Backtesting Trading Strategies with GAN To Avoid Overfitting

Many works have shown the overfitting hazard of selecting a trading strategy based only on good IS (in sample) performance. But most of them have merely shown such phenomena exist without offering ways to avoid them. We propose an approach to avoid overfitting: A good (meaning non-overfitting) trading strategy should still work well on paths generated in accordance with the distribution of the historical data. We use GAN with LSTM to learn or fit the distribution of the historical time series . ...