Multi-TF AI SuperTrend with ADX - Strategy [PresentTrading]

## █ Introduction and How it is Different
The trading strategy in question is an enhanced version of the SuperTrend indicator, combined with AI elements and an ADX filter. It's a multi-timeframe strategy that incorporates two SuperTrends from different timeframes and utilizes a k-nearest neighbors (KNN) algorithm for trend prediction. It's different from traditional SuperTrend indicators because of its AI-based predictive capabilities and the addition of the ADX filter for trend strength.

BTC 8hr Performance

ETH 8hr Performance

## █ Strategy, How it Works: Detailed Explanation (Revised)

### Multi-Timeframe Approach
The strategy leverages the power of multiple timeframes by incorporating two SuperTrend indicators, each calculated on a different timeframe. This multi-timeframe approach provides a holistic view of the market's trend. For example, a 8-hour timeframe might capture the medium-term trend, while a daily timeframe could capture the longer-term trend. When both SuperTrends align, the strategy confirms a more robust trend.

### K-Nearest Neighbors (KNN)
The KNN algorithm is used to classify the direction of the trend based on historical SuperTrend values. It uses weighted voting of the 'k' nearest data points. For each point, it looks at its 'k' closest neighbors and takes a weighted average of their labels to predict the current label. The KNN algorithm is applied separately to each timeframe's SuperTrend data.

### SuperTrend Indicators
Two SuperTrend indicators are used, each from a different timeframe. They are calculated using different moving averages and ATR lengths as per user settings. The SuperTrend values are then smoothed to make them suitable for KNN-based prediction.

### ADX and DMI Filters
The ADX filter is used to eliminate weak trends. Only when the ADX is above 20 and the directional movement index (DMI) confirms the trend direction, does the strategy signal a buy or sell.

### Combining Elements
A trade signal is generated only when both SuperTrends and the ADX filter confirm the trend direction. This multi-timeframe, multi-indicator approach reduces false positives and increases the robustness of the strategy.

By considering multiple timeframes and using machine learning for trend classification, the strategy aims to provide more accurate and reliable trade signals.

BTC 8hr Performance (Zoom-in)

## █ Trade Direction
The strategy allows users to specify the trade direction as 'Long', 'Short', or 'Both'. This is useful for traders who have a specific market bias. For instance, in a bullish market, one might choose to only take 'Long' trades.

## █ Usage
Parameters: Adjust the number of neighbors, data points, and moving averages according to the asset and market conditions.
Trade Direction: Choose your preferred trading direction based on your market outlook.
ADX Filter: Optionally, enable the ADX filter to avoid trading in a sideways market.
Risk Management: Use the trailing stop-loss feature to manage risks.

## █ Default Settings
Neighbors (K): 3
Data points for KNN: 12
SuperTrend Length: 10 and 5 for the two different SuperTrends
ATR Multiplier: 3.0 for both
ADX Length: 21
ADX Time Frame: 240
Default trading direction: Both

By customizing these settings, traders can tailor the strategy to fit various trading styles and assets.

Watch patiently/ then trade

ด้วยจิตวิญญาณของ TradingView อย่างแท้จริง ผู้เขียนสคริปต์นี้ได้เผยแพร่เป็นโอเพนซอร์ส เพื่อให้ผู้ค้าสามารถเข้าใจและตรวจสอบได้ ไชโยให้กับผู้เขียน! คุณสามารถใช้ได้ฟรี แต่การใช้รหัสนี้ซ้ำในสิ่งพิมพ์อยู่ภายใต้กฎระเบียบการใช้งาน คุณสามารถตั้งเป็นรายการโปรดเพื่อใช้บนชาร์ตได้


ข้อมูลและบทความไม่ได้มีวัตถุประสงค์เพื่อก่อให้เกิดกิจกรรมทางการเงิน, การลงทุน, การซื้อขาย, ข้อเสนอแนะ หรือคำแนะนำประเภทอื่น ๆ ที่ให้หรือรับรองโดย TradingView อ่านเพิ่มเติมที่ เงื่อนไขการใช้บริการ