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Housing Market Variables and Predictability of State-Level Stock Market Volatility of the United States: Evidence from a GARCH-MIDAS Approach

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometrics & Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Oguzhan Cepni

    (Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark)

Abstract

This paper utilizes the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to predict the daily volatility of state-level stock returns in the United States (US), based on the monthly state and national housing price returns. We find that housing price returns generally tend to affect state-level volatility negatively. More importantly, the GARCH-MIDAS model, supplemented by these predictors, outperforms, in a statistically significant manner over short-, medium-, and long-term forecasting horizons, the benchmark GARCH-MIDAS model with realized volatility (GARCH-MIDAS-RV) for 90% of the states, with the performance of state and national housing returns being virtually inseparable. Such superior forecasting performances continue to hold when housing price returns is replaced with housing permits and housing market media attention indexes, suggesting an overwhelming role of housing market variables: traditional and behavioural, in forecasting state-level stock returns volatility. Our findings have important implications for investors and policymakers.

Suggested Citation

  • Afees A. Salisu & Rangan Gupta & Oguzhan Cepni, 2023. "Housing Market Variables and Predictability of State-Level Stock Market Volatility of the United States: Evidence from a GARCH-MIDAS Approach," Working Papers 202330, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202330
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    More about this item

    Keywords

    Monthly Housing Market Variables; Daily State-Level Stock Returns Volatility; GARCH-MIDAS; Forecasting;
    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
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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