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Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models

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  • Stavros Degiannakis
  • Evdokia Xekalaki

Abstract

A number of ARCH models are considered in the framework of evaluating the performance of a method for model selection based on a standardized prediction error criterion (SPEC). According to this method, the ARCH model with the lowest sum of squared standardized forecasting errors is selected for predicting future volatility. A number of statistical criteria, that measure the distance between predicted and inter-day realized volatility, are used to examine the performance of a model to predict future volatility, for forecasting horizons ranging from one day to 100 days ahead. The results reveal that the SPEC model selection procedure has a satisfactory performance in picking that model that generates 'better' volatility predictions. A comparison of the SPEC algorithm with a set of other model evaluation criteria yields similar findings. It appears, therefore, that it can be regarded as a tool in guiding the choice of the appropriate model for predicting future volatility, with applications in evaluating portfolios, managing financial risk and creating speculative strategies with options.

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Bibliographic Info

Article provided by Taylor and Francis Journals in its journal Applied Financial Economics.

Volume (Year): 17 (2007)
Issue (Month): 2 ()
Pages: 149-171

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Handle: RePEc:taf:apfiec:v:17:y:2007:i:2:p:149-171

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Citations

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Cited by:
  1. Timotheos Angelidis & Stavros Degiannakis, 2007. "Backtesting VaR Models: An Expected Shortfall Approach," Working Papers 0701, University of Crete, Department of Economics.
  2. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Simulated evidence on the distribution of the standardized one-step-ahead prediction errors in ARCH processes," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 3(1), pages 31-37, January.
  3. Angelidis, Timotheos & Degiannakis, Stavros, 2008. "Volatility forecasting: Intra-day versus inter-day models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 449-465, December.

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