Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting

Riksbank Research Paper Series No. 133

Sveriges Riksbank Working Paper Series No. 309

35 Pages Posted: 22 Dec 2015

See all articles by Andre Lucas

Andre Lucas

Vrije Universiteit Amsterdam; Tinbergen Institute

Xin Zhang

Sveriges Riksbank - Research Division

Multiple version iconThere are 2 versions of this paper

Date Written: September 2015

Abstract

A simple methodology is presented for modeling time variation in volatilities and other higher-order moments using a recursive updating scheme similar to the familiar RiskMetrics(TM) approach. We update parameters using the score of the forecasting distribution. This allows the parameter dynamics to adapt automatically to any nonnormal data features and robustifies the subsequent estimates. The new approach nests several of the earlier extensions to the exponentially weighted moving average (EWMA) scheme. In addition, it can easily be extended to higher dimensions and alternative forecasting distributions. The method is applied to Value-at-Risk forecasting with (skewed) Student's t distributions and a time-varying degrees of freedom and/or skewness parameter. We show that the new method is competitive to or better than earlier methods in forecasting volatility of individual stock returns and exchange rate returns.

Keywords: dynamic volatilities, dynamic higher-order moments, integrated generalized autoregressive score models, Exponentially Weighted Moving Average (EWMA), Value-at-Risk (VaR)

JEL Classification: C51, C52, C53, G15

Suggested Citation

Lucas, Andre and Zhang, Xin, Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting (September 2015). Riksbank Research Paper Series No. 133, Sveriges Riksbank Working Paper Series No. 309, Available at SSRN: https://ssrn.com/abstract=2706535 or http://dx.doi.org/10.2139/ssrn.2706535

Andre Lucas

Vrije Universiteit Amsterdam ( email )

SBE/EDS, De Boelelaan 1105
Amsterdam, 1081 HV
Netherlands
+31 20 598 6039 (Phone)
+31 20 598 6020 (Fax)

HOME PAGE: http://personal.vu.nl/a.lucas

Tinbergen Institute

Roetersstraat 31
Amsterdam, 1018 WB
Netherlands

HOME PAGE: http://www.tinbergen.nl

Xin Zhang (Contact Author)

Sveriges Riksbank - Research Division ( email )

S-103 37 Stockholm
Sweden

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
108
Abstract Views
851
Rank
225,965
PlumX Metrics