The Session End exit signal is based on this window.
NINJATRADER SETTINGS
1. Your NT8 Account. Separate multiple accounts by comma for multi-account placement.
2. Your preferred NT8 instrument in NT compatible format. (e.g. ES 03-25, ES MAR25)
3. Your preferred NT8 quantity
TRADE MANAGEMENT
We've provided both options, you can either use an ATM strategy template or stop loss and take profit levels. More info on Tick and Percentage based stops and targets.
Key Points for successful Trade Management settings application:
1. The ATM template name and qty must match what's saved on Ninja
2. You can choose either ticks or percentage based application - but not both.
3. The stops and target levels need to be offset based on the directional price scale. If you're buying then the stop requires a negative sign and vise versa for Sell orders.
Buy Example:
Take Profit = 50
Stop Loss = -20
CROSSTRADE ADVANCED OPTIONS
Features such as our Flatten first, Require Market Position, Delay Timer, Rate Limiting, and Max Position command enhancements have also been included. More info on these can be found in our Help Docs.
INSTUCTIONS FOR ALERT CREATION
Remove the default info provided by the strategy and then add your CrossTrade secret key and the dynamic strategy variable {{strategy.order.alert_message}}
For example:
Key=your-secret-key;
{{strategy.order.alert_message}}
Trade well,
- CrossTrade Team
three Supertrend EMA Strategy by Prasanna +DhanuThe indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
Custom Strategy: ETH Martingale 2.0Strategic characteristics
ETH Little Martin 2.0 is a self-developed trading strategy based on the Martingale strategy, mainly used for trading ETH (Ethereum). The core idea of this strategy is to place orders in the same direction at a fixed price interval, and then use Martin's multiple investment principle to reduce losses, but this is also the main source of losses.
Parameter description:
1 Interval： The minimum spacing for taking profit, stop loss, and opening/closing of orders. Different targets have different spacing. Taking ETH as an example, it is generally recommended to have a spacing of 2% for fluctuations in the target.
2 Base Price： This is the price at which you triggered the first order. Similarly, I am using ETH as an example. If you have other targets, I suggest using the initial value of a price that can be backtesting. The Base Price is only an initial order price and has no impact on subsequent orders.
3 Initial Order Amount： Users can set an initial order amount to control the risk of each transaction. If the stop loss is reached, we will double the amount based on this value. This refers to the value of the position held, not the number of positions held.
4 Loss Multiplier： The strategy will increase the next order amount based on the set multiple after the stop loss, in order to make up for the previous losses through a larger position. Note that after taking profit, it will be reset to 1 times the Initial Order Amount.
5. Long Short Operation: The first order of the strategy is a multiple entry, and in subsequent orders, if the stop loss is reached, a reverse order will be opened. The position value of a one-way order is based on the Loss Multiplier multiple investment, so it is generally recommended that the Loss Multiplier default to 2.
Improvement direction
Although this strategy already has a certain trading logic, there are still some improvement directions that can be considered:
1. Dynamic adjustment of spacing: Currently, the spacing is fixed, and it can be considered to dynamically adjust the spacing based on market volatility to improve the adaptability of the strategy. Try using dynamic spacing, which may be more suitable for the actual market situation.
2. Filtering criteria: Orders and no orders can be optimized separately. The biggest problem with this strategy is that it will result in continuous losses during fluctuations, and eventually increase the investment amount. You can consider filtering out some fluctuations or only focusing on trend trends.
3. Risk management: Add more risk management measures, such as setting a maximum loss limit to avoid huge losses caused by continuous stop loss.
4. Optimize the stop loss multiple: Currently, the stop loss multiple is fixed, and it can be considered to dynamically adjust the multiple according to market conditions to reduce risk.
Liquid Pours XtremeStrategy Description: Liquid Pours Xtreme
The Liquid Pours Xtreme is an innovative trading strategy that combines the analysis of specific time-based patterns with price comparisons to identify potential opportunities in the forex market. Designed for traders seeking a structured methodology based on clear rules, this strategy offers integration with Telegram for real-time alerts and provides visual tools to enhance trade management.
Key Features:
Analysis of Specific Time Patterns: The strategy captures and compares closing prices at two key moments during the trading day, identifying recurring patterns that may indicate future market movements.
Dynamic SL and TP Levels Implementation: Utilizes tick-based calculations to set Stop-Loss and Take-Profit levels, adapting to the current market volatility.
Advanced Telegram Integration: Provides detailed alerts including information such as the asset, signal time, entry price, and SL/TP levels, facilitating real-time decision-making.
Complete Customization: Allows users to adjust key parameters, including operation schedules, weekdays, and visual settings, adapting to different trading styles.
Enhanced Chart Visualization: Includes visual elements like candle color changes based on signal state, event markers, and halos to highlight important moments.
Default Strategy Properties: Specific configuration for optimal risk management and simulation.
How the Strategy Works
Capturing Prices at Key Moments:
- The strategy records the closing price at two user-defined specific times. These times typically correspond to periods of high market volatility, such as the opening of the European session and the US pre-market.
- Rationale: Volatility and trading volume usually increase during these times, presenting opportunities for significant price movements.
Generating Signals Based on Price Comparison:
- Buy Signal: If the second closing price is lower than the first, it indicates possible accumulation and is interpreted as a bullish signal.
- Sell Signal: If the second closing price is higher than the first, it suggests possible distribution and is interpreted as a bearish signal.
- Signals are only generated on selected trading days, allowing you to avoid days with lower liquidity or higher risk.
Calculating Dynamic SL and TP Levels:
- Stop-Loss (SL) and Take-Profit (TP) levels are calculated based on the entry price and a user-defined number of ticks, adapting to market volatility.
- The strategy offers the option to base these levels on the close of the signal candle or the open of the next candle, providing flexibility according to the trader's preference.
- SL and TP boxes are drawn on the chart for visual reference, facilitating trade management.
Automatic Execution and Alerts:
- Upon signal generation, the strategy automatically executes a market order (buy or sell).
- Sends a detailed alert to your Telegram channel, including essential information for quick decision-making.
Visual Elements:
- Colors candles based on the signal state: buy, sell, or neutral, allowing for quick trend identification.
- Provides a smooth color transition between signal states and uses markers and halos to highlight important events and signals on the chart.
Trade Management:
- Manages open trades with automatic exit conditions based on the established SL and TP levels.
- Includes mechanisms to prevent exceeding TradingView's limitations on boxes and labels, ensuring optimal script performance.
Originality and utility:
- This strategy incorporates a unique approach focusing on specific time patterns and their relationship to institutional activity in the market.
How to Use the Strategy
Add the Script to the Chart:
- Go to the indicators menu in TradingView.
- Search for " Liquid Pours Xtreme " and add it to your chart.
Set Up Telegram Alerts:
- Enter your Telegram Chat ID in the script parameters to receive alerts.
- Customize the Buy and Sell alert messages as desired.
Configure Time Patterns:
- Set the hours and minutes for the two times you want to compare closing prices, aligning them with relevant market sessions or events.
Set SL and TP Parameters:
- Define the number of ticks for the Stop-Loss and Take-Profit levels, adapting them to the asset you're trading and your risk tolerance.
- Choose the basis for SL and TP calculation (close of the signal candle or open of the next candle).
Select Trading Days:
- Enable or disable trading on specific days of the week, allowing you to avoid days with lower activity or unexpected volatility.
Customize Visual Elements:
- Adjust the colors and styles of visual elements to enhance readability and suit your personal preferences.
Monitor the Strategy:
- Observe the chart for signals and use Telegram alerts to stay informed of new opportunities, even when you're not at your terminal.
Testing and Optimization:
- Use TradingView's backtesting features to evaluate the historical performance of the strategy with different parameters.
- Adjust and optimize the parameters based on the results and your own analysis.
Adjust the Strategy Properties:
- Ensure that the strategy properties (order size, commission, slippage) are aligned with your trading account and platform to obtain realistic results.
Strategy Properties (Important)
This script backtest is conducted on M30 EURUSD , using the following backtesting properties:
Initial Capital: $10,000
Order Size: 50,000 Contracts (equivalent to 0.5% of the capital)
Commission: $0.20 per order
Slippage: 1 tick
Pyramiding: 1 order
Verify Price for Limit Orders: 0 ticks
Recalculate on Order Execution: Enabled
Recalculate on Every Tick: Enabled
Recalculate After Order Filled: Enabled
Bar Magnifier for Backtesting Precision: Enabled
We use these properties to ensure a realistic preview of the backtesting system. Note that default properties may vary for different reasons:
- Order Size: It is essential to calculate the contract size according to the traded asset and desired risk level.
- Commission and Slippage: These costs can vary depending on the market and instrument; there is no default value that might return realistic results.
We strongly recommend all users adjust the Properties within the script settings to align with their accounts and trading platforms to ensure the results from the strategies are realistic.
Backtesting Results:
- Net Profit: $4,037.50 (40.37%)
- Total Closed Trades : 292
- Profitability Percentage: 26.71%
- Profit Factor: 1.369
- Max Drawdown: $769.30 (6.28%)
- Average Trade: $13.83 (0.03%)
- Average Bars in Trades: 11
These results were obtained under the mentioned conditions and properties, providing an overview of the strategy's historical performance.
Interpreting Results:
- The strategy has demonstrated profitability in the analyzed period, although with a win rate of 26.71%, indicating that success relies on a favorable risk-reward ratio.
- The profit factor of 1.369 suggests that total gains exceed total losses by that proportion.
- It is crucial to consider the maximum drawdown of 6.28% when evaluating the strategy's suitability to your risk tolerance.
Risk Warning:
Trading leveraged financial instruments carries a high level of risk and may not be suitable for all investors. Before deciding to trade, you should carefully consider your investment objectives, level of experience, and risk tolerance. Past performance does not guarantee future results. It is essential to conduct additional testing and adjust the strategy according to your needs.
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What Makes This Strategy Original?
Time-Based Pattern Approach: Unlike conventional strategies, this strategy focuses on identifying time patterns that reflect institutional activity and macroeconomic events that can influence the market.
Advanced Technological Integration: The combination of automatic execution and customized alerts via Telegram provides an efficient and modern tool for active traders.
Customization and Adaptability: The wide range of adjustable parameters allows the strategy to be tailored to different assets, time zones, and trading styles.
Enhanced Visual Tools: Incorporated visual elements facilitate quick market interpretation and informed decision-making.
Additional Considerations
Continuous Testing and Optimization: Users are encouraged to perform additional backtesting and optimize parameters according to their own observations and requirements.
Complementary Analysis: Use this strategy in conjunction with other indicators and fundamental analysis to reinforce decision-making.
Rigorous Risk Management: Ensure that SL and TP levels, as well as position sizing, align with your risk management plan.
Updates and Support: I am committed to providing updates and improvements based on community feedback. For inquiries or suggestions, feel free to contact me.
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Example Configuration
Assuming you want to use the strategy with the following parameters:
Telegram Chat ID: Your unique Telegram Chat ID
First Time (Hour:Minute): 6:30
Second Time (Hour:Minute): 7:30
SL Ticks: 100
TP Ticks: 400
SL and TP Basis: Close of the Signal Candle
Trading Days: Tuesday, Wednesday, Thursday
Simulated Initial Capital: $10,000
Risk per Trade in Simulation: $50 (-0.5% of capital)
Slippage and Commissions in Simulation: 1 tick of slippage and $0.20 commission per trade
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Conclusion
The Liquid Pours Xtreme strategy offers an innovative approach by combining specific time analysis with robust risk management and modern technological tools. Its original and adaptable design makes it valuable for traders looking to diversify their methods and capitalize on opportunities based on less conventional patterns.
Ready for immediate implementation in TradingView, this strategy can enrich your trading arsenal and contribute to a more informed and structured approach to your operations.
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Final Disclaimer:
Financial markets are volatile and can present significant risks. This strategy should be used as part of a comprehensive trading approach and does not guarantee positive results. It is always advisable to consult with a professional financial advisor before making investment decisions.
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Bollinger Breakout Strategy with Direction Control [4H crypto]Bollinger Breakout Strategy with Direction Control - User Guide
This strategy leverages Bollinger Bands, RSI, and directional filters to identify potential breakout trading opportunities. It is designed for traders looking to capitalize on significant price movements while maintaining control over trade direction (long, short, or both). Here’s how to use this strategy effectively:
How the Strategy Works
Indicators Used:
Bollinger Bands:
A volatility-based indicator with an upper and lower band around a simple moving average (SMA). The bands expand or contract based on market volatility.
RSI (Relative Strength Index):
Measures momentum to determine overbought or oversold conditions. In this strategy, RSI is used to confirm breakout strength.
Trade Direction Control:
You can select whether to trade:
Long only: Buy positions.
Short only: Sell positions.
Both: Trade in both directions depending on conditions.
Breakout Conditions:
Long Trade:
The price closes above the upper Bollinger Band.
RSI is above the midline (50), confirming upward momentum.
The "Trade Direction" setting allows either "Long" or "Both."
Short Trade:
The price closes below the lower Bollinger Band.
RSI is below the midline (50), confirming downward momentum.
The "Trade Direction" setting allows either "Short" or "Both."
Risk Management:
Stop-Loss:
Long trades: Set at 2% below the entry price.
Short trades: Set at 2% above the entry price.
Take-Profit:
Calculated using a Risk/Reward Ratio (default is 2:1).
Adjust this in the strategy settings.
Inputs and Customization
Key Parameters:
Bollinger Bands Length: Default is 20. Adjust based on the desired sensitivity.
Multiplier: Default is 2.0. Higher values widen the bands; lower values narrow them.
RSI Length: Default is 14, which is standard for RSI.
Risk/Reward Ratio: Default is 2.0. Increase for more aggressive profit targets, decrease for conservative exits.
Trade Direction:
Options: "Long," "Short," or "Both."
Example: Set to "Long" in a bullish market to focus only on buy trades.
How to Use This Strategy
Adding the Strategy:
Paste the script into TradingView’s Pine Editor and add it to your chart.
Setting Parameters:
Adjust the Bollinger Band settings, RSI, and Risk/Reward Ratio to fit the asset and timeframe you're trading.
Analyzing Signals:
Green line (Upper Band): Signals breakout potential for long trades.
Red line (Lower Band): Signals breakout potential for short trades.
Blue line (Basis): Central Bollinger Band (SMA), helpful for understanding price trends.
Testing the Strategy:
Use the Strategy Tester in TradingView to backtest performance on your chosen asset and timeframe.
Optimizing for Assets:
Forex pairs, cryptocurrencies (like BTC), or stocks with high volatility are ideal for this strategy.
Works best on higher timeframes like 4H or Daily.
Best Practices
Combine with Volume: Confirm breakouts with increased volume for higher reliability.
Avoid Sideways Markets: Use additional trend filters (like ADX) to avoid trades in low-volatility conditions.
Optimize Parameters: Regularly adjust the Bollinger Bands multiplier and RSI settings to match the asset's behavior.
By utilizing this strategy, you can effectively trade breakouts while maintaining flexibility in trade direction. Adjust the parameters to match your trading style and market conditions for optimal results!
Triple CCI Strategy MFI Confirmed [Skyrexio]Overview
Triple CCI Strategy MFI Confirmed leverages 3 different periods Commodity Channel Index (CCI) indicator in conjunction Money Flow Index (MFI) and Exponential Moving Average (EMA) to obtain the high probability setups. Fast period CCI is used for having the high probability to enter in the direction of short term trend, middle and slow period CCI are used for confirmation, if market now likely in the mid and long-term uptrend. MFI is used to confirm trade with the money inflow/outflow with the high probability. EMA is used as an additional trend filter. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Four layers trade filtering system: Strategy utilizes two different period CCI indicators, MFI and EMA indicators to confirm the signals produced by fast period CCI.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Fast period CCI shall crossover the zero-line.
Slow and Middle period CCI shall be above zero-lines.
Price shall close above the EMA. Crossover is not obligatory
MFI shall be above 50
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 14, used for calculation short term period CCI)
CCI Middle Length (by default = 25, used for calculation short term period CCI)
CCI Slow Length (by default = 50, used for calculation long term period CCI)
MFI Length (by default = 14, used for calculation MFI
EMA Length (by default = 50, period of EMA, used for trend filtering EMA calculation)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI, MFI and EMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator that measures the deviation of a security's price from its average price over a specific period. It helps traders identify overbought or oversold conditions and potential trend reversals.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Money Flow Index (MFI) is a technical indicator that measures the strength of money flowing into and out of a security. It combines price and volume data to assess buying and selling pressure and is often used to identify overbought or oversold conditions. The formula for MFI involves several steps:
1. Calculate the Typical Price (TP):
TP = (high + low + close) / 3
2. Calculate the Raw Money Flow (RMF):
Raw Money Flow = TP × Volume
3. Determine Positive and Negative Money Flow:
If the current TP is greater than the previous TP, it's Positive Money Flow.
If the current TP is less than the previous TP, it's Negative Money Flow.
4. Calculate the Money Flow Ratio (MFR):
Money Flow Ratio = Sum of Positive Money Flow (over n periods) / Sum of Negative Money Flow (over n periods)
5. Calculate the Money Flow Index (MFI):
MFI = 100 − (100 / (1 + Money Flow Ratio))
MFI above 80 can be considered as overbought, below 20 - oversold.
The Exponential Moving Average (EMA) is a type of moving average that places greater weight and significance on the most recent data points. It is widely used in technical analysis to smooth price data and identify trends more quickly than the Simple Moving Average (SMA).
Formula:
1. Calculate the multiplier
Multiplier = 2 / (n + 1) , Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
This strategy leverages Fast period CCI, which shall break the zero line to the upside to say that probability of short term trend change to the upside increased. This zero line crossover shall be confirmed by the Middle and Slow periods CCI Indicators. At the moment of breakout these two CCIs shall be above 0, indicating that there is a high probability that price is in middle and long term uptrend. This approach increases chances to have a long trade setup in the direction of mid-term and long-term trends when the short-term trend starts to reverse to the upside.
Additionally strategy uses MFI to have a greater probability that fast CCI breakout is confirmed by this indicator. We consider the values of MFI above 50 as a higher probability that trend change from downtrend to the uptrend is real. Script opens long trades only if MFI is above 50. As you already know from the MFI description, it incorporates volume in its calculation, therefore we have another one confirmation factor.
Finally, strategy uses EMA an additional trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses another one EMA (by default = 20 period) as a trailing profit level.
Backtest Results
Operating window: Date range of backtests is 2022.04.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -4.13%
Maximum Single Profit: +19.66%
Net Profit: +5421.21 USDT (+54.21%)
Total Trades: 108 (44.44% win rate)
Profit Factor: 2.006
Maximum Accumulated Loss: 777.40 USDT (-7.77%)
Average Profit per Trade: 50.20 USDT (+0.85%)
Average Trade Duration: 44 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Dual Strategy Selector V2 - CryptogyaniOverview:
This script provides traders with a dual-strategy system that they can toggle between using a simple dropdown menu in the input settings. It is designed to cater to different trading styles and needs, offering both simplicity and advanced filtering techniques. The strategies are built around moving average crossovers, enhanced by configurable risk management tools like take profit levels, trailing stops, and ATR-based stop-loss.
Key Features:
Two Strategies in One Script:
Strategy 1: A classic moving average crossover strategy for identifying entry signals based on trend reversals. Includes user-defined take profit and trailing stop-loss options for profit locking.
Strategy 2: An advanced trend-following system that incorporates:
A higher timeframe trend filter to confirm entry signals.
ATR-based stop-loss for dynamic risk management.
Configurable partial take profit to secure gains while letting the trade run.
Highly Customizable:
All key parameters such as SMA lengths, take profit levels, ATR multiplier, and timeframe for the trend filter are adjustable via the input settings.
Dynamic Toggle:
Traders can switch between Strategy 1 and Strategy 2 with a single dropdown, allowing them to adapt the strategy to market conditions.
How It Works:
Strategy 1:
Entry Logic: A long trade is triggered when the fast SMA crosses above the slow SMA.
Exit Logic: The trade exits at either a user-defined take profit level (percentage or pips) or via an optional trailing stop that dynamically adjusts based on price movement.
Strategy 2:
Entry Logic: Builds on the SMA crossover logic but adds a higher timeframe trend filter to align trades with the broader market direction.
Risk Management:
ATR-Based Stop-Loss: Protects against adverse moves with a volatility-adjusted stop-loss.
Partial Take Profit: Allows traders to secure a percentage of gains while keeping some exposure for extended trends.
How to Use:
Select Your Strategy:
Use the dropdown in the input settings to choose Strategy 1 or Strategy 2.
Configure Parameters:
Adjust SMA lengths, take profit, and risk management settings to align with your trading style.
For Strategy 2, specify the higher timeframe for trend filtering.
Deploy and Monitor:
Apply the script to your preferred asset and timeframe.
Use the backtest results to fine-tune settings for optimal performance.
Why Choose This Script?:
This script stands out due to its dual-strategy flexibility and enhanced features:
For beginners: Strategy 1 provides a simple yet effective trend-following system with minimal setup.
For advanced traders: Strategy 2 includes powerful tools like trend filters and ATR-based stop-loss, making it ideal for challenging market conditions.
By combining simplicity with advanced features, this script offers something for everyone while maintaining full transparency and user customization.
Default Settings:
Strategy 1:
Fast SMA: 21, Slow SMA: 49
Take Profit: 7% or 50 pips
Trailing Stop: Optional (disabled by default)
Strategy 2:
Fast SMA: 20, Slow SMA: 50
ATR Multiplier: 1.5
Partial Take Profit: 50%
Higher Timeframe: 1 Day (1D)
Skeleton Key LiteSkeleton Key Lite Strategy
Note : Every input, except for the API Alerts, depends on an external indicator to provide the necessary values for the strategy to function.
Definitions
Strategy Direction: The trading direction (long or short) as determined by an external source, such as an indicator.
Threshold Conditions:
- Enter Condition: Defines the condition for entering a trade.
- Exit Condition: Defines the condition for exiting a trade.
Stop Loss (SL):
- Trail SL: A trailing stop loss, dynamically updated during the trade.
- Basic SL: A static stop loss level.
- Emergency SL (ER SL): A fallback stop loss for extreme conditions.
- Max SL: The maximum risk tolerance in stop loss.
- Limit SL: A predefined stop loss that is executed as a limit order.
Take Profit (TP):
- Max TP: The maximum profit target for a trade.
- Limit TP: A predefined take profit level executed as a limit order.
API Alerts:
- API Entry: JSON-based configuration for sending entry signals.
- API Exit: JSON-based configuration for sending exit signals.
Broad Concept
The Skeleton Key Lite strategy script is designed to provide a generalized framework for orchestrating trade execution based on external indicators. It allows QuantAlchemy and others to encapsulate strategies into indicators, which can then be backtested and automated using this strategy script.
Inputs
Note : All inputs are dependent on external indicators for values except for the API Alerts.
Strategy Direction:
- Source: Direction signal from an external indicator.
- Options: `LONG` (`1`), `SHORT` (`-1`).
Trade Conditions:
- Enter: Source input, trigger for entry condition.
- Exit: Source input, trigger for exit condition.
Stops and Take Profits:
- Trail SL: Enable/disable dynamic trailing stop loss.
- Basic SL: Enable/disable static stop loss.
- Emergency SL: Enable/disable emergency stop loss.
- Max SL: Enable/disable maximum risk stop loss.
- Max TP: Enable/disable maximum take profit.
- Limit SL: Enable/disable predefined stop loss executed as a limit order.
- Limit TP: Enable/disable predefined take profit executed as a limit order.
Alerts:
- API Entry: Configurable JSON message for entry signals.
- API Exit: Configurable JSON message for exit signals.
How It Works
Trade Logic:
- Conditions for entering and exiting trades are evaluated based on the selected input sources.
Stop Loss and Take Profit Management:
- Multiple stop loss types (trailing, basic, emergency, etc.) and take profit levels are calculated dynamically during the trade entry. Trailing stop loss is updated during the trade based on the selected input.
API Alerts:
- Alerts are triggered using customizable JSON messages, which can be integrated with external trading systems or APIs.
Trade Execution:
- Enter: Initiates a new trade if entry conditions are met and there is no open position.
- Exit: Closes all trades if exit conditions are met or stop loss/take profit thresholds are hit.
Key Features
Customizable: Fully configurable entry and exit conditions based on external indicators.
Encapsulation: Integrates seamlessly with indicators, allowing strategies to be developed as indicator-based signals.
Comprehensive Risk Management:
- Multiple stop loss and take profit options.
- Emergency stop loss for unexpected conditions.
API Integration: Alerts are designed to interface with external systems for automation and monitoring.
Plots
The script plots key variables on the chart for better visualization:
Enter and Exit Signals:
- `enter`: Displays when the entry condition is triggered.
- `exit`: Displays when the exit condition is triggered.
Risk Management Levels:
- `trailSL`: Current trailing stop loss level.
- `basicSL`: Static stop loss level.
- `erSL`: Emergency stop loss level.
- `maxSL`: Maximum risk stop loss level.
Profit Management Levels:
- `maxTP`: Maximum take profit level.
- `limitTP`: Limit-based take profit level.
Limit Orders:
- `limitSL`: Limit-based stop loss level.
- `limitTP`: Limit-based take profit level.
Proposed Interpretations
Entry and Exit Points:
- Use the plotted signals (`enter`, `exit`) to analyze the trade entry and exit points visually.
Risk and Profit Levels:
- Monitor the stop loss (`SL`) and take profit (`TP`) levels to assess trade performance.
Dynamic Trail SL:
- Observe the `trailSL` to evaluate how the trailing stop adapts during the trade.
Limitations
Dependence on Indicators:
- This script relies on external indicators to provide signals for strategy execution.
No Indicator Included:
- Users must integrate an appropriate indicator for source inputs.
Back-Test Constraints:
- Back-testing results depend on the accuracy and design of the integrated indicators.
Final Thoughts
The Skeleton Key Lite strategy by QuantAlchemy provides a robust framework for automated trading by leveraging indicator-based signals. Its flexibility and comprehensive risk management make it a valuable tool for traders seeking to implement and backtest custom strategies.
Disclaimer
This script is for educational purposes only. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion and risk.
Max Pain StrategyThe Max Pain Strategy uses a combination of volume and price movement thresholds to identify potential "pain zones" in the market. A "pain zone" is considered when the volume exceeds a certain multiple of its average over a defined lookback period, and the price movement exceeds a predefined percentage relative to the price at the beginning of the lookback period.
Here’s how the strategy functions step-by-step:
Inputs:
length: Defines the lookback period used to calculate the moving average of volume and the price change over that period.
volMultiplier: Sets a threshold multiplier for the volume; if the volume exceeds the average volume multiplied by this factor, it triggers the condition for a potential "pain zone."
priceMultiplier: Sets a threshold for the minimum percentage price change that is required for a "pain zone" condition.
Calculations:
averageVolume: The simple moving average (SMA) of volume over the specified lookback period.
priceChange: The absolute difference in price between the current bar's close and the close from the lookback period (length).
Pain Zone Condition:
The condition for entering a position is triggered if both the volume is higher than the average volume by the volMultiplier and the price change exceeds the price at the length-period ago by the priceMultiplier. This is an indication of significant market activity that could result in a price move.
Position Entry:
A long position is entered when the "pain zone" condition is met.
Exit Strategy:
The position is closed after the specified holdPeriods, which defines how many periods the position will be held after being entered.
Visualization:
A small triangle is plotted on the chart where the "pain zone" condition is met.
The background color changes to a semi-transparent red when the "pain zone" is active.
Scientific Explanation of the Components
Volume Analysis and Price Movement: These are two critical factors in trading strategies. Volume often serves as an indicator of market strength (or weakness), and price movement is a direct reflection of market sentiment. Higher volume with significant price movement may suggest that the market is entering a phase of increased volatility or trend formation, which the strategy aims to exploit.
Volume analysis: The study of volume as an indicator of market participation, with increased volume often signaling stronger trends (Murphy, J. J., Technical Analysis of the Financial Markets).
Price movement thresholds: A large price change over a short period may be interpreted as a breakout or a potential reversal point, aligning with volatility and liquidity analysis (Schwager, J. D., Market Wizards).
Repainting Check: This strategy does not involve any repainting because it is based on current and past data, and there is no reference to future values in the decision-making process. However, any strategy that uses lagging indicators or conditions based on historical bars, like close , is inherently a lagging strategy and might not predict real-time price action accurately until after the fact.
Risk Management: The position hold duration is predefined, which adds an element of time-based risk control. This duration ensures that the strategy does not hold a position indefinitely, which could expose it to unnecessary risk.
Potential Issues and Considerations
Repainting:
The strategy does not utilize future data or conditions that depend on future bars, so it does not inherently suffer from repainting issues.
However, since the strategy relies on volume and price change over a set lookback period, the decision to enter or exit a trade is only made after the data for the current bar is complete, meaning the trade decisions are somewhat delayed, which could be seen as a lagging feature rather than a repainting one.
Lagging Nature:
As with many technical analysis-based strategies, this one is based on past data (moving averages, price changes), meaning it reacts to market movements after they have already occurred, rather than predicting future price actions.
Overfitting Risk:
With parameters like the lookback period and multipliers being user-adjustable, there is a risk of overfitting to historical data. Adjusting parameters too much based on past performance can lead to poor out-of-sample results (Gauthier, P., Practical Quantitative Finance).
Conclusion
The Max Pain Strategy is a simple approach to identifying potential market entries based on volume spikes and significant price changes. It avoids repainting by relying solely on historical and current bar data, but it is inherently a lagging strategy that reacts to price and volume patterns after they have occurred. Therefore, the strategy can be effective in trending markets but may struggle in highly volatile, sideways markets.
The Most Powerful TQQQ EMA Crossover Trend Trading StrategyTQQQ EMA Crossover Strategy Indicator
Meta Title: TQQQ EMA Crossover Strategy - Enhance Your Trading with Effective Signals
Meta Description: Discover the TQQQ EMA Crossover Strategy, designed to optimize trading decisions with fast and slow EMA crossovers. Learn how to effectively use this powerful indicator for better trading results.
Key Features
The TQQQ EMA Crossover Strategy is a powerful trading tool that utilizes Exponential Moving Averages (EMAs) to identify potential entry and exit points in the market. Key features of this indicator include:
**Fast and Slow EMAs:** The strategy incorporates two EMAs, allowing traders to capture short-term trends while filtering out market noise.
**Entry and Exit Signals:** Automated signals for entering and exiting trades based on EMA crossovers, enhancing decision-making efficiency.
**Customizable Parameters:** Users can adjust the lengths of the EMAs, as well as take profit and stop loss multipliers, tailoring the strategy to their trading style.
**Visual Indicators:** Clear visual plots of the EMAs and exit points on the chart for easy interpretation.
How It Works
The TQQQ EMA Crossover Strategy operates by calculating two EMAs: a fast EMA (default length of 20) and a slow EMA (default length of 50). The core concept is based on the crossover of these two moving averages:
- When the fast EMA crosses above the slow EMA, it generates a *buy signal*, indicating a potential upward trend.
- Conversely, when the fast EMA crosses below the slow EMA, it produces a *sell signal*, suggesting a potential downward trend.
This method allows traders to capitalize on momentum shifts in the market, providing timely signals for trade execution.
Trading Ideas and Insights
Traders can leverage the TQQQ EMA Crossover Strategy in various market conditions. Here are some insights:
**Scalping Opportunities:** The strategy is particularly effective for scalping in volatile markets, allowing traders to make quick profits on small price movements.
**Swing Trading:** Longer-term traders can use this strategy to identify significant trend reversals and capitalize on larger price swings.
**Risk Management:** By incorporating customizable stop loss and take profit levels, traders can manage their risk effectively while maximizing potential returns.
How Multiple Indicators Work Together
While this strategy primarily relies on EMAs, it can be enhanced by integrating additional indicators such as:
- **Relative Strength Index (RSI):** To confirm overbought or oversold conditions before entering trades.
- **Volume Indicators:** To validate breakout signals, ensuring that price movements are supported by sufficient trading volume.
Combining these indicators provides a more comprehensive view of market dynamics, increasing the reliability of trade signals generated by the EMA crossover.
Unique Aspects
What sets this indicator apart is its simplicity combined with effectiveness. The reliance on EMAs allows for smoother signals compared to traditional moving averages, reducing false signals often associated with choppy price action. Additionally, the ability to customize parameters ensures that traders can adapt the strategy to fit their unique trading styles and risk tolerance.
How to Use
To effectively utilize the TQQQ EMA Crossover Strategy:
1. **Add the Indicator:** Load the script onto your TradingView chart.
2. **Set Parameters:** Adjust the fast and slow EMA lengths according to your trading preferences.
3. **Monitor Signals:** Watch for crossover points; enter trades based on buy/sell signals generated by the indicator.
4. **Implement Risk Management:** Set your stop loss and take profit levels using the provided multipliers.
Regularly review your trading performance and adjust parameters as necessary to optimize results.
Customization
The TQQQ EMA Crossover Strategy allows for extensive customization:
- **EMA Lengths:** Change the default lengths of both fast and slow EMAs to suit different time frames or market conditions.
- **Take Profit/Stop Loss Multipliers:** Adjust these values to align with your risk management strategy. For instance, increasing the take profit multiplier may yield larger gains but could also increase exposure to market fluctuations.
This flexibility makes it suitable for various trading styles, from aggressive scalpers to conservative swing traders.
Conclusion
The TQQQ EMA Crossover Strategy is an effective tool for traders seeking an edge in their trading endeavors. By utilizing fast and slow EMAs, this indicator provides clear entry and exit signals while allowing for customization to fit individual trading strategies. Whether you are a scalper looking for quick profits or a swing trader aiming for larger moves, this indicator offers valuable insights into market trends.
Incorporate it into your TradingView toolkit today and elevate your trading performance!
