.png){kind=icon}
Return
Decay factor optimisation in time weighted simulation - Evaluating VaR performance
.png){kind=icon}
OA
AI
DOI：10.1016/j.ijforecast.2010.09.007.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We propose an optimisation approach for determining the optimal decay factor in time weighted (BRW) simulation. The backtesting of the BRW simulation, which involves different decay factors, together with a broad range of competing VaR models, has been performed on a sample of seven stock indexes and two commodities: gold and WTI oil. The results obtained show that the BRW simulation with an optimised decay factor relative to the Lopez (1998) size-adjusted function is among the best performing VaR models, second only to the conditional extreme value approach (McNeil & Frey, 2000). The optimised decay factors are sufficiently stable over time, giving economic justification to the optimisation because they do not change over longer time periods. Unlike most of the VaR models tested, in the large majority of cases, the optimised BRW model passes the Basel II criteria but yields significantly lower VaR forecasts than the extreme value approaches, thus resulting in a lower idle capital, i.e. lower costs. (C) 2011 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keywords:
Value at Risk
Time weighted (BRW) simulation
Optimisation
Decay factor
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.1
Papers:
3.1K
Citations:
9.9K
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSave
no more
no more