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已更新 VWMA-KNN Supertrend Nifty 50

VWMA-KNN Supertrend
The strategy essentially bridges traditional technical analysis with modern data science techniques, making it a hybrid quantitative approach to market timing and trend identification. combining traditional technical indicators with predictive algorithms.
Why This Specific Combination?
Complementary Strengths:
1. VWMA → Filters noise, focuses on significant moves
2. Supertrend → Provides clear trend framework and stop-loss levels
3. KNN → Adds predictive intelligence and pattern recognition
4. Volume → Ensures all signals are backed by real market participation
Problem-Solution Mapping:
• Problem: Traditional Supertrend has lag and false signals
• Solution: VWMA reduces noise, KNN anticipates changes
• Problem: Pure ML can be unstable and overfitted
• Solution: Supertrend provides robust trend framework
• Problem: Many indicators ignore volume
• Solution: VWMA integration throughout
Synergistic Effects:
• Volume validation + Trend following + Pattern recognition = More reliable signals
• Each component covers weaknesses of the others
• Creates a multi-dimensional view: price, volume, volatility, and historical patterns
This combination attempts to create a "smart trend follower" that learns from history while staying grounded in proven technical analysis principles.
Trading Logic Flow
1. Enter initial positions based on signals
2. Monitor trend - force exit opposing positions if trend changes
3. If position moves against you by 120 points AND trend is still favorable, double down
4. Exit when profit targets are hit (targets decrease with position size)
5. Reset all tracking variables on exit
This strategy attempts to profit from mean reversion while respecting the overall trend direction, using martingale sizing to potentially recover from initial losses.
The strategy essentially bridges traditional technical analysis with modern data science techniques, making it a hybrid quantitative approach to market timing and trend identification. combining traditional technical indicators with predictive algorithms.
Why This Specific Combination?
Complementary Strengths:
1. VWMA → Filters noise, focuses on significant moves
2. Supertrend → Provides clear trend framework and stop-loss levels
3. KNN → Adds predictive intelligence and pattern recognition
4. Volume → Ensures all signals are backed by real market participation
Problem-Solution Mapping:
• Problem: Traditional Supertrend has lag and false signals
• Solution: VWMA reduces noise, KNN anticipates changes
• Problem: Pure ML can be unstable and overfitted
• Solution: Supertrend provides robust trend framework
• Problem: Many indicators ignore volume
• Solution: VWMA integration throughout
Synergistic Effects:
• Volume validation + Trend following + Pattern recognition = More reliable signals
• Each component covers weaknesses of the others
• Creates a multi-dimensional view: price, volume, volatility, and historical patterns
This combination attempts to create a "smart trend follower" that learns from history while staying grounded in proven technical analysis principles.
Trading Logic Flow
1. Enter initial positions based on signals
2. Monitor trend - force exit opposing positions if trend changes
3. If position moves against you by 120 points AND trend is still favorable, double down
4. Exit when profit targets are hit (targets decrease with position size)
5. Reset all tracking variables on exit
This strategy attempts to profit from mean reversion while respecting the overall trend direction, using martingale sizing to potentially recover from initial losses.
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仅限邀请脚本
只有经作者批准的用户才能访问此脚本。您需要申请并获得使用权限。该权限通常在付款后授予。如需了解更多详情,请按照以下作者的说明操作,或直接联系pavithrashetty1605。
除非您完全信任其作者并了解脚本的工作原理,否則TradingView不建议您付费或使用脚本。您还可以在我们的社区脚本中找到免费的开源替代方案。
作者的说明
DM me for free access pavithrashetty1605
提醒:在请求访问权限之前,请阅读仅限邀请脚本指南。
免责声明
这些信息和出版物并不意味着也不构成TradingView提供或认可的金融、投资、交易或其它类型的建议或背书。请在使用条款阅读更多信息。