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- Data-mining And Validating Thousands Of Potential Price…
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- Quant Trading Without Neural Networks or Genetic Algorithms
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- The Most Important Performance Measure of Trading Strategies
- Identifying High Probability Short-term Patterns
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Category Archives: Trading System Design
The development of a trading strategy for FANG stocks was based on applying portfolio backtest validation during the identification phase. This was done for the purpose of reducing data-mining bias. This article outlines the steps followed and the results.
The TFADAPT and PSI trading systems were not data-mined. The latter is based on a formula from a text on probability and stochastic processes and the former uses a trend detection method that takes into account volatility.
Classical technical analysis has contributed to the largest non-violent wealth-redistribution in the history of mankind. Modern technical analysis is not doing any better.
Last April I wrote an article where I introduced a strict validation method for machine-designed trading algos. This article includes the forward performance of the trading algo in that article, as well as, of another algo that was machine-designed in … Continue reading
One would think that by backtesting more ideas and more frequently, the chances of discovering an edge increase. However, the opposite exactly happens: the chances of discovering something of value diminish with frequent backtesting.
The new system code feature of Price Action Lab significantly improves the code generation capabilities of the software by allowing trading algo generation from any number of price patterns, long, short or both.
I investigate the validity of claims that data prior to 2009 are obsolete for the purpose of trading system development. It is shown that a high proportion of profitable price patterns in more recent daily data maintain their profitability in past data. … Continue reading