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

Aviral Tiwari, Rangan Gupta, Juncal Cunado and Xin Sheng

Economics and Business Letters, 2020, vol. 9, issue 3, 178-188

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.

Date: 2020
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Working Paper: Testing the White Noise Hypothesis in High-Frequency Housing Returns of the United States (2019)
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