Aggregation of exponential smoothing processes with an application to portfolio risk evaluation

Giacomo Sbrana and Andrea Silvestrini

No 2010039, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: In this paper we propose a unified framework to analyse contemporaneous and temporal aggregation of exponential smoothing (EWMA) models. Focusing on a vector IMA(1,1) model, we obtain a closed form representation for the parameters of the contemporaneously and temporally aggregated process as a function of the parameters of the original one. In the framework of EWMA estimates of volatility, we present an application dealing with Value-at-Risk (VaR) prediction at different sampling frequencies for an equally weighted portfolio composed of multiple indices. We apply the aggregation results by inferring the decay factor in the portfolio volatility equation from the estimated vector IMA(1,1) model of squared returns. Empirical results show that VaR predictions delivered using this suggested approach are at least as accurate as those obtained by applying the standard univariate RiskMetrics TM methodology.

Keywords: contemporaneous and temporal aggregation; EWMA; volatility; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C10 C32 C43 (search for similar items in EconPapers)
Date: 2010-07-01
New Economics Papers: this item is included in nep-ecm, nep-for and nep-rmg
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Related works:
Journal Article: Aggregation of exponential smoothing processes with an application to portfolio risk evaluation (2013)
Working Paper: Aggregation of exponential smoothing processes with an application to portfolio risk evaluation (2012)
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