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Forecasting gains of robust realized variance estimators: evidence from European stock markets

Author

Listed:
  • Prateek Sharma

    (Indian Institute of Management, Lucknow (IIML))

  • Swati Sharma

    (Jawaharlal Nehru University (JNU))

Abstract

The classical realized variance (RV) estimator is biased due to microstructure effects and asset price jumps. Robust realized variance (RRV) estimators adjust for these biases, and make more efficient of use of the intraday data. This article examines the benefits of using RRV estimators instead of the RV estimator, in the context of volatility forecasting. The recently proposed Realized GARCH framework is used to generate daily forecasts of the conditional variance for eight European stock indices. The out-of-sample comparisons indicate that the RRV estimators improve upon the RV estimator on efficiency and bias criteria.

Suggested Citation

  • Prateek Sharma & Swati Sharma, 2015. "Forecasting gains of robust realized variance estimators: evidence from European stock markets," Economics Bulletin, AccessEcon, vol. 35(1), pages 61-69.
    • Handle: RePEc:ebl:ecbull:eb-15-00042
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Realized Variance; Realized GARCH; realized kernel; forecasting; volatility; Bipower variation; Microstructure noise;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G0 - Financial Economics - - General

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