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Economic policy uncertainty and volatility of treasury futures

Author

Listed:
  • Maojun Zhang

    (Suzhou University of Science and Technology)

  • Yang Zhao

    (Suzhou University of Science and Technology)

  • Jiangxia Nan

    (Suzhou University of Science and Technology)

Abstract

This paper investigates the relation between Treasury futures market volatility and economic policy uncertainty using GARCH-MIDAS. We formulated models with the realized volatility of Treasury futures, the level and volatility of economic policy uncertainty. We find that the realized volatility of Treasury futures and economic policy uncertainty play a significant role in the dynamics of long-run volatility in Treasury futures markets in China and United States.

Suggested Citation

  • Maojun Zhang & Yang Zhao & Jiangxia Nan, 2022. "Economic policy uncertainty and volatility of treasury futures," Review of Derivatives Research, Springer, vol. 25(1), pages 93-107, April.
  • Handle: RePEc:kap:revdev:v:25:y:2022:i:1:d:10.1007_s11147-021-09182-8
    DOI: 10.1007/s11147-021-09182-8
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    References listed on IDEAS

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    1. Michael W. Brandt & Kenneth A. Kavajecz & Shane E. Underwood, 2007. "Price discovery in the treasury futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(11), pages 1021-1051, November.
    2. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    3. Fang, Libing & Yu, Honghai & Li, Lei, 2017. "The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets," Economic Modelling, Elsevier, vol. 66(C), pages 139-145.
    4. Kasing Man & Junbo Wang & Chunchi Wu, 2013. "Price Discovery in the U.S. Treasury Market: Automation vs. Intermediation," Management Science, INFORMS, vol. 59(3), pages 695-714, September.
    5. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    8. Orlowski, Lucjan T., 2015. "From pit to electronic trading: Impact on price volatility of U.S. Treasury futures," Review of Financial Economics, Elsevier, vol. 25(C), pages 3-9.
    9. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    10. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    11. Weihua Shi & Larry Eisenberg & Cheng-few Lee, 2009. "Intraday Patterns, Announcement Effects, and Volatility Persistence in the Japanese Government Bond Futures Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 63-85.
    12. Ederington, Louis H & Lee, Jae Ha, 1993. "How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
    13. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    14. repec:bla:jfinan:v:59:y:2004:i:6:p:2623-2654 is not listed on IDEAS
    15. Mao‐Wei Hung & Hua Zhang, 1995. "Price movements and price discovery in the municipal bond index and the index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(4), pages 489-506, June.
    16. Wisniewski, Tomasz Piotr & Lambe, Brendan John, 2015. "Does economic policy uncertainty drive CDS spreads?," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 447-458.
    17. Huseyin Gulen & Mihai Ion, 2016. "Editor's Choice Policy Uncertainty and Corporate Investment," The Review of Financial Studies, Society for Financial Studies, vol. 29(3), pages 523-564.
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    Cited by:

    1. Zhang, Maojun & Zhang, Rongjia & Zhao, Yang, 2024. "Economic policy uncertainty and volatility of corporate bond credit spread: Evidence from China and the United States," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 827-841.

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