• ISSN: 2301-3567 (Print), 2972-3981 (Online)
    • Abbreviated Title: J. Econ. Bus. Manag.
    • Frequency: Quarterly
    • DOI: 10.18178/JOEBM
    • Editor-in-Chief: Prof. Eunjin Hwang
    • Executive Editor: Ms. Fiona Chu
    • Abstracting/ Indexing:  CNKIGoogle ScholarCrossref
    • E-mail: joebm.editor@gmail.com
JOEBM 2022 Vol.10(1): 72-78 ISSN: 2301-3567
DOI: 10.18178/joebm.2022.10.1.676

Analysis and Forecast on the Price Change of Shanghai Stock Index

Qi Qi

Abstract—This paper selects the closing price data of Shanghai stock index from January 4, 2000 to June 2020 as the research data. Through ADF test, white noise test and ARCH effect test, it is found that the closing price sequence of Shanghai stock index has the characteristics of non-stationary and autocorrelation. Its first-order difference sequence is a stationary white noise sequence, and has the characteristics of peak thick tail and conditional heteroscedasticity, based on this, ARMA model and GARCH model are selected to model the data, and it is found that the closing price sequence of Shanghai stock index has leverage effect. At the same time, the model is further used to make short-term forecast, including dynamic forecast and static forecast for the time series data, and the conclusion is that GARCH(1,2) is the more favorable model, and the shortcomings of this analysis are pointed out.

Index Terms—Time series, ARMA model, GARCH model, Shanghai stock index, non-white noise series.

The author is with Shihezi University, Shihezi, Xinjiang Uygur Autonomous Region, 832000, China (e-mail: q17755517009@163.com).

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Cite:Qi Qi, "Analysis and Forecast on the Price Change of Shanghai Stock Index," Journal of Economics, Business and Management vol. 10, no. 1, pp. 72-78, 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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