IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v47y2019icp391-405.html
   My bibliography  Save this article

The role of term spread and pattern changes in predicting stock returns and volatility of the United Kingdom: Evidence from a nonparametric causality-in-quantiles test using over 250 years of data

Author

Listed:
  • Gupta, Rangan
  • Risse, Marian
  • Volkman, David A.
  • Wohar, Mark E.

Abstract

Given the existence of nonlinear relationship between equity premium and term spread, as well as pattern changes and the interaction of pattern changes with the term-spread and changes in the shape of the yield curve, we use a nonparametric k-th order causality-in-quantiles test to predict the movement in excess returns and volatility based on changes in the shape of the yield curve. With the test applied to over 250 years of monthly data for the UK covering the period 1753:08 to 2017:02, we find that pattern changes and the interaction of pattern changes with the term-spread, besides the term spread itself, tends to also play an important role in predicting volatility at the upper end of its conditional distribution. In addition, the effect on excess returns from term spread, pattern changes and the interaction is found to have improved markedly over time, barring at the conditional median of the equity premium. Finally, comparisons are made with historical data of the US and South Africa, and implications of our results are discussed.

Suggested Citation

  • Gupta, Rangan & Risse, Marian & Volkman, David A. & Wohar, Mark E., 2019. "The role of term spread and pattern changes in predicting stock returns and volatility of the United Kingdom: Evidence from a nonparametric causality-in-quantiles test using over 250 years of data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 391-405.
  • Handle: RePEc:eee:ecofin:v:47:y:2019:i:c:p:391-405
    DOI: 10.1016/j.najef.2018.05.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940817303996
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ostdiek, Barbara, 1998. "The world ex ante risk premium: an empirical investigation," Journal of International Money and Finance, Elsevier, vol. 17(6), pages 967-999, December.
    2. Eva Ferreira & M. Isabel Martínez Serna & Eliseo Navarro & Gonzalo Rubio, 2008. "Economic Sentiment and Yield Spreads in Europe," European Financial Management, European Financial Management Association, vol. 14(2), pages 206-221.
    3. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    4. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
    5. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    6. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    7. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    8. McCown, James Ross, 1999. "The Effects of Inverted Yield Curves on Asset Returns," The Financial Review, Eastern Finance Association, vol. 34(2), pages 109-126, May.
    9. Diks Cees & Panchenko Valentyn, 2005. "A Note on the Hiemstra-Jones Test for Granger Non-causality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-9, June.
    10. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
    11. David A. Volkman & Olivier J. P. Maisondieu Laforge & Mark Wohar, 2014. "The conditional influence of term spread and pattern changes on future equity returns," Applied Economics, Taylor & Francis Journals, vol. 46(9), pages 913-923, March.
    12. Eduardo Acosta-González & Fernando Fernández-Rodríguez, 2007. "Model selection via genetic algorithms illustrated with cross-country growth data," Empirical Economics, Springer, vol. 33(2), pages 313-337, September.
    13. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    14. Emanuel Moench, 2012. "Term structure surprises: the predictive content of curvature, level, and slope," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(4), pages 574-602, June.
    15. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(04), pages 861-887, August.
    16. Jacob Boudoukh & Matthew Richardson & Robert F. Whitelaw, 1997. "Nonlinearities in the Relation Between the Equity Risk Premium and the Term Structure," Management Science, INFORMS, vol. 43(3), pages 371-385, March.
    17. Bekiros, Stelios & Gupta, Rangan & Majumdar, Anandamayee, 2016. "Incorporating economic policy uncertainty in US equity premium models: A nonlinear predictability analysis," Finance Research Letters, Elsevier, vol. 18(C), pages 291-296.
    18. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
    19. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    20. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    21. Hiemstra, Craig & Jones, Jonathan D, 1994. " Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    22. Boudoukh, Jacob & Richardson, Matthew & Smith, Tom, 1993. "Is the ex ante risk premium always positive? *1: A new approach to testing conditional asset pricing models," Journal of Financial Economics, Elsevier, vol. 34(3), pages 387-408, December.
    23. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    24. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    25. James Claus, 2001. "Equity Premia as Low as Three Percent? Evidence from Analysts' Earnings Forecasts for Domestic and International Stock Markets," Journal of Finance, American Finance Association, vol. 56(5), pages 1629-1666, October.
    26. David C. Wheelock & Mark E. Wohar, 2009. "Can the term spread predict output growth and recessions? a survey of the literature," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 419-440.
    27. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.
    28. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    29. Racine, Jeff & Li, Qi, 2004. "Nonparametric estimation of regression functions with both categorical and continuous data," Journal of Econometrics, Elsevier, vol. 119(1), pages 99-130, March.
    30. Bai, Zhidong & Wong, Wing-Keung & Zhang, Bingzhi, 2010. "Multivariate linear and nonlinear causality tests," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 5-17.
    31. Ross McCown, James, 2001. "Yield curves and international equity returns," Journal of Banking & Finance, Elsevier, vol. 25(4), pages 767-788, April.
    32. David A. Volkman & Olivier J.P. Maisondieu Laforge & Mark Wohar, 2012. "Interactive effect of changes in the shape of the yield curve and conditional term spread on expected equity returns," Applied Financial Economics, Taylor & Francis Journals, vol. 22(18), pages 1491-1500, September.
    33. Bai, Zhidong & Li, Heng & Wong, Wing-Keung & Zhang, Bingzhi, 2011. "Multivariate causality tests with simulation and application," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1063-1071, August.
    34. Campbell R. Harvey, 1997. "The Relation between the Term Structure of Interest Rates and Canadian Economic Growth," Canadian Journal of Economics, Canadian Economics Association, vol. 30(1), pages 169-193, February.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Stock returns; Volatility; Yield curve changes; Conditional term spreads; Nonparametric causality-in-quantiles test;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:47:y:2019:i:c:p:391-405. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.