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Circuit Breakers and the Tail Index of Equity Returns

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  • John W. Galbraith

Abstract

Using the tail index of returns on U.S. equities as a summary measure of extreme behavior, we examine changes in the equity markets surrounding the development of program trading for portfolio insurance, the crash of 1987, and the subsequent introduction of circuit breakers and other changes in market architecture. Recently-developed tests for the null of constancy of the tail index, versus the alternative of a change at an unknown date, permit inference on changes in extreme behavior over a long time period while allowing for second-moment dependence in the return data. We find strong evidence of a decrease in the tail index (increase in the probability of extreme events) around the beginning of large-scale program trading, and weaker, but still substantial, evidence of further significant change in the tail index following the introduction of circuit breakers. Point estimates of the tail index suggest that the tail index may have roughly regained pre-program trading levels. More generally, the results tend to suggest that long samples of U.S. equity returns should not be treated as samples from a single distribution function, particularly in examining extremes. Copyright 2004, Oxford University Press.

Suggested Citation

  • John W. Galbraith, 2004. "Circuit Breakers and the Tail Index of Equity Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 109-129.
  • Handle: RePEc:oup:jfinec:v:2:y:2004:i:1:p:109-129
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbh005
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    1. Christopher K. Ma & Ramesh P. Rao & R. Stephen Sears, 1989. "Limit moves and price resolution: The case of the treasury bond futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 9(4), pages 321-335, August.
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    5. Carmela Quintos & Zhenhong Fan & Peter C. B. Phillips, 2001. "Structural Change Tests in Tail Behaviour and the Asian Crisis," Review of Economic Studies, Oxford University Press, vol. 68(3), pages 633-663.
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    Cited by:

    1. Bryan Kelly & Hao Jiang, 2013. "Tail Risk and Asset Prices," NBER Working Papers 19375, National Bureau of Economic Research, Inc.
    2. Straetmans, Stefan & Candelon, Bertrand, 2013. "Long-term asset tail risks in developed and emerging markets," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 1832-1844.
    3. Escribano Sáez, Álvaro & Blazsek, Szabolcs Istvan & Ayala, Astrid, 2017. "Dynamic conditional score models with time-varying location, scale and shape parameters," UC3M Working papers. Economics 25043, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Lee, Chien-Chiang & Chiu, Yi-Bin, 2016. "Globalization and insurance activity: Evidence on the industrial and emerging countries," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 328-349.
    5. Wagner, Niklas, 2005. "Autoregressive conditional tail behavior and results on Government bond yield spreads," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 247-261.
    6. Riedel, Christoph & Wagner, Niklas, 2015. "Is risk higher during non-trading periods? The risk trade-off for intraday versus overnight market returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 53-64.
    7. John G. Galbraith & Serguei Zernov, 2006. "Extreme Dependence In The Nasdaq And S&P Composite Indexes," Departmental Working Papers 2006-14, McGill University, Department of Economics.
    8. Bollerslev, Tim & Todorov, Viktor, 2014. "Time-varying jump tails," Journal of Econometrics, Elsevier, vol. 183(2), pages 168-180.

    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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