 Aggregation of exponential smoothing processes with an application to portfolio risk evaluationGiacomo Sbrana and Andrea Silvestrini Post-Print from HAL 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) Published in Journal of Banking and Finance, 2012, n.p. ⟨10.1016/j.jbankfin.2012.06.015⟩ There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00779483 DOI: 10.1016/j.jbankfin.2012.06.015 Access Statistics for this paper More papers in Post-Print from HAL |
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