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Nonlinear duration dependence in stock market cycles

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  • Yvette S. Harman
  • Thomas W. Zuehlke

Abstract

We reexamine duration dependence in stock market cycles using a generalized Weibull model. Recent empirical work by Cochran and DeFina [Cochran, S. J., & DeFina, R. H. (1995). Duration dependence in the U.S. stock market cycle: A parametric approach. Applied Financial Economics, 5, 309–318.], who use a chronology of stock market cycles to estimate a Weibull hazard model, shows duration dependence in stock prices. They find evidence of duration dependence in prewar market expansions and postwar market contractions. We update their postwar sample, then use a more flexible model that finds evidence of duration dependence for all prewar and postwar samples. The generalized Weibull model is shown to be statistically superior to the conventional Weibull model for all samples except prewar expansions.

Suggested Citation

  • Yvette S. Harman & Thomas W. Zuehlke, 2007. "Nonlinear duration dependence in stock market cycles," Review of Financial Economics, John Wiley & Sons, vol. 16(4), pages 350-362.
  • Handle: RePEc:wly:revfec:v:16:y:2007:i:4:p:350-362
    DOI: 10.1016/j.rfe.2006.08.001
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    References listed on IDEAS

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    1. Sichel, Daniel E, 1991. "Business Cycle Duration Dependence: A Parametric Approach," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 254-260, May.
    2. John Y. Campbell, 2000. "Asset Pricing at the Millennium," Journal of Finance, American Finance Association, vol. 55(4), pages 1515-1567, August.
    3. Thomas Zuehlke, 2003. "Estimation of a Tobit model with unknown censoring threshold," Applied Economics, Taylor & Francis Journals, vol. 35(10), pages 1163-1169.
    4. Zuehlke, Thomas W, 2003. "Business Cycle Duration Dependence Reconsidered," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(4), pages 564-569, October.
    5. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1, March.
    6. Francis X. Diebold & Glenn Rudebusch & Daniel Sichel, 1993. "Further Evidence on Business-Cycle Duration Dependence," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 255-284, National Bureau of Economic Research, Inc.
    7. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886, December.
    8. John G. Cragg & Russell S. Uhler, 1970. "The Demand for Automobiles," Canadian Journal of Economics, Canadian Economics Association, vol. 3(3), pages 386-406, August.
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    Cited by:

    1. Vitor Castro, 2013. "The Portuguese stock market cycle: Chronology and duration dependence," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(1), pages 1-23.
    2. Si, Deng-Kui & Liu, Xi-Hua & Kong, Xianli, 2019. "The comovement and causality between stock market cycle and business cycle in China: Evidence from a wavelet analysis," Economic Modelling, Elsevier, vol. 83(C), pages 17-30.
    3. Maryam Akbari Nasiri, 2020. "How Long Do Housing Cycles Last? A Duration Analysis For Emerging Economies," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 23(2), pages 179-200, July.
    4. Xiao-Lin Li & Yi-Na Li & Lu Bai, 2019. "Stock Market Cycle and Business Cycle in China: Evidence from a Bootstrap Rolling Window Approach," Review of Economics & Finance, Better Advances Press, Canada, vol. 17, pages 35-50, August.
    5. Valeriy Zakamulin, 2023. "Not all bull and bear markets are alike: insights from a five-state hidden semi-Markov model," Risk Management, Palgrave Macmillan, vol. 25(1), pages 1-25, March.
    6. Giner, Javier & Zakamulin, Valeriy, 2023. "A regime-switching model of stock returns with momentum and mean reversion," Economic Modelling, Elsevier, vol. 122(C).

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