Detecting periods in which a time series model fails to predict the observed volatility

Andreas Stadie

Computational Statistics, 2003, vol. 18, issue 3, 375-386

Abstract: The cumulative sums of squares (CUSUMSQ) provide a means for detecting change points in the volatility (variance) of time series. In this paper a new method for detecting such change points is proposed. The method is based on a combination of two existing algorithms and is intended to combine their positive features in a single algorithm. The results of a simulation experiment to compare the performance of the algorithms are presented and, as an example, the algorithm is applied to the CUSUMSQ of pseudo-residuals. This provides a method of detecting periods in which a time series model fails to predict the observed volatility. Copyright Physica-Verlag 2003

Keywords: variance change points; CUSUMSQ; pseudo-residuals; evaluating density forecasts; volatility (search for similar items in EconPapers)
Date: 2003
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:18:y:2003:i:3:p:375-386

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DOI: 10.1007/BF03354604

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