Estimating and Forecasting Portfolio's Value-at-Risk with Wavelet-Based Extreme Value Theory: Evidence from Crude Oil Prices and Us Exchange Rates

11 Pages Posted: 24 Apr 2018

See all articles by Rania Jammazi

Rania Jammazi

Tunis El Manar University - Faculty of Economics and Management Sciences

Duc Khuong Nguyen

IPAG Business School

Date Written: January 2017

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

Suggested Citation

Jammazi, Rania and Nguyen, Duc Khuong, Estimating and Forecasting Portfolio's Value-at-Risk with Wavelet-Based Extreme Value Theory: Evidence from Crude Oil Prices and Us Exchange Rates (January 2017). Journal of the Operational Research Society, Vol. 68, Issue 11, 2017, Available at SSRN: https://ssrn.com/abstract=3161435 or http://dx.doi.org/10.1057/s41274-016-0133-z

Rania Jammazi (Contact Author)

Tunis El Manar University - Faculty of Economics and Management Sciences ( email )

11, balkiss Street
Tunis, Sousse 1061
Tunisia

Duc Khuong Nguyen

IPAG Business School ( email )

184 BD Saint Germain
Paris, 75006
France

HOME PAGE: http://www.ipag.fr/en/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
1
Abstract Views
145
PlumX Metrics