Jin Wang
ABSTRACT
With the continuous development of the digital economy and the maturity of artificial intelligence technology, coupled with the continuous development and innovation of the financial market, the in-depth application and progress of machine learning methods in the economic and financial fields have become a common pursuit of professionals in related industries. The emergence of various machine learning methods has facilitated the realization of the accurate price predictions in the financial industry. In view of this, this paper constructs a PSO-SVM price prediction model that integrates future market information to predict the price of the HS300 consumer index. Firstly, only the information related to the HS300 consume index is utilized to forecast the price of the HS300 consume index. Then, future market information is incorporated into the prediction model. The research result shows that introducing future market information leads to better prediction results, indicating that future market information indeed influences the price dynamics. It is necessary to introduce future market information to predict corresponding prices by using PSO-SVM price prediction model.
- Chen Qiang, Ye Azhong. Stock Returns, return volatility and Chinese urban resident consumption behavior [J]. Economic Research (Quarterly), 2009, 8(3):995-1012.Google Scholar
- Hu Yonggang, Guo Changlin. Stock wealth, signal transmission and Chinese urban resident consumption [J]. Economic Research, 2012, 47(3):115-126.Google Scholar
- Minami, S. Predicting equity price with corporate action events using LSTM-RNN [J]. Journal of Mathematical Finance, 2018, 8(1): 58-63.Google ScholarCross Ref
- Zhang, H. L. The forecasting model of stock price based on PCA and BP Neural Network[J]. Journal of financial risk management, 2018, 7(4):369-385.Google Scholar
- Li Zhichao, Liu Sheng. A comparative study of forecasting based on ARIMA grey model and regression model [J]. Statistics and Decision, 2019, 35(23):38-41.Google Scholar
- Ince H, Trafalis T B. Short term forecasting with support vector machines and application to stock price prediction [J]. International Journal of General Systems, 2008, 37(6):677-687.Google ScholarCross Ref
- Liu X, Ma X. Based on BP Neural Network Stock Prediction[J]. Journal of Curriculum and Teaching, 2012, 1(1):45-50.Google ScholarCross Ref
- Hsu S H, Hsieh J J P A, Chih T C, A two-stage architecture for stock price forecasting by integrating self-organizing map and support vector regression[J]. Expert Systems with Applications, 2009, 36(4):7947-7951.Google ScholarDigital Library
- Vatanparast M, Asadi M, Mohammadi S, Stock price prediction based on LM-BP neural network and over-point estimation by counting time intervals: Evidence from the Stock Exchange[J]. Financial Engineering and Portfolio Management, 2019, 10(39):193-218.Google Scholar
- Lu W, Li J, Wang J, A CNN-BiLSTM-AM method for stock price prediction[J]. Neural Computing and Applications, 2021(33): 4741-4753.Google Scholar
- Hua Renhai, Liu Qingfu. An investigation into the price discovery ability between stock index futures and stock index spot market[J]. Quantitative Economics & Technical Economic Research, 2010, 27(10):90-100.Google Scholar
Index Terms
- Price Prediction of HS 300 Consumer Index Based on PSO-SVM and Futures Market Information
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