Influence of Covid-19 Outbreak Control Policies on the China Stock Market Price Investigated by LSTM Forecasting Models

With the volatility in stock prices during the Covid-19 outbreak, stock price prediction has become critical to investors in several industries. Predicting the stock price in China became a challenge since China has provided several rigorous Covid-19 outbreak control policies which could influence the China stock price. We investigated the prediction performance of the Long-Short Term Memory (LSTM) with the application of Adam optimizer to explain the influence of Covid-19 outbreak control policies on stock prices during this volatility period. We collected the training and testing datasets from several industries between January 2020 and February 2023. We measured the prediction performances using the coefficient of determination 7(r²) before leveraging to explain the correlation between Covid-19 pandemic control policies and the stock closing prices. The results show a correlation significant between the stock closing prices and the pandemic control policies observed through sample industries in the stock market. This study substantiated that pandemic control policies can impact stock prices. We adopted the features importance evaluation technique, Shapley Additive Explanations (SHAP), to interpret the influence of observed attributes on each prediction model.