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dc.contributor.author陈坚
dc.contributor.authorCHEN Jian
dc.date.accessioned2016-02-15T00:55:09Z
dc.date.available2016-02-15T00:55:09Z
dc.date.issued2014-08
dc.identifier.citation厦门大学学报(哲学社会科学版), 2014, 224 (4):45-54zh_CN
dc.identifier.issn0438-0460
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/94622
dc.description陈坚,厦门大学经济学院助理教授,经济学博士。zh_CN
dc.description.abstract【中文摘要】目前,在险价值(VaR)被广泛应用于风险管理与投资组合分析中,在股票市场,它表示股票收益的尾部风险。相关研究发现VaR对未来股票收益具有预测作用。根据Copula方法和极值理论方法分别构建VaR,考察其对中国股票市场是否具有样本内和样本外的预测能力,实证结果发现:与传统经济变量作对比,基于极值理论的VaR具有较强的预测能力,而基于Copula方法的VaR的预测效果并不十分显著。 【Abstract】Currently,Value-at-Risk (VaR) has been heavily used in risk management and investment analysis. On the stock market,VaR represents the tail risk of stock return distribution. Related studies show that VaR is able to predict future excess stock returns. In this paper,we construct VaR through the extreme value theory ( EVT) and the Copula method,and investigate the predictability of two VaR measures. Empirical results show that,compared with economic variables, the VaR based on EVT has strong in-sample and out-of-sample predictive power. By contrast, the predictability of VaR based on the Copula method is not very significant.zh_CN
dc.description.sponsorship国家自然科学基金项目“基于扇形偏好的一般均衡期权定价方法及其对股价跳跃的应用” (71201136)zh_CN
dc.language.isozhzh_CN
dc.publisher厦门大学学报(哲学社会科学版)编辑部zh_CN
dc.subject样本外预测zh_CN
dc.subjectout-of -sample predictionzh_CN
dc.subject极值理论zh_CN
dc.subjectextreme value theoryzh_CN
dc.subjectCopulazh_CN
dc.subjectVaRzh_CN
dc.subject尾部风险zh_CN
dc.subjecttail riskzh_CN
dc.title中国股票市场尾部风险与收益率预测——基于Copula与极值理论的VaR对比研究zh_CN
dc.title.alternativeChina's Stock Market Tail Risk and Return Prediction: A Contrastive Study of VaR Based on Copula and EVTzh_CN
dc.typeJournal Paperzh_CN


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