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Persistence of volatility in futures markets

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  • Zhiyao Chen
  • Robert T. Daigler
  • Ali M. Parhizgari

Abstract

This article examines the characteristics of key measures of volatility for different types of futures contracts to provide a better foundation for modeling volatility behavior and derivative values. Particular attention is focused on analyzing how different measures of volatility affect volatility persistence relationships. Intraday realized measures of volatility are found to be more persistent than daily measures, the type of GARCH procedure used for conditional volatility analysis is critical, and realized volatility persistence is not coherent with conditional volatility persistence. Specifically, although there is a good fit between the realized and conditional volatilities, no coherence exists between their degrees of persistence, a counterintuitive finding that shows realized and conditional volatility measures are not a substitute for one another. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:571–594, 2006

Suggested Citation

  • Zhiyao Chen & Robert T. Daigler & Ali M. Parhizgari, 2006. "Persistence of volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(6), pages 571-594, June.
    • Handle: RePEc:wly:jfutmk:v:26:y:2006:i:6:p:571-594
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    Cited by:

    1. Junni L. Zhang & Wolfgang Karl Hardle & Cathy Y. Chen & Elisabeth Bommes, 2020. "Distillation of News Flow into Analysis of Stock Reactions," Papers 2009.10392, arXiv.org.
    2. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    3. Vera-Valdés, J. Eduardo, 2022. "The persistence of financial volatility after COVID-19," Finance Research Letters, Elsevier, vol. 44(C).
    4. Parhizgari, A.M. & Padungsaksawasdi, Chaiyuth, 2021. "Global equity market leadership positions through implied volatility measures," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 180-205.
    5. Bommes, Elisabeth & Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl, 2018. "Textual Sentiment and Sector specific reaction," IRTG 1792 Discussion Papers 2018-043, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    6. Frezza, Massimiliano & Bianchi, Sergio & Pianese, Augusto, 2021. "Fractal analysis of market (in)efficiency during the COVID-19," Finance Research Letters, Elsevier, vol. 38(C).
    7. Chi Ming Ho, 2013. "Private information, overconfidence and intraday trading behaviour: empirical study of the Taiwan stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 23(4), pages 325-345, February.
    8. S. Bhaumik & M. Karanasos & A. Kartsaklas, 2008. "Derivatives Trading and the Volume-Volatility Link in the Indian Stock Market," William Davidson Institute Working Papers Series wp935, William Davidson Institute at the University of Michigan.
    9. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti & Aris Kartsaklas, 2021. "Investors' trading behaviour and stock market volatility during crisis periods: A dual long‐memory model for the Korean Stock Exchange," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4441-4461, July.
    10. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    11. Charfeddine, Lanouar, 2014. "True or spurious long memory in volatility: Further evidence on the energy futures markets," Energy Policy, Elsevier, vol. 71(C), pages 76-93.
    12. Herrmann, Klaus & Teis, Stefan & Yu, Weijun, 2014. "Components of intraday volatility and their prediction at different sampling frequencies with application to DAX and BUND futures," FAU Discussion Papers in Economics 15/2014, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    13. Bachmair, K., 2023. "The Effects of the LIBOR Scandal on Volatility and Liquidity in LIBOR Futures Markets," Cambridge Working Papers in Economics 2303, Faculty of Economics, University of Cambridge.
    14. Chen, Feier & Miao, Yuqi & Tian, Kang & Ding, Xiaoxu & Li, Tingyi, 2017. "Multifractal cross-correlations between crude oil and tanker freight rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 344-354.
    15. Zhang, Junni L. & Härdle, Wolfgang Karl & Chen, Cathy Y. & Bommes, Elisabeth, 2015. "Distillation of news flow into analysis of stock reactions," SFB 649 Discussion Papers 2015-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

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