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Research on Stock Price Forecasting Model Based on Deep Learning

The stock market is a recognized complex dynamic system. Its influencing factors include abnormal state, nonlinearity, high noise, long storage time and so on. It is difficult to explain it with a simple mathematical model. The analysis and prediction of stock market is a very challenging subject. Due to the great progress of deep learning method in various fields, financial researchers began to apply it to the prediction of financial time series. It can extract high-level abstract features from a large number of original data. The stock market plays an increasingly important role in China's economic system. The change of stock market affects all aspects of social and economic life. Effectively predicting the change of stock price has important practical value. Compared with traditional methods, deep learning theory has strong self-learning ability and nonlinear approximation ability, can process a large number of stock prediction data, and has strong robustness and robustness. Nonlinear relations can solve complex problems.