Testing the White Noise Hypothesis in High-Frequency Housing Returns of the United States

Aviral Tiwari, Rangan Gupta, Juncal Cuñado () and Xin Sheng ()
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Xin Sheng: Lord Ashcroft International Business School, Anglia Ruskin University, Chelmsford, CM1 1SQ, U.K.

No 201952, Working Papers from University of Pretoria, Department of Economics

Abstract: 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.

Keywords: Blockwise wild bootstrap; Randomized block size; Serial correlation; Weak-form efficiency; White noise test; Daily US housing returns (search for similar items in EconPapers)
JEL-codes: C12 C58 R31 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2019-07
New Economics Papers: this item is included in nep-ure
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Journal Article: Testing the white noise hypothesis in high-frequency housing returns of the United States (2020)
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