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Testing the white noise hypothesis in high-frequency housing returns of the United States

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  • Aviral Kumar Tiwari
  • Rangan Gupta
  • Juncal Cunado
  • Xin Sheng

Abstract

Utilizing a daily dataset of aggregate housing market returns of the United States, we test whether housing market returns are white noise using the blockwise wild bootstrap in a rolling-window framework. We investigate the dynamic evolution of housing market efficiency and find that the white noise hypothesis is accepted in most windows associated with non-crisis periods. However, for some periods before the burst of the housing market bubbles, and during the subprime mortgage crisis, European sovereign debt crisis and the Brexit, the white noise hypothesis is rejected, indicating that the housing market is inefficient in periods of turbulence. Our results have important implications for economic agents.

Suggested Citation

  • Aviral Kumar Tiwari & Rangan Gupta & Juncal Cunado & Xin Sheng, 2020. "Testing the white noise hypothesis in high-frequency housing returns of the United States," Economics and Business Letters, Oviedo University Press, vol. 9(3), pages 178-188.
    • Handle: RePEc:ove:journl:aid:14521
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • 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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