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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.

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  • 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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    Cited by:

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    3. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
    4. Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "Variants of Consumption-Wealth Ratios and Predictability of U.S. Government Bond Risk Premia: Old is still Gold," Working Papers 201912, University of Pretoria, Department of Economics.

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    More about this item

    Keywords

    C22; C32; C53; Q41; Stock returns; Housing returns; Causality-in-quantiles test; Nonparametric;
    All these keywords.

    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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