ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module

Yujin Baek, Ha Young Kim

Abstract: Highlights•Proposed a new modularized forecasting framework (ModAugNet) for stock market.•ModAugNet has two LSTM modules: overfitting Prevention Module and Prediction Module.•Found that Prevention Module helps to prevent network from overfitting when training.•Verified that ModAugNet significantly outperformed a model without Prevention Module.•Showed that test performance solely depends on test input of Prediction Module.