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Bridge homogeneous volatility estimators

Author

Listed:
  • A. Saichev
  • D. Sornette
  • V. Filimonov
  • F. Corsi

Abstract

We present a theory of bridge homogeneous volatility estimators for log-price stochastic processes. Starting with the standard definition of a Brownian bridge as the conditional Wiener process with two endpoints fixed, we introduce the concept of an incomplete bridge by breaking the symmetry between the two endpoints. For any given time interval, this allows us to encode the information contained in the open, high, low and close prices into an incomplete bridge. The efficiency of the new proposed estimators is favourably compared with that of the classical Garman--Klass and Parkinson estimators.

Suggested Citation

  • A. Saichev & D. Sornette & V. Filimonov & F. Corsi, 2014. "Bridge homogeneous volatility estimators," Quantitative Finance, Taylor & Francis Journals, vol. 14(1), pages 87-99, January.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:1:p:87-99
    DOI: 10.1080/14697688.2013.819985
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    References listed on IDEAS

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    1. 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.
    2. E. Bacry & S. Delattre & M. Hoffmann & J. F. Muzy, 2013. "Modelling microstructure noise with mutually exciting point processes," Quantitative Finance, Taylor & Francis Journals, vol. 13(1), pages 65-77, January.
    3. 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.
    4. 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.
    5. 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.
    6. Fulvio Corsi & Gilles Zumbach & Ulrich A. Muller & Michel M. Dacorogna, 2001. "Consistent High-precision Volatility from High-frequency Data," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 183-204, July.
    7. 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.
    8. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    9. Chan, Leo & Lien, Donald, 2003. "Using high, low, open, and closing prices to estimate the effects of cash settlement on futures prices," International Review of Financial Analysis, Elsevier, vol. 12(1), pages 35-47.
    10. Emmanuel Bacry & Sylvain Delattre & Marc Hoffmann & Jean-François Muzy, 2013. "Modelling microstructure noise with mutually exciting point processes," Post-Print hal-01313995, HAL.
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