Research on quantitative trading strategy based on LSTM

With the gradual maturity of the domestic financial quantitative trading market, more and more investors have recognized the quantitative investment because of its relatively stable income. Investment trading is not interfered by human beings. Analyzing the historical data of market trading has the characteristics of high probability of winning. This paper will take s300etf(159912) as an example, combine the double moving average and Counter-market operating indicator(CDP), explain the application law of the indicator, and discuss how to better grasp the market and achieve higher return on investment through the two indicators. Stock data is a classical financial time series, so Long Short-Term Memory(LSTM), as a classical model in the cyclic neural network model, can predict the trading index through LSTM. In this paper, the backtrader platform is used to simulate the transaction of historical data, and the benefits of the simulated transaction are discussed.