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The Predictability of cay and cayMS for Stock and Housing Returns: A Nonparametric Causality in Quantile Test

Author

Listed:
  • Mehmet Balcilar

    (Eastern Mediterranean University, Turkey and University of Pretoria, South Africa)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Ricardo M. Sousa

    (Department of Economics, University of Minho, Campus of Gualtar, 4710-057 - Braga - Portugal)

  • Mark E. Wohar

    (University of Nebraska-Omaha, USA and Loughborough University, UK)

Abstract
We use a nonparametric causality-in-quantiles test to compare the predictive ability of cay and cayMS for excess and real stock and housing returns and their volatility using quarterly data for the US over the periods of 1952:Q1-2014:Q3 and 1953:Q2-2014:Q3 respectively. 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, we confirm the outperformance of cayMS vis-à-vis cay and their relevance for excess stock returns. Furthermore, we show that cayMS is particularly useful at forecasting certain quantiles of the conditional distribution. As for housing returns, the empirical evidence suggests that the predictive ability of cay and cayMS is relatively low. Yet, cay outperforms cayMS over the majority of the quantiles of the conditional distribution of the variance of real housing returns.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Ricardo M. Sousa & Mark E. Wohar, 2015. "The Predictability of cay and cayMS for Stock and Housing Returns: A Nonparametric Causality in Quantile Test," Working Papers 201577, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201577
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    Citations

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    Cited by:

    1. Chang, Tsangyao & Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian, 2019. "Predicting stock market movements with a time-varying consumption-aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 458-467.
    2. Rangan Gupta & Hardik A. Marfatia & Eric Olson, 2020. "Effect of uncertainty on U.S. stock returns and volatility: evidence from over eighty years of high-frequency data," Applied Economics Letters, Taylor & Francis Journals, vol. 27(16), pages 1305-1311, September.

    More about this item

    Keywords

    stock returns; housing returns; quantile; nonparametric; causality;
    All these keywords.

    JEL classification:

    • 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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