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Estimation of volatility measures using high frequency data (in Russian)

Author

Listed:
  • Ilze Kalnina

    (Universite de Montreal, Montreal, Canada)

  • Natalia Sizova

    (Rice University, Houston, USA)

Abstract

The availability of high frequency intra-day observations has created a new paradigm in volatility measurement. New methods in conjunction with high-frequency data allow nonparametric estimation of daily volatility and its forecast, variance-covariance matrices, instantaneous volatility and the jump contribution to the total variance. We survey some methods of volatility measurement including the recent literature on volatility estimation with ultra-high-frequency data in the presence of the market microstructure noise. We also discuss challenges specific to the estimation of the variance-covariance matrices with asynchronous observations.

Suggested Citation

  • Ilze Kalnina & Natalia Sizova, 2015. "Estimation of volatility measures using high frequency data (in Russian)," Quantile, Quantile, issue 13, pages 3-14, May.
    • Handle: RePEc:qnt:quantl:y:2015:i:13:p:3-14
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    References listed on IDEAS

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