Open AccessCAViaR and the Empirical Study on China’s Stock Market
Author(s) -
Daming Wu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012096
Subject(s) - composite index , stock market , econometrics , stock exchange , autoregressive conditional heteroskedasticity , economics , stock market index , autoregressive model , china , index (typography) , financial economics , imperfect , stock (firearms) , value at risk , market risk , volatility (finance) , risk management , geography , finance , computer science , linguistics , context (archaeology) , philosophy , archaeology , world wide web
The patterns of China’s stock market during 2004 and 2020 are characterized by Value at Risks (VaR) of 3 important stock indexes: Shanghai Security Composite index (SSEC), Shanghai Stock Exchange B Share index (SHBSHR) and Shenzhen Security Component index (SZSC), applying conditional autoregressive value at risk (CAViaR) model. The estimation results fit the real situation well. The unique style of news impact curves illustrates the peculiarity of China’s stock market caused by imperfect market mechanism and the small traders’ psychology-overconfidence. By comparing the estimation results, we found that SAV was a proper model for calculating 1% VaR of both SSEC and SHBSHR, while it was better for SZSC to choose Indirect GARCH model for 1% VaR estimation.