Dự báo giá trị chịu rủi ro và thua lỗ dự kiến tại thị trường chứng khoán Việt Nam với phân phối xác suất biến thiên theo thời gian
DOI:
https://doi.org/10.24311/jabes/2023.34.3.7Keywords:
Value at Risk, Expected Shortfall, Backtesting, Time Series ForecastingAbstract
This paper explores the role of time-varying higher moments in the conditional distribution of financial returns in Vietnam. In particular, the author examines the forecasting performance of several GARCH-type models with alternative conditional distributions in predicting Value at Risk and Expected Shortfall for VN-Index and HNX-Index in both 1% and 5% quantiles over a battery of backtesting methods. Our horserace indicates that the GJR-ACD model with time-varying higher moments and Skewed Generalized Error conditional distribution consistently and significantly outperforms other methods. Our findings highlight the role of allowing for time-varying higher moments in VaR and ES forecasts in Vietnam, which is of particular importance for practitioners and market participants.
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