CAJ | 학술논문

本文同时使用日VaR和CVaR模型可实现对市场风险的双重监控，其估计一直是风险管理的重点。科技的发展使获得高频数据成为可能，由于其包含丰富波动信息，学者们开始利用它来研究日VaR和CVaR的估计问题。本文通过整合基于高频数据的CARR模型和非参数的极值理论EVT，实现对日VaR和CVaR的动态估计。上证和深圳综指的实证结果表明，与基于日度数据GARCH类模型和未与极值理论整合的CARR模型的VaR和CVaR相比，本文方法极大提高了估计拍维确．悻．同时所得仕讳豇右茱，辛新自-奔右尉响柏籀馇．件
본문동시사용일VaR화CVaR모형가실현대시장풍험적쌍중감공，기고계일직시풍험관리적중점。과기적발전사획득고빈수거성위가능，유우기포함봉부파동신식，학자문개시이용타래연구일VaR화CVaR적고계문제。본문통과정합기우고빈수거적CARR모형화비삼수적겁치이론EVT，실현대일VaR화CVaR적동태고계。상증화심수종지적실증결과표명，여기우일도수거GARCH류모형화미여겁치이론정합적CARR모형적VaR화CVaR상비，본문방법겁대제고료고계박유학．행．동시소득사휘강우수，신신자-분우위향백주사．건
Using daily VaR and CVaR simultaneously can doubly control mar ket risks. Their estimations are the key point of risk management. The rapid devel opment of science and technology makes it possible to obtain high frequent data. Because they have much information about volatility, scholars begin to study daily VaR and CVaR based on high frequent data. In the paper, we are to estimate daily VaR and CVaR by integrating the CARR model and extreme value theory. The em pirical analysis on Shanghai and Shenzhen composite indexes showes that, com pared with type of GARCH models based on daily data and CARR model not in tegrating extreme value theory, our method remarkably improves the accuracy of VaR and CVaR estimators. Moreover, the two estimators are robust to the distribu tion of new information.