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


  • Aviral Kumar Tiwari Montpellier Business School, Avenue des Moulins
  • Rangan Gupta Department of Economics, University of Pretoria, Pretoria
  • Juncal Cunado School of Economics, University of Navarra,
  • Xin Sheng Anglia Ruskin University




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.



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How to Cite

Tiwari, A. K., Gupta, R., Cunado, J., & Sheng, X. (2020). Testing the white noise hypothesis in high-frequency housing returns of the United States. Economics and Business Letters, 9(3), 178–188. https://doi.org/10.17811/ebl.9.3.2020.178-188