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The empirical similarity approach for volatility prediction

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  • Golosnoy, Vasyl
  • Hamid, Alain
  • Okhrin, Yarema

Abstract

In this paper we adapt the empirical similarity (ES) concept for the purpose of combining volatility forecasts originating from different models. Our ES approach is suitable for situations where a decision maker refrains from evaluating success probabilities of forecasting models but prefers to think by analogy. It allows to determine weights of the forecasting combination by quantifying distances between model predictions and corresponding realizations of the process of interest as they are perceived by decision makers. The proposed ES approach is applied for combining models in order to forecast daily volatility of the major stock market indices.

Suggested Citation

  • Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
    • Handle: RePEc:eee:jbfina:v:40:y:2014:i:c:p:321-329
    DOI: 10.1016/j.jbankfin.2013.12.009
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    4. D. Schneller & S. Heiden & M. Heiden & A. Hamid, 2018. "Home is Where You Know Your Volatility – Local Investor Sentiment and Stock Market Volatility," German Economic Review, Verein für Socialpolitik, vol. 19(2), pages 209-236, May.
    5. Ralf Becker & Adam Clements & Robert O'Neill, 2018. "A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns," Econometrics, MDPI, vol. 6(1), pages 1-27, February.
    6. Demetrescu, Matei & Golosnoy, Vasyl & Titova, Anna, 2020. "Bias corrections for exponentially transformed forecasts: Are they worth the effort?," International Journal of Forecasting, Elsevier, vol. 36(3), pages 761-780.
    7. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    8. Seo, Sung Won & Kim, Jun Sik, 2015. "The information content of option-implied information for volatility forecasting with investor sentiment," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 106-120.
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    More about this item

    Keywords

    Case based decisions; Empirical similarity; Forecasting combinations; Volatility forecasts;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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