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On The Robustness Of Range-Based Volatility Estimators

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  • Ozgur (Ozzy) Akay
  • Mark D. Griffiths
  • Drew B. Winters
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    Abstract

    Abstract We empirically examine Parkinson's range-based volatility estimate in the federal funds market, which is unique because institutional regulations create a predictable pattern in interday volatility. We find that range-based volatility estimates and standard deviations produce the expected volatility pattern. We also find that at trading pressure points where microstructure noise should be greatest, range-based estimates are less than the standard deviations. Thus, we support the argument that range-based volatility estimates remove the upward bias created by microstructure noise. We find that the Parkinson method is the most efficient range-based volatility measure among a set of alternates in this market. Copyright (c) 2010 The Southern Finance Association and the Southwestern Finance Association.

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    Bibliographic Info

    Article provided by Southern Finance Association & Southwestern Finance Association in its journal Journal of Financial Research.

    Volume (Year): 33 (2010)
    Issue (Month): 2 ()
    Pages: 179-199

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    Handle: RePEc:bla:jfnres:v:33:y:2010:i:2:p:179-199

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    Cited by:
    1. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
    2. Çankaya, Serkan & Ulusoy, Veysel & Eken, Hasan/M., 2011. "The Behavior of Istanbul Stock Exchange Market: An Intraday Volatility/Return Analysis Approach," MPRA Paper 43656, University Library of Munich, Germany.
    3. Chen, Wei-Peng & Choudhry, Taufiq & Wu, Chih-Chiang, 2013. "The extreme value in crude oil and US dollar markets," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 191-210.

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