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AI SuperTrend x Pivot Percentile - Strategy [PresentTrading]█ Introduction and How it is Different The AI SuperTrend x Pivot Percentile strategy is a sophisticated trading approach that integrates AI-driven analysis with traditional technical indicators. Combining the AI SuperTrend with the Pivot Percentile strategy highlights several key advantages: 1. Enhanced Accuracy in Trend Prediction: The AI SuperTrend utilizes K-Nearest Neighbors (KNN) algorithm for trend prediction, improving accuracy by considering historical data patterns. This is complemented by the Pivot Percentile analysis which provides additional context on trend strength. 2. Comprehensive Market Analysis: The integration offers a multi-faceted approach to market analysis, combining AI insights with traditional technical indicators. This dual approach captures a broader range of market dynamics. BTC 6H L/S Performance Local █ Strategy: How it Works - Detailed Explanation 🔶 AI-Enhanced SuperTrend Indicators 1. SuperTrend Calculation: - The SuperTrend indicator is calculated using a moving average and the Average True Range (ATR). The basic formula is: - Upper Band = Moving Average + (Multiplier × ATR) - Lower Band = Moving Average - (Multiplier × ATR) - The moving average type (SMA, EMA, WMA, RMA, VWMA) and the length of the moving average and ATR are adjustable parameters. - The direction of the trend is determined based on the position of the closing price in relation to these bands. 2. AI Integration with K-Nearest Neighbors (KNN): - The KNN algorithm is applied to predict trend direction. It uses historical price data and SuperTrend values to classify the current trend as bullish or bearish. - The algorithm calculates the 'distance' between the current data point and historical points. The 'k' nearest data points (neighbors) are identified based on this distance. - A weighted average of these neighbors' trends (bullish or bearish) is calculated to predict the current trend. For more please check: Multi-TF AI SuperTrend with ADX - Strategy 🔶 Pivot Percentile Analysis 1. Percentile Calculation: - This involves calculating the percentile ranks for high and low prices over a set of predefined lengths. - The percentile function is typically defined as: - Percentile = Value at (P/100) × (N + 1)th position - Where P is the desired percentile, and N is the number of data points. 2. Trend Strength Evaluation: - The calculated percentiles for highs and lows are used to determine the strength of bullish and bearish trends. - For instance, a high percentile rank in the high prices may indicate a strong bullish trend, and vice versa for bearish trends. For more please check: Pivot Percentile Trend - Strategy 🔶 Strategy Integration 1. Combining SuperTrend and Pivot Percentile: - The strategy synthesizes the insights from both AI-enhanced SuperTrend and Pivot Percentile analysis. - It compares the trend direction indicated by the SuperTrend with the strength of the trend as suggested by the Pivot Percentile analysis. 2. Signal Generation: - A trading signal is generated when both the AI-enhanced SuperTrend and the Pivot Percentile analysis agree on the trend direction. - For instance, a bullish signal is generated when both the SuperTrend is bullish, and the Pivot Percentile analysis shows strength in bullish trends. 🔶 Risk Management and Filters - ADX and DMI Filter: The strategy uses the Average Directional Index (ADX) and the Directional Movement Index (DMI) as filters to assess the trend's strength and direction. - Dynamic Trailing Stop Loss: Based on the SuperTrend indicator, the strategy dynamically adjusts stop-loss levels to manage risk effectively. This strategy stands out for its ability to combine real-time AI analysis with established technical indicators, offering traders a nuanced and responsive tool for navigating complex market conditions. The equations and algorithms involved are pivotal in accurately identifying market trends and potential trade opportunities. █ Usage To effectively use this strategy, traders should: 1. Understand the AI and Pivot Percentile Indicators: A clear grasp of how these indicators work will enable traders to make informed decisions. 2. Interpret the Signals Accurately: The strategy provides bullish, bearish, and neutral signals. Traders should align these signals with their market analysis and trading goals. 3. Monitor Market Conditions: Given that this strategy is sensitive to market dynamics, continuous monitoring is crucial for timely decision-making. 4. Adjust Settings as Needed: Traders should feel free to tweak the input parameters to suit their trading preferences and to respond to changing market conditions. █Default Settings and Their Impact on Performance 1. Trading Direction (Default: "Both") Effect: Determines whether the strategy will take long positions, short positions, or both. Adjusting this setting can align the strategy with the trader's market outlook or risk preference. 2. AI Settings (Neighbors: 3, Data Points: 24) Neighbors: The number of nearest neighbors in the KNN algorithm. A higher number might smooth out noise but could miss subtle, recent changes. A lower number makes the model more sensitive to recent data but may increase noise. Data Points: Defines the amount of historical data considered. More data points provide a broader context but may dilute recent trends' impact. 3. SuperTrend Settings (Length: 10, Factor: 3.0, MA Source: "WMA") Length: Affects the sensitivity of the SuperTrend indicator. A longer length results in a smoother, less sensitive indicator, ideal for long-term trends. Factor: Determines the bandwidth of the SuperTrend. A higher factor creates wider bands, capturing larger price movements but potentially missing short-term signals. MA Source: The type of moving average used (e.g., WMA - Weighted Moving Average). Different MA types can affect the trend indicator's responsiveness and smoothness. 4. AI Trend Prediction Settings (Price Trend: 10, Prediction Trend: 80) Price Trend and Prediction Trend Lengths: These settings define the lengths of weighted moving averages for price and SuperTrend, impacting the responsiveness and smoothness of the AI's trend predictions. 5. Pivot Percentile Settings (Length: 10) Length: Influences the calculation of pivot percentiles. A shorter length makes the percentile more responsive to recent price changes, while a longer length offers a broader view of price trends. 6. ADX and DMI Settings (ADX Length: 14, Time Frame: 'D') ADX Length: Defines the period for the Average Directional Index calculation. A longer period results in a smoother ADX line. Time Frame: Sets the time frame for the ADX and DMI calculations, affecting the sensitivity to market changes. 7. Commission, Slippage, and Initial Capital These settings relate to transaction costs and initial investment, directly impacting net profitability and strategy feasibility.
Pine Script™ strategy
by PresentTrading
14
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.
Pine Script™ strategy
by PresentTrading
4
Double AI Super Trend Trading - Strategy [PresentTrading]█ Introduction and How It is Different The Double AI Super Trend Trading Strategy is a cutting-edge approach that leverages the power of not one, but two AI algorithms, in tandem with the SuperTrend technical indicator. The strategy aims to provide traders with enhanced precision in market entry and exit points. It is designed to adapt to market conditions dynamically, offering the flexibility to trade in both bullish and bearish markets. *The KNN part is mainly referred from @Zeiierman. BTCUSD 8hr performance ETHUSD 8hr performance █ Strategy, How It Works: Detailed Explanation 1. SuperTrend Calculation The SuperTrend is a popular indicator that captures market trends through a combination of the Volume-Weighted Moving Average (VWMA) and the Average True Range (ATR). This strategy utilizes two sets of SuperTrend calculations with varying lengths and factors to capture both short-term and long-term market trends. 2. KNN Algorithm The strategy employs k-Nearest Neighbors (KNN) algorithms, which are supervised machine learning models. Two sets of KNN algorithms are used, each focused on different lengths of historical data and number of neighbors. The KNN algorithms classify the current SuperTrend data point as bullish or bearish based on the weighted sum of the labels of the k closest historical data points. 3. Signal Generation Based on the KNN classifications and the SuperTrend indicator, the strategy generates signals for the start of a new trend and the continuation of an existing trend. 4. Trading Logic The strategy uses these signals to enter long or short positions. It also incorporates dynamic trailing stops for exit conditions. Local picture █ Trade Direction The strategy allows traders to specify their trading direction: long, short, or both. This enables the strategy to be versatile and adapt to various market conditions. █ Usage ToolTips: Comprehensive tooltips are provided for each parameter to guide the user through the customization process. Inputs: Traders can customize numerous parameters including the number of neighbors in KNN, ATR multiplier, and types of moving averages. Plotting: The strategy also provides visual cues on the chart to indicate bullish or bearish trends. Order Execution: Based on the generated signals, the strategy will execute buy or sell orders automatically. █ Default Settings The default settings are configured to offer a balanced approach suitable for most scenarios: Initial Capital: $10,000 Default Quantity Type: 10% of equity Commission: 0.1% Slippage: 1 Currency: USD These settings can be modified to suit various trading styles and asset classes.
Pine Script™ strategy
by PresentTrading
2
AI SuperTrend - Strategy [presentTrading] █ Introduction and How it is Different The AI Supertrend Strategy is a unique hybrid approach that employs both traditional technical indicators and machine learning techniques. Unlike standard strategies that rely solely on traditional indicators or mathematical models, this strategy integrates the power of k-Nearest Neighbors (KNN), a machine learning algorithm, with the tried-and-true SuperTrend indicator. This blend aims to provide traders with more accurate, responsive, and context-aware trading signals. *The KNN part is mainly referred from @Zeiierman. BTCUSD 8hr performance ETHUSD 8hr performance █ Strategy, How it Works: Detailed Explanation SuperTrend Calculation Volume-Weighted Moving Average (VWMA): A VWMA of the close price is calculated based on the user-defined length (len). This serves as the central line around which the upper and lower bands are calculated. Average True Range (ATR): ATR is calculated over a period defined by len. It measures the market's volatility. Upper and Lower Bands: The upper band is calculated as VWMA + (factor * ATR) and the lower band as VWMA - (factor * ATR). The factor is a user-defined multiplier that decides how wide the bands should be. KNN Algorithm Data Collection: An array (data) is populated with recent n SuperTrend values. Corresponding labels (labels) are determined by whether the weighted moving average price (price) is greater than the weighted moving average of the SuperTrend (sT). Distance Calculation: The absolute distance between each data point and the current SuperTrend value is calculated. Sorting & Weighting: The distances are sorted in ascending order, and the closest k points are selected. Each point is weighted by the inverse of its distance to the current point. Classification: A weighted sum of the labels of the k closest points is calculated. If the sum is closer to 1, the trend is predicted as bullish; if closer to 0, bearish. Signal Generation Start of Trend: A new bullish trend (Start_TrendUp) is considered to have started if the current trend color is bullish and the previous was not bullish. Similarly for bearish trends (Start_TrendDn). Trend Continuation: A bullish trend (TrendUp) is considered to be continuing if the direction is negative and the KNN prediction is 1. Similarly for bearish trends (TrendDn). Trading Logic Long Condition: If Start_TrendUp or TrendUp is true, a long position is entered. Short Condition: If Start_TrendDn or TrendDn is true, a short position is entered. Exit Condition: Dynamic trailing stops are used for exits. If the trend does not continue as indicated by the KNN prediction and SuperTrend direction, an exit signal is generated. The synergy between SuperTrend and KNN aims to filter out noise and produce more reliable trading signals. While SuperTrend provides a broad sense of the market direction, KNN refines this by predicting short-term price movements, leading to a more nuanced trading strategy. Local picture █ Trade Direction The strategy allows traders to choose between taking only long positions, only short positions, or both. This is particularly useful for adapting to different market conditions. █ Usage ToolTips: Explains what each parameter does and how to adjust them. Inputs: Customize values like the number of neighbors in KNN, ATR multiplier, and moving average type. Plotting: Visual cues on the chart to indicate bullish or bearish trends. Order Execution: Based on the generated signals, the strategy will execute buy/sell orders. █ Default Settings The default settings are selected to provide a balanced approach, but they can be modified for different trading styles and asset classes. Initial Capital: $10,000 Default Quantity Type: 10% of equity Commission: 0.1% Slippage: 1 Currency: USD By combining both machine learning and traditional technical analysis, this strategy offers a sophisticated and adaptive trading solution.
Pine Script™ strategy
by PresentTrading
14