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Analytic Approximations to GARCH Aggregated Returns Distributions with Applications to VaR and ETL
Year Of Publication: 2011
Month Of Publication: May
Pages: 28
Download Count: 3
View Count: 2012
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 6-9-2011
Publisher: Administrator
It is widely accepted that some of the most accurate predictions of aggregated asset returns are based on an appropriately specified GARCH process. As the forecast horizon is greater than the frequency of the GARCH model, such predictions either require time-consuming simulations or they can be approximated using a recent development in the GARCH literature, viz. analytic conditional moment formulae for GARCH aggregated returns. We demonstrate that this methodology yields robust and rapid calculations of the Value-at-Risk (VaR) generated by a GARCH process. Our extensive empirical study applies Edgeworth and Cornish-Fisher expansions and Johnson SU distributions, combined with normal and Student t, symmetric and asymmetric (GJR) GARCH processes to returns data on different financial assets; it validates the accuracy of the analytic approximations to GARCH aggregated returns and derives GARCH VaR estimates that are shown to be highly accurate over multiple horizons and significance levels.
This is an early version of the paper published in International Review of Financial Analysis (2013).
Alexander, Carol Sign in to follow this author
Lazar, Emese Sign in to follow this author
Stanescu, Silvia Sign in to follow this author
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