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Analyzing Stock Market Volatility Using Extreme‐Day Measures

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  • Charles P. Jones
  • Mark D. Walker
  • Jack W. Wilson

Abstract

We develop a simple measure of volatility based on extreme‐day returns and apply it to market returns from 1885 to 2002. Because returns are not normally distributed, the extreme‐day measure, which is distribution free, might provide a better measure of stock market risk than the traditional standard deviation. The extreme‐day measure more accurately explains investor behavior relative to standard deviation as shown by equity fund flows, and we find evidence that large negative changes appear to influence investor behavior more than large positive changes.

Suggested Citation

  • Charles P. Jones & Mark D. Walker & Jack W. Wilson, 2004. "Analyzing Stock Market Volatility Using Extreme‐Day Measures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 27(4), pages 585-601, December.
    • Handle: RePEc:bla:jfnres:v:27:y:2004:i:4:p:585-601
    DOI: 10.1111/j.1475-6803.2004.00109.x
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    References listed on IDEAS

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    1. G. William Schwert, 1997. "Stock Market Volatility: Ten Years After the Crash," Center for Financial Institutions Working Papers 97-51, Wharton School Center for Financial Institutions, University of Pennsylvania.
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    2. Ahmed Naeem & Sarfraz Mudassira, 2018. "Stock Market Volatility Measure Using Non-Traditional Tool Case of Germany," Economics and Business, Sciendo, vol. 32(1), pages 126-135, July.
    3. J. Cuñado & L. Gil-Alana & F. Gracia, 2009. "US stock market volatility persistence: evidence before and after the burst of the IT bubble," Review of Quantitative Finance and Accounting, Springer, vol. 33(3), pages 233-252, October.
    4. Lean, Hooi Hooi & Teng, Kee Tuan, 2013. "Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach," Economic Modelling, Elsevier, vol. 32(C), pages 333-342.
    5. Imed Gammoudi & Lotfi BelKacem & Mohamed El Ghourabi, 2014. "Value at Risk Estimation for Heavy Tailed Distributions," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 8(3), pages 109-125.
    6. Ahmed, Mohamed S. & Alhadab, Mohammad, 2020. "Momentum, asymmetric volatility and idiosyncratic risk-momentum relation: Does technology-sector matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 355-371.
    7. Gil-Alana, Luis A. & Shittu, Olanrewaju I. & Yaya, OlaOluwa S., 2014. "On the persistence and volatility in European, American and Asian stocks bull and bear markets," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 149-162.
    8. Kee Tuan Teng & Siew Hwa Yen & Soo Y. Chua & Hooi Hooi Lean, 2016. "Time-Varying Linkages of Economic Activities in China and the Stock Markets in ASEAN-5," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 10(2), June.
    9. Hossein Niavand, & Farzaneh Haghighat Nia, 2017. "Globalization: The Relationship between Iran and India stock market," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 6(3), pages 1-31, august.
    10. Lorne N. Switzer & Jun Wang & Seungho Lee, 2017. "Extreme risk and small investor behavior in developed markets," Journal of Asset Management, Palgrave Macmillan, vol. 18(6), pages 457-475, October.
    11. Yan, Kai & Zhang, Wei & Shen, Dehua, 2020. "Stylized facts of the carbon emission market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).

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