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A comparative study of alternative extreme‐value volatility estimators

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  • Turan G. Bali
  • David Weinbaum
Abstract
Recent advances in econometric methodology and newly available sources of data are used to examine empirically the performance of the various extreme‐value volatility estimators that have been proposed over the past two decades. Overwhelming support is found for the use of extreme‐value estimators when computing daily volatility measures across all assets: Daily extreme‐value volatility estimators are both less biased and substantially more efficient than the traditional close‐to‐close estimator. In the case of weekly and monthly measures, the results still suggest that extreme‐value estimators are appropriate, but the evidence is more mixed. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:873–892, 2005

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  • Turan G. Bali & David Weinbaum, 2005. "A comparative study of alternative extreme‐value volatility estimators," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(9), pages 873-892, September.
    • Handle: RePEc:wly:jfutmk:v:25:y:2005:i:9:p:873-892
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    Cited by:

    1. Ozgur (Ozzy) Akay & Mark D. Griffiths & Drew B. Winters, 2010. "On The Robustness Of Range‐Based Volatility Estimators," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(2), pages 179-199, June.
    2. Agarwal, Vikas & Arisoy, Y. Eser & Naik, Narayan Y., 2017. "Volatility of aggregate volatility and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 125(3), pages 491-510.
    3. Arnerić, Josip & Matković, Mario & Sorić, Petar, 2019. "Comparison of range-based volatility estimators against integrated volatility in European emerging markets," Finance Research Letters, Elsevier, vol. 28(C), pages 118-124.
    4. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    5. Korkusuz, Burak & Kambouroudis, Dimos & McMillan, David G., 2023. "Do extreme range estimators improve realized volatility forecasts? Evidence from G7 Stock Markets," Finance Research Letters, Elsevier, vol. 55(PB).
    6. Ganneval, S., 2016. "Spatial price transmission on agricultural commodity markets under different volatility regimes," Economic Modelling, Elsevier, vol. 52(PA), pages 173-185.
    7. Molnár, Peter, 2012. "Properties of range-based volatility estimators," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 20-29.
    8. Mazza, Paolo & Petitjean, Mikael, 2016. "On the usefulness of intraday price ranges to gauge liquidity in cap-based portfolios," Economic Modelling, Elsevier, vol. 54(C), pages 67-81.
    9. Dar-Hsin Chen & Chun-Da Chen & Su-Chen Wu, 2014. "VaR and the cross-section of expected stock returns: an emerging market evidence," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(3), pages 441-459, June.
    10. Neda Todorova, 2012. "Volatility estimators based on daily price ranges versus the realized range," Applied Financial Economics, Taylor & Francis Journals, vol. 22(3), pages 215-229, February.
    11. Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
    12. I‐Ming Jiang & Jui‐Cheng Hung & Chuan‐San Wang, 2014. "Volatility Forecasts: Do Volatility Estimators and Evaluation Methods Matter?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(11), pages 1077-1094, November.
    13. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    14. Khoo, Zhi De & Ng, Kok Haur & Koh, You Beng & Ng, Kooi Huat, 2024. "Forecasting volatility of stock indices: Improved GARCH-type models through combined weighted volatility measure and weighted volatility indicators," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    15. Saad Mouti, 2023. "Rough volatility: evidence from range volatility estimators," Papers 2312.01426, arXiv.org, revised Sep 2024.
    16. Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.

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