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

Giacomo Sbrana and Andrea Silvestrini

Journal of Banking & Finance, 2013, vol. 37, issue 5, 1437-1450

Abstract: In this paper we propose a unified framework to analyse contemporaneous and temporal aggregation of a widely employed class of integrated moving average (IMA) models. 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. These results are useful due to the close analogy between the integrated GARCH (1,1) model for conditional volatility and the IMA (1,1) model for squared returns, which share the same autocorrelation function. In this framework, 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 aggregate parameter 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 standard univariate methodologies, such as RiskMetrics.

Keywords: Contemporaneous and temporal aggregation; ARIMA; Volatility; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C10 C32 C43 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Aggregation of exponential smoothing processes with an application to portfolio risk evaluation (2012)
Working Paper: Aggregation of exponential smoothing processes with an application to portfolio risk evaluation (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:37:y:2013:i:5:p:1437-1450

DOI: 10.1016/j.jbankfin.2012.06.015

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