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Optimal Prediction Periods for New and Old Volatility Indexes in USA and German Markets

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Listed:
  • Javier Giner

    (University of La Laguna)

  • Sandra Morini

    (University of La Laguna)

  • Rafael Rosillo

    (University of León)

Abstract

In 1993, the Chicago Board of Options Exchange (CBOE) introduced the VXO, a volatility index based on implied volatilities on S&P 100 index. In 2003, the CBOE changed their volatility index design and introduced the VIX in order to enhance its economic significance and to facilitate hedging. In this paper, using data from the USA and the German stock markets, we compare the forecasting capability of the volatility indexes with that of historical volatility and conditional volatility models. Following this analysis, we have studied whether it may be the case that volatility indexes forecast the realized volatilities more accurately for a different period to 30 (or 45) days, attempting to answer the question: what time horizon is the informational content of volatility indexes best adjusted for? The optimal prediction period of each volatility index (VXO, VIX, VDAX and V1X) in terms of coefficient of determination is analysed. The results identify a difference between the observed optimal forecasting period and the theoretical one. This could be explained from different perspectives such as the index’s design, investor cognitive bias or overreaction.

Suggested Citation

  • Javier Giner & Sandra Morini & Rafael Rosillo, 2016. "Optimal Prediction Periods for New and Old Volatility Indexes in USA and German Markets," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 527-549, April.
    • Handle: RePEc:kap:compec:v:47:y:2016:i:4:d:10.1007_s10614-015-9500-0
    DOI: 10.1007/s10614-015-9500-0
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    References listed on IDEAS

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