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Estimation Adjusted VaR
Year Of Publication: 2012
Month Of Publication: July
Pages: 42
Download Count: 7
View Count: 1338
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 10-22-2012
Publisher: Administrator
Summary
Standard risk measures, such as the Value-at-Risk (VaR), or the Expected
Shortfall, have to be estimated and their estimated counterparts are subject to estimation uncertainty. Replacing, in the theoretical formulas, the true parameter value by an estimator based on n observations of the Profit and Loss variable, induces an asymptotic bias of order 1/n in the coverage probabilities. This paper shows how to correct for this bias by introducing a new estimator of the VaR, called Estimation adjusted VaR (EVaR). This adjustment allows for a joint treatment of theoretical and estimation risks, taking into account for their possible dependence. The estimator is derived for a general parametric dynamic model and is particularized to stochastic drift and volatility models. The finite sample properties of the EVaR estimator are studied by simulation and an empirical study of the S&P Index is proposed.
Author(s)
Gourieroux, Christian Sign in to follow this author
Zakoïan, Jean-Michel Sign in to follow this author
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