Estimating and forecasting portfolio’s Value-at-Risk with wavelet-based extreme value theory: Evidence from crude oil prices and US exchange rates

Rania Jammazi and Duc Khuong Nguyen

Journal of the Operational Research Society, 2017, vol. 68, issue 11, 1352-1362

Abstract: Abstract This article proposes a wavelet-based extreme value theory (W-EVT) approach to estimate and forecast portfolio’s Value-at-Risk (VaR) given the stylized facts and complex structure of financial data. Our empirical application to portfolios of crude oil prices and US dollar exchange rates shows that the W-EVT models provide an effective and powerful tool for gauging extreme moments and improving the accuracy of portfolio’s VaR estimates and forecasts after noise is removed from the original data.

Keywords: stochastic processes; wavelet analysis; extreme value theory; VaR; oil-exchange rate portfolios (search for similar items in EconPapers)
JEL-codes: C52 C53 G17 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (7)

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DOI: 10.1057/s41274-016-0133-z

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