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State-dependent Momentum in International Stock Markets

  • Dirk G Baur
  • Thomas Dimpfl

    (University of Tubingen)

We estimate quantile autoregression (QAR) models to analyze variations in the autoregressive coefficients of 55 international stock index returns and demonstrate that it is important to allow the autoregressive parameters to vary with quantiles. The empirical results identify distinctively different patterns of autoregressive coefficients in the lower, central and upper quantiles of the distribution across all countries. More specifically, the study suggests that investors follow momentum strategies in lower quantiles or "bad states". We also demonstrate that the quantile autoregression estimates can be used to test for asymmetric responses of the volatility.

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Paper provided by Finance Discipline Group, UTS Business School, University of Technology, Sydney in its series Working Paper Series with number 169.

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Length: 37
Date of creation: 01 Aug 2012
Date of revision:
Handle: RePEc:uts:wpaper:169
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  1. Mardi Dungey & Renee Fry & Brenda Gonzalez-Hermosillo & Vance Martin, 2005. "Empirical modelling of contagion: a review of methodologies," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 9-24.
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  9. William N. Goetzmann & Massimo Massa, 1999. "Daily Momentum And Contrarian Behavior Of Index Fund Investors," Yale School of Management Working Papers ysm13, Yale School of Management.
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  11. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
  12. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
  13. Hibbert, Ann Marie & Daigler, Robert T. & Dupoyet, Brice, 2008. "A behavioral explanation for the negative asymmetric return-volatility relation," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2254-2266, October.
  14. Ihsan Ullah Badshah, 2013. "Quantile Regression Analysis of the Asymmetric Return‐Volatility Relation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(3), pages 235-265, 03.
  15. Engle, Robert F & Ng, Victor K, 1993. "Time-Varying Volatility and the Dynamic Behavior of the Term Structure," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(3), pages 336-49, August.
  16. James W. Taylor, 2008. "Using Exponentially Weighted Quantile Regression to Estimate Value at Risk and Expected Shortfall," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(3), pages 382-406, Summer.
  17. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
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  19. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
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