Resource title

Accurate Value-at-Risk forecast with the (good old) normal-GARCH model

Resource image

image for OpenScout resource :: Accurate Value-at-Risk forecast with the (good old) normal-GARCH model

Resource description

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.

Resource author

Christoph Hartz, Stefan Mittnik, Marc S. Paolella

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/25489

Resource license

Adapt according to the presented license agreement and reference the original author.