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Most Efficient Homogeneous Volatility Estimators

Author

Listed:
  • Alexander I. SAICHEV

    (ETH Zurich)

  • Didier SORNETTE

    (ETH Zurich and Swiss Finance Institute)

  • Vladimir FILIMONOV

    (ETZ Zurich)

Abstract

We present a new theory of homogeneous volatility (and variance) estimators for arbitrary stochastic processes. The main tool of our theory is the parsimonious encoding of all the information contained in the OHLC prices for a given time interval by the joint distributions of the high-minusopen, low-minus-open and close-minus-open values, whose analytical expression is derived exactly for Wiener processes with drift. The efficiency of the new proposed estimators is favorably compared with that of the Garman-Klass, Roger-Satchell and maximum likelihood estimators.

Suggested Citation

  • Alexander I. SAICHEV & Didier SORNETTE & Vladimir FILIMONOV, 2009. "Most Efficient Homogeneous Volatility Estimators," Swiss Finance Institute Research Paper Series 09-35, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp0935
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    Citations

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    Cited by:

    1. Alexander Saichev & Didier Sornette & Vladimir Filimonov & Fulvio Corsi, 2009. "Homogeneous Volatility Bridge Estimators," Papers 0912.1617, arXiv.org.
    2. Andreea Röthig & Andreas Röthig & Carl Chiarella, 2015. "On Candlestick-based Trading Rules Profitability Analysis via Parametric Bootstraps and Multivariate Pair-Copula based Models," Research Paper Series 362, Quantitative Finance Research Centre, University of Technology, Sydney.

    More about this item

    Keywords

    Variance and volatility estimators; efficiency; homogeneous functions; Schwarz inequality; extremes of Wiener processes;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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