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Volatility Estimation with Price Quanta

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  • L. C. G. Rogers

Abstract

Volatility estimators based on high, low, opening and closing prices have been developed, and perform well on simulated data, but on real data they frequently give lower values for volatility than the simple open–close estimator. This may be due to the fact that for real data, the maximum (or minimum) price is often at the beginning or end of the day. While this could not happen if the observed process was log Brownian, it could happen if the observed process were log Brownian, but observed only to the nearest penny. We develop the theory of such approximations to derive the corrected versions of the basic estimators.

Suggested Citation

  • L. C. G. Rogers, 1998. "Volatility Estimation with Price Quanta," Mathematical Finance, Wiley Blackwell, vol. 8(3), pages 277-290, July.
    • Handle: RePEc:bla:mathfi:v:8:y:1998:i:3:p:277-290
    DOI: 10.1111/1467-9965.00056
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    Cited by:

    1. Igor Kliakhandler, 2007. "Execution edge of pit traders and intraday price ranges of soft commodities," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 343-350.
    2. Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012. "Stochastic volatility models including open, close, high and low prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
    3. Kazemilari, Mansooreh & Djauhari, Maman Abdurachman, 2015. "Correlation network analysis for multi-dimensional data in stocks market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 62-75.

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