A Quantile Regression Approach to Estimate Value at Risk: Evidence from China Stock Market

Xiao-Rong Yang ； Chun He ； Jie Chen

《管理科學與統計決策》 10卷4期 (2013/12) Pp. 1-11

https://doi.org/10.6704/JMSSD.2013.10.4.1

並列摘要

Considering that the financial time series usually exhibit leptokurtosis, fat-tail, bias, clustering and leverage in reality, a quantile regression approach is applied to estimate the VaR (Value at Risk) in this paper. We build the quantile regression VaR model to compute VaR of Shanghai Composite Index, based on GARCH family models and different distributions of the residual. The back-testing is used to evaluate the performance of VaR estimations. The comparisons under various assumptions indicate that the proposed quantile regression VaR model is insensitive to both the model and the distribution of residual, which signifies that the model has excellent applicability. In addition, this paper suggests that the longer the holding period is, the better the performance is.

並列關鍵字

VaR Model ； GARCH Family Models ； VaR of Shanghai Composite Index

參考文獻

(Chen M Y, Chen J E (2002), Application of quantile regression to estimat ion of value at risk. National Chung-Cheng University).

Chen, Y,Luo, J,Yang, J(2011).A Study of Copper Future Market's VaR Measurement Based on Asymmetric GARCH Model.Journal of Chengdu University of Technology (Social Scieces).

Engle, R(2001).GARCH 101: The use of ARCH/GARCH models in applied econometrics.The Journal of Economic Perspectives.15(4),157-168.

Gong, R,Chen, Z C,Yang, D R(2005).To evaluate VaR of China stock marketing comparatively by using GARCH family model and comment.Quantitative & Technica Economis.67-81.

Jin, X,Xu, H Y(2007).Semi-parameter approach based on EGARCH-VaR model and empirical research.Journal of Northeastern University (Natural Scince).28(14),141-144.