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主讲人 |
Feng Yao |
简介 |
<p> Abstract：We propse nonparametric estimators for conditional value-at-risk(VaR)and expected shortfall(ES)associated with conditional distributions of a series of returns on a financial asset.The return series and the conditioning covariates,which may include lagged returns and other exogenous variables,are assumed to be strong mixing and follow a fully nonparametric conditional location-scale model.First stage nonparametric estimators for location and scale are combined with a generalized Pareto approximation for distribution tails proposed by Pickands(1975)to give final estimators for conditional VaR and ES.We provide consistency and asymptotic normality of the proposed estimators under suitable normalization.We also present the results of a Monte Carlo study that sheds light on their finite sample performance. Empirical viability of the model and estimators is investigated through a backtesting exercise using returns on future contracts for five agricultural commodities.</p>
<p>Keywords and phrases: Value-at-risk, expected shortfall, extreme value theory, nonparametric locationscale models, strong mixing.</p>
<p><a href="/Events/Upload/File/2014/11/20141111051618121.pdf">Paper</a></p> |
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主讲人简介 |
<p> Associate Professor, Department of Economics, West Virginia University</p>
<p><a href="/Events/Upload/File/2014/11/2014111105160398.pdf">CV</a></p> |
期数 |
厦门大学高级计量经济学与统计学系列讲座2014秋季学期第五讲（总第48讲） |
