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State-dependent Momentum in International Stock Markets

Author

Listed:
  • Dirk G Baur
  • Thomas Dimpfl

    (University of Tubingen)

Abstract

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.

Suggested Citation

  • Dirk G Baur & Thomas Dimpfl, 2012. "State-dependent Momentum in International Stock Markets," Working Paper Series 169, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  • Handle: RePEc:uts:wpaper:169
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    File URL: http://www.finance.uts.edu.au/research/wpapers/wp169.pdf
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    References listed on IDEAS

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    1. James W. Taylor, 2008. "Using Exponentially Weighted Quantile Regression to Estimate Value at Risk and Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 382-406, Summer.
    2. Koenker, Roger & Xiao, Zhijie, 2006. "Quantile Autoregression," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 980-990, September.
    3. 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.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 254-265.
    6. Taimur Baig & Ilan Goldfajn, 1999. "Financial Market Contagion in the Asian Crisis," IMF Staff Papers, Palgrave Macmillan, vol. 46(2), pages 1-3.
    7. 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 336-349, August.
    8. Brian H. Boyer & Tomomi Kumagai & Kathy Yuan, 2006. "How Do Crises Spread? Evidence from Accessible and Inaccessible Stock Indices," Journal of Finance, American Finance Association, vol. 61(2), pages 957-1003, April.
    9. Robert F. Engle & Magdalena E. Sokalska, 0. "Forecasting intraday volatility in the US equity market. Multiplicative component GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 10(1), pages 54-83.
    10. Goetzmann, William N. & Massa, Massimo, 2002. "Daily Momentum and Contrarian Behavior of Index Fund Investors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(3), pages 375-389, September.
    11. Andrew Ang & Joseph Chen & Yuhang Xing, 2006. "Downside Risk," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1191-1239.
      • Andrew Ang & Joseph Chen & Yuhang Xing, 2005. "Downside risk," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
    12. 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.
    13. 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.
    14. Roger Koenker & Zhijie Xiao, 2004. "Unit Root Quantile Autoregression Inference," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 775-787, January.
    15. Asem, Ebenezer, 2009. "Dividends and price momentum," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 486-494, March.
    16. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1148-1171, October.
    17. 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.
    18. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    19. Veronesi, Pietro, 1999. "Stock Market Overreaction to Bad News in Good Times: A Rational Expectations Equilibrium Model," The Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 975-1007.
    20. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    21. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    22. 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, March.
    23. James W. Taylor, 2008. "Estimating Value at Risk and Expected Shortfall Using Expectiles," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 231-252, Spring.
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    Cited by:

    1. Kuck, Konstantin & Maderitsch, Robert, 2019. "Intra-day dynamics of exchange rates: New evidence from quantile regression," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 247-257.

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    More about this item

    Keywords

    quantile autoregression (QAR); return autocorrelation; investor behaviour; momentum; underreaction; financial crisis;
    All these keywords.

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