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Efficiency and probabilistic properties of bridge volatility estimator


  • Lapinova, S.
  • Saichev, A.
  • Tarakanova, M.


We discuss the efficiency of the quadratic bridge volatility estimator in comparison with Parkinson, Garman–Klass and Roger–Satchell estimators. It is shown in particular that point and interval estimations of volatility, resting on the bridge estimator, are considerably more efficient than analogous estimations, resting on the Parkinson, Garman–Klass and Roger–Satchell ones.

Suggested Citation

  • Lapinova, S. & Saichev, A. & Tarakanova, M., 2013. "Efficiency and probabilistic properties of bridge volatility estimator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1439-1451.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:6:p:1439-1451 DOI: 10.1016/j.physa.2012.11.047

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    References listed on IDEAS

    1. Ramey, Garey & Ramey, Valerie A, 1995. "Cross-Country Evidence on the Link between Volatility and Growth," American Economic Review, American Economic Association, vol. 85(5), pages 1138-1151, December.
    2. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    3. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    5. Chou, Ray Yeutien & Liu, Nathan, 2010. "The economic value of volatility timing using a range-based volatility model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2288-2301, November.
    6. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    7. Kunitomo, Naoto, 1992. "Improving the Parkinson Method of Estimating Security Price Volatilities," The Journal of Business, University of Chicago Press, vol. 65(2), pages 295-302, April.
    8. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    9. Yacine Aït-Sahalia, 2005. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 351-416.
    10. Valenti, Davide & Spagnolo, Bernardo & Bonanno, Giovanni, 2007. "Hitting time distributions in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 311-320.
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