Combining Technical Indicators and Deep Learning by using LSTM Stock Price Predictor

A stock market price prediction is one of the most challenging tasks. There are many effected factors to make the stock market price go up or down such as dynamic environment, economy, politics. Thus, it is very difficult to predict a future price. Although, there are many technical indicators available for traders and investors at the present, the indicators might not be able to capture market behaviors. Nowadays, machine learning has more influence on the financial market prediction and trading strategies. This work introduced a stock market prediction by using the LSTM network model to predict future prices based on historical data. The model was trained in SET100 index from 2016 to 2019. Then, the model was tested through our trading operations on all stocks in SET100 in 2019 and 2020 to evaluate the profitable model. The experimental results show that the model is promising. The model in both long-only strategy and long-short strategy can achieve higher return than buy and hold, MACD, BB, RSI strategies both 2019 and 2020.