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The Blue Owl Press hosts a series of articles that outline the trading system development procedures I recommend.  The website also has links to my books, my videos, justssr下载, and resources (including books, videos, and courses) related to the development of trading systems for stocks, commodities, futures, and ETFs.

The underlying approach is the scientific method.  Trading systems are combinations of models and data.  The data includes historical price and volume of traded securities.  The models are fit to the data in the development phase where patterns that precede profitable trades are identified, then validated using the walk forward process and forward testing of out-of-sample data to ensure that the trading systems are robust, profitable, and safe to trade.  

Traditional trading system development platforms, such as AmiBroker, TradeStation, and NinjaTrader, where the model is adjusted using backtesting and optimization are discussed.  Machine learning and artificial intelligence techniques using Python and the scikit-learn libraries are also described.

Measurements of goodness-of-fit, such as accuracy, expectancy, profitability, compound rate of growth, and drawdown are explained.  The advantages of state signals with mark-to-market evaluation over impulse signals are explained.  Several original and unique metrics, including safe-f and CAR25, are used to guide development, assess risk, and normalize results to enable comparison of alternative uses of funds. 

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Thoughtful discussion is welcome.

Dr. Howard Bandy

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