Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2014-07-22
Revision-Date: 2015-09-09
Number: 14-092/IV/DSF77
Author-Name: André Lucas
Author-Workplace-Name: VU University Amsterdam, the Netherlands
Author-Name: Xin Zhang
Author-Workplace-Name: Sveriges Riksbank, Sweden
Title: Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting
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 approach. We update parameters using the score of the forecasting distribution. This allows the parameter dynamics to adapt automatically to any non-normal 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.
Classification-JEL: C51, C52, C53, G15
Keywords: dynamic volatilities, time varying higher order moments, integrated generalized autoregressive score models, Exponential Weighted Moving Average (EWMA), Value-at-Risk (VaR)
File-Url: https://papers.tinbergen.nl/14092.pdf
File-Format: application/pdf
File-Size: 430051 bytes
Handle: RePEc:tin:wpaper:20140092