JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2025, Vol. 60 ›› Issue (8): 21-33.doi: 10.6040/j.issn.1671-9352.0.2023.322

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Stock market risk measurement based on W-G-VaR model

ZHANG Hui1, WEI Jiaqi1, MENG Wenyu2, ZHU Qingfeng1   

  1. 1. School of Statistics and Mathematics, Shandong University of Finance and Economics, Jinan 250014, Shandong, China;
    2. School of Finance, Shandong University of Finance and Economics, Jinan 250014, Shandong, China
  • Published:2025-07-25

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Abstract: In order to verify that capturing the uncertainty features of the probability distribution of financial time series based on different frequency domain scales can effectively improve the measurement accuracy of VaR model, the W-G-VaR model is constructed by combining wavelet multi-resolution analysis with nonlinear expectation theory for the first time. Standard & Poors 500 composite stock price index(S& P 500 Index)and Shanghai(securities)composite index are selected as samples for empirical analysis. The results show that, compared to the G-VaR model, the W-G-VaR model constructed from the dual perspectives of the time domain and the frequency domain has more accurate risk measurement results throughout the sample period, especially during the occurrence of major risks, and the size of the window when capturing uncertainties does not affect the superiority of the W-G-VaR model.

Key words: wavelet multi-resolution analysis, nonlinear expectation theory, W-G-VaR model, tail risk

CLC Number: 

  • O211.9
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