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

• Aviral Kumar Tiwari ^{[5] [4]} ; Rangan Gupta ^[1] ; Juncal Cunado ^[2] ; Xin Sheng ^[3]
  1. [1] University of Pretoria

     University of Pretoria

     City of Tshwane, Sudáfrica

     
  2. [2] Universidad de Navarra

     Universidad de Navarra

     Pamplona, España

     
  3. [3] Anglia Ruskin University

     Anglia Ruskin University

     Cambridge District, Reino Unido

     
  4. [4] South Ural State University

     South Ural State University

     Rusia

     
  5. [5] Rajagiri Business School, Rajagiri Valley Campus, Kochi, India

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• Localización: Economics and Business Letters, ISSN-e 2254-4380, Vol. 9, Nº. Extra 3, 2020 (Ejemplar dedicado a: Selected papers from 7th International PhD Meeting in Economics 2019), págs. 178-188
• Idioma: inglés
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• Resumen

  • In the pure time-series sense, weak-form of efficiency of the housing market would imply unpredictability of housing returns. Given this, 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.