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This article discusses the challenges faced by investors seeking to apply machine learning in electronic trading environments and provides a guide on how to enhance the accuracy of machine learning models for time series analysis. By focusing on predicting technical indicator values rather than security price changes, accuracy can be improved to around 70%. The article also includes step-by-step instructions using Python and MQL5 to analyze historical data from a MetaTrader 5 terminal.
