elayden / Deep-Learning-Framework-for-Financial-Time-Series-Prediction-in-Python-Keras

Randomly partitions time series segments into train, development, and test sets; Trains multiple models optimizing parameters for development set, final cross-validation in test set; Calculates model’s annualized return, improvement from buy/hold, percent profitable trades, profit factor, max drawdown

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