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Do cay and cayMS predict stock and housing returns? Evidence from a nonparametric causality test

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  • Balcilar, Mehmet
  • Gupta, Rangan
  • Sousa, Ricardo M.
  • Wohar, Mark E.

Abstract

We use a nonparametric causality-in-quantiles test to compare the predictive ability of the consumption-wealth ratio (cay) and the Markov Switching version (cayMS) for excess and real stock and housing returns and their volatility. Our results reveal strong evidence of nonlinearity and regime changes in the relationship between asset returns and cay or cayMS, which corroborates the relevance of this econometric framework. Moreover, both cay or cayMS are found to predict only excess stock returns over its entire conditional distribution, with the latter being a strong predictor only at certain quantiles. As for the housing market, these two consumption-wealth ratios only predict the volatility of real housing returns, with cayMS outperforming cay over the majority of the conditional distribution.

Suggested Citation

  • Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2017. "Do cay and cayMS predict stock and housing returns? Evidence from a nonparametric causality test," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 269-279.
  • Handle: RePEc:eee:reveco:v:48:y:2017:i:c:p:269-279
    DOI: 10.1016/j.iref.2016.12.007
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    1. Pakoš, Michal, 2011. "Estimating Intertemporal and Intratemporal Substitutions When Both Income and Substitution Effects Are Present: The Role of Durable Goods," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 439-454.
    2. Case Karl E. & Quigley John M. & Shiller Robert J., 2005. "Comparing Wealth Effects: The Stock Market versus the Housing Market," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-34, May.
    3. Rocha Armada, Manuel J. & Sousa, Ricardo M. & Wohar, Mark E., 2015. "Consumption growth, preference for smoothing, changes in expectations and risk premium," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 80-97.
    4. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2014. "Sticky prices or economically-linked economies: The case of forecasting the Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 95-109.
    5. Hanno N. Lustig & Stijn G. Van Nieuwerburgh, 2005. "Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective," Journal of Finance, American Finance Association, vol. 60(3), pages 1167-1219, June.
    6. Piazzesi, Monika & Schneider, Martin & Tuzel, Selale, 2007. "Housing, consumption and asset pricing," Journal of Financial Economics, Elsevier, vol. 83(3), pages 531-569, March.
    7. 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.
    8. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
    9. Karl E. Case & John M. Quigley & Robert J. Shiller, 2011. "Wealth Effects Revisited 1978-2009," Cowles Foundation Discussion Papers 1784, Cowles Foundation for Research in Economics, Yale University.
    10. Martin Lettau, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    11. Sousa, Ricardo M., 2010. "Consumption, (dis)aggregate wealth, and asset returns," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 606-622, September.
    12. Ricardo M. Sousa, 2015. "Linking wealth and labour income with stock returns and government bond yields," The European Journal of Finance, Taylor & Francis Journals, vol. 21(10-11), pages 806-825, September.
    13. António Afonso & Ricardo M. Sousa, 2011. "Consumption, Wealth, Stock And Government Bond Returns: International Evidence," Manchester School, University of Manchester, vol. 79(6), pages 1294-1232, December.
    14. Leung, Charles, 2004. "Macroeconomics and housing: a review of the literature," Journal of Housing Economics, Elsevier, vol. 13(4), pages 249-267, December.
    15. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    16. Francesco Bianchi & Martin Lettau & Sydney C. Ludvigson, 2016. "Monetary Policy and Asset Valuation," NBER Working Papers 22572, National Bureau of Economic Research, Inc.
    17. Caporale, Guglielmo Maria & Sousa, Ricardo M., 2016. "Consumption, wealth, stock and housing returns: Evidence from emerging markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 562-578.
    18. Bekiros, Stelios & Gupta, Rangan, 2015. "Predicting stock returns and volatility using consumption-aggregate wealth ratios: A nonlinear approach," Economics Letters, Elsevier, vol. 131(C), pages 83-85.
    19. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
    20. Motohiro Yogo, 2006. "A Consumption-Based Explanation of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 61(2), pages 539-580, April.
    21. 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.
    22. 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.
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    Keywords

    C22; C32; C53; Q41; Stock returns; Housing returns; Causality-in-quantiles test; Nonparametric;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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