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The Clustering of Extreme Movements: Stock Prices and the Weather

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  • Burton G. Malkiel

    (Princeton University)

  • Atanu Saha

    (AlixPartners)

  • Alex Grecu

    (Huron Consulting Group)

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    Abstract

    A striking feature of the United States stock market is the tendency of days with very large movements of stock prices to be clustered together. We define an extreme movement in stock prices as one that can be characterized as a three sigma event; that is, a daily movement in the broad stock-market index that is three or more standard deviations away from the average movement. We find that such extreme movements are typically preceded by, but not necessarily followed by, unusually large stock-price movements. Interestingly, a similar clustering of extreme observations of temperature in New York City can be observed. A particularly robust finding in this paper is that extreme movements in stock prices are usually preceded by larger than average daily movements during the preceding three-day period. This suggests that investors might fashion a market timing strategy, switching from stocks to cash in advance of predicted extreme negative stock returns. In fact, we have been able to simulate market timing strategies that are successful in avoiding nearly eighty percent of the negative extreme move days, yielding a significantly lower volatility of returns. We find, however, that a variety of alternative strategies do not improve an investor’s long-run average return over the return that would be earned by the buy-and-hold investor who simply stayed fully-invested in the stock market.

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    File URL: http://www.princeton.edu/ceps/workingpapers/186malkiel.pdf
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    Bibliographic Info

    Paper provided by Princeton University, Department of Economics, Center for Economic Policy Studies. in its series Working Papers with number 1162.

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    Date of creation: Feb 2009
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    Handle: RePEc:pri:cepsud:186malkiel

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    Related research

    Keywords: Volatility clustering; duration analysis; portfolio strategy;

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    References

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    1. Rogalski, Richard J, 1984. " New Findings Regarding Day-of-the-Week Returns over Trading and Non-trading Periods: A Note," Journal of Finance, American Finance Association, vol. 39(5), pages 1603-14, December.
    2. Robert J. Shiller & Pierre Perron, 1985. "Testing the Random Walk Hypothesis: Power versus Frequency of Observation," NBER Technical Working Papers 0045, National Bureau of Economic Research, Inc.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    4. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. French, Kenneth R., 1980. "Stock returns and the weekend effect," Journal of Financial Economics, Elsevier, vol. 8(1), pages 55-69, March.
    7. Gibbons, Michael R & Hess, Patrick, 1981. "Day of the Week Effects and Asset Returns," The Journal of Business, University of Chicago Press, vol. 54(4), pages 579-96, October.
    8. Bremer, Marc & Sweeney, Richard J, 1991. " The Reversal of Large Stock-Price Decreases," Journal of Finance, American Finance Association, vol. 46(2), pages 747-54, June.
    9. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
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