标题:VALUE AT RISK ESTIMATION BY COMBINING SEMI-PARAMETRIC DENSITY ESTIMATION WITH HISTORICAL SIMULATION
作者:Wang, Kaiping
作者机构:[Wang, KP]Shandong Univ, Sch Management, Jinan, Peoples R China.
通讯作者:Wang, KP
通讯作者地址:[Wang, KP]Shandong Univ, Sch Management, Jinan, Peoples R China.
来源:ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH
出版年:2012
卷:46
期:4
页码:163-178
关键词:Value at Risk; historical simulation; semi-parametric density; estimation; multiplicative adjustment; kernel estimation
摘要:The Value at Risk (VaR) has become a standard risk measure for financial assets. In this paper we propose an alternative way to implement the historical simulation approach to VaR estimation, utilizing a semi-parametric density estimation approach with multiplicative adjustment. The semi-parametric density estimator has the very same asymptotic variance as the standard non-parametric method, while there is substantial room for reducing the bias if the chosen parametric initial function belongs to a wide neighborhood around the true density function. We derive an expression for the pdf of any order statistic of the return distribution utilizing the semi-parametric method. The mean of the estimated pdf is the VaR estimate, and the standard deviation of the estimated pdf can be used to construct a confidence interval around the estimate. We apply this approach to four financial returns series.
收录类别:SCOPUS;SCIE;SSCI
WOS核心被引频次:1
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872904363&partnerID=40&md5=4922bff0c3b14efef2d1b2642eb22e70
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