Analysis and Prediction of China Stock Market Return Based on BP Neural Network

Yize Zhang

Chapter 55 in Internet Finance and Digital Economy:Advances in Digital Economy and Data Analysis Technology, 2023, pp 739-753 from World Scientific Publishing Co. Pte. Ltd.

Abstract: It is difficult to find rules in the huge stock system, but we can enter from a small entrance, explore the inextricable links between the market return and some time series variables, and predict the overall return based on these variables. This paper first explains the relationship between the following economic and financial time series variables and market return, then explain the reasons for choosing them: CPI, momentum, dividend rate, market book ratio, P/E ratio, a turnover rate of trading volume calculation, market-capitalization-weighted idiosyncratic volatility, logarithm of stock market liquidity index, Amihud illiquidity index, skew; secondly, this paper uses Python to make descriptive statistical analysis of these variable data; Thirdly, it plots variables and yields to compare trends; Then, it constructs a neural network model by multiple regression to select significantly correlated variables; Finally, the BP neural network is used to predict the return of China’s stock market.

Keywords: Internet Economy; Online Finance; Financial Engineering; Big Data; Blockchain; Supply Chain; E-commerce (search for similar items in EconPapers)
JEL-codes: G2 O33 (search for similar items in EconPapers)
Date: 2023
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