Varying the VaR for unconditional and conditional environments

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Title: Varying the VaR for unconditional and conditional environments
Authors: Cotter, John
Permanent link: http://hdl.handle.net/10197/1138
Date: 2004
Abstract: Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from twelve European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme value theory are statistically robust explicitly allowing for fat-tailed densities. Conditional tail estimates are obtained by adjusting the unconditional extreme value procedure with GARCH filtered returns. The conditional modelling results in iid returns allowing for the use of a simple and efficient multi-period extreme value scaling law.The paper examines the properties of these distinct conditional and unconditional trading models. The paper finds that the biases inherent in unconditional single and multi-period estimates assuming normality extend to the conditional setting.
Type of material: Working Paper
Publisher: University College Dublin. School of Business. Centre for Financial Markets
Series/Report no.: Centre for Financial Markets working paper series; WP-04-06
Copyright (published version): Centre for Financial Markets, 2004
Keywords: Value at RiskGARCH filterExtreme value theoryConditional risk
Subject LCSH: Risk--Econometric models
Extreme value theory
Econometric models
Other versions: http://www.ucd.ie/bankingfinance/docs/wp/COTTER2.PDF
Language: en
Status of Item: Not peer reviewed
Appears in Collections:Centre for Financial Markets Working Papers

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