Data Management

Aggregation Of Exponential Smoothing Processes With An Application To Portfolio Risk Evaluation

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Executive Summary

In this paper the authors propose a unified framework to analyze contemporaneous and temporal aggregation of exponential smoothing models. Focusing on a vector IMA (1, 1) model, they 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, they present an application dealing with Value-at-Risk (VaR) prediction at different sampling frequencies for an equally weighted portfolio composed of multiple indices.

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