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Is there an ideal in-sample length for forecasting volatility?

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  • Kambouroudis, Dimos S.
  • McMillan, David G.

Abstract

There is limited research carried out to date in the academic literature addressing the issue of the ideal in-sample size when forecasting volatility. This paper therefore considers how much data is required in order to produce accurate forecasts. Broadly speaking, two views exist between practitioners/investors who typically prefer a small in-sample to minimise data holding requirements and researchers/academics who typically chose large in-sample periods. Using a process of expanding window regressions where the in-sample start period expands (backward recursion) we conduct forecasts over twenty-three international markets, including both developed and emerging. Our findings, which demonstrate a degree of homogeneity, show that for the majority of the markets large in-sample periods are not necessary in order to produce the most accurate forecasts supporting the practitioners’/investors’ view.

Suggested Citation

  • Kambouroudis, Dimos S. & McMillan, David G., 2015. "Is there an ideal in-sample length for forecasting volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 114-137.
  • Handle: RePEc:eee:intfin:v:37:y:2015:i:c:p:114-137
    DOI: 10.1016/j.intfin.2015.02.006
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    References listed on IDEAS

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    More about this item

    Keywords

    Forecasting; In-sample; Stock market; Volatility;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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