Stock Price Forecasting and Prediction in Python

In order to meet the needs of the financial industry and the financial market, effectively improve the rate of return on funds and avoid market risks, this paper proposes a stock price prediction model based on convolution neural network, which has obvious self-adaptability and self-learning ability. Combining the characteristics of CNN (Convolution Neural Network) and Thai stock market, the data set is trained and tested after pretreatment. On this basis, three stocks (BBL, CAPLL&PTT) listed on the Thai Stock Exchange are tested and compared with the actual stock price. The results show that the model based on CNN can effectively identify the changing trend of stock price and predict it which can provide valuable reference for stock price forecast. The prediction accuracy is high, and it is worth further promotion in the financial field.