Academic Journal of Business & Management, 2022, 4(5); doi: 10.25236/AJBM.2022.040503.
Qianxiao Fei, Yuwei Xiang
SHIEN-MING WU School of Intelligent Engineering, South China University of Technology, Guangzhou, Guangdong, 510000, China
Stock is one of the major financial management methods in today's society, and its index prediction method is widely on research. Stock index is regarded as an important stock market analysis indicators, precise prediction and analysis of stock index can effectively reflect the current stock fair situation. This paper summarizes the existing forecasting methods in the current academic research, the use of relevant data to analyze the accuracy of the newly established model and according to the prediction characteristics and prediction objects of different forecasting methods, the deep neural network is applied to the prediction of stock index. Taking the Shanghai Stock Exchange 50 (SSE 50) stock index as the research object, long short term memory (LSTM)and Convolutional Neural Networks-Long short term memory (CNN-LSTM) helps to established a high accuracy stock index prediction model. The static and rolling data prediction results show that CNN-LSTM model has high accuracy in prediction and is more suitable for investors to use in investment decisions.
CNN; LSTM; CNN-LSTM; Stock Index Prediction
Qianxiao Fei, Yuwei Xiang. Forecast of Shanghai Stock Exchange 50 Stock Index Based on CNN-LSTM. Academic Journal of Business & Management (2022) Vol. 4, Issue 5: 10-14. https://doi.org/10.25236/AJBM.2022.040503.
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