Combining non-constant weights with historical simulation VaR
Abstract
This paper shows how the historical simulation method can be extended to deal with a time series that displays different importance weights. The method is shown to be particularly useful in dealing with seasonality. It builds on the work by Hull and White (1998) about volatility rescaling, and it demonstrates some subtle points that arise in the presence of non-constant weights across time series.
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Author's Biography
Riccardo Rebonato is Global Head of Market Risk and Global Head of the Quantitative Research Team at RBS, a Visiting Lecturer at Oxford University (Mathematical Finance) and Adjunct Professor at Imperial College (Tanaka Business School). He sits on the Board of Directors of ISDA and on the Board of Trustees for GARP. He holds doctorates in nuclear engineering and solid state physics and was a research fellow in physics at Corpus Christi College, Oxford, UK. He is the author of the books Plight of the Fortune Tellers — Thoughts on the Quantitative Management of Financial Risk (2007), Volatility and Correlation in Option Pricing (1999, 2004), Modern Pricing of Interest-Rate Derivatives (2002) and Interest-Rate Option Models (1996, 1998). His papers on finance have been published in several academic journals.
Vasant Shanbhogue is Head of Quantitative Analysis for Gas and Power at RBS Sempra Commodities. Vasant has over 15 years’ experience in energy commodities markets and has held various roles covering market risk, credit risk and option and structured deal pricing.
Citation
Rebonato, Riccardo and Shanbhogue, Vasant (2010, September 1). Combining non-constant weights with historical simulation VaR. In the Journal of Risk Management in Financial Institutions, Volume 3, Issue 4. https://doi.org/10.69554/LQRV6937.
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