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Forecasting VaR using analytic higher moments for GARCH processes

journal contribution
posted on 2023-06-08, 15:22 authored by Carol AlexanderCarol Alexander, Emese Lazar, Stanescu Silvia
It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency of the GARCH model, such predictions have typically required time-consuming simulations of the aggregated returns distributions. This paper shows that fast, quasi-analytic GARCH VaR calculations can be based on new formulae for the first four moments of aggregated GARCH returns. Our extensive empirical study compares the Cornish–Fisher expansion with the Johnson SU distribution for fitting distributions to analytic moments of normal and Student t, symmetric and asymmetric (GJR) GARCH processes to returns data on different financial assets, for the purpose of deriving accurate GARCH VaR forecasts over multiple horizons and significance levels.

History

Publication status

  • Published

Journal

International Review of Financial Analysis

ISSN

1057-5219

Publisher

Elsevier

Volume

30

Page range

36-45

Department affiliated with

  • Business and Management Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2013-08-12

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