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Using information quality for volatility model combinations

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  • Vasyl Golosnoy
  • Yarema Okhrin

Abstract

This paper proposes updated methodology for volatility model combinations which account for the informational content of innovations. An adaptive measure of information quality serves for the selection of model weights in order to improve daily volatility forecasts. The information quality proxy is related to the size of unexpected shocks in the volatility process. Our approach is illustrated in an empirical study with German stock market data.

Suggested Citation

  • Vasyl Golosnoy & Yarema Okhrin, 2015. "Using information quality for volatility model combinations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1055-1073, June.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:6:p:1055-1073
    DOI: 10.1080/14697688.2012.739728
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    2. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.

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