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

  1. Aviral Kumar Tiwari 15
  2. Rangan Gupta 2
  3. Juncal Cunado 3
  4. Xin Sheng 4
  1. 1 Rajagiri Business School, Rajagiri Valley Campus, Kochi, India
  2. 2 University of Pretoria
    info

    University of Pretoria

    Pretoria, Sudáfrica

    ROR https://ror.org/00g0p6g84

  3. 3 Universidad de Navarra
    info

    Universidad de Navarra

    Pamplona, España

    ROR https://ror.org/02rxc7m23

  4. 4 Anglia Ruskin University, Chelmsford, UK
  5. 5 South Ural State University
    info

    South Ural State University

    Cheliábinsk, Rusia

    ROR https://ror.org/03sfk2504

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Journal:
Economics and Business Letters

ISSN: 2254-4380

Year of publication: 2020

Issue Title: Selected papers from 7th International PhD Meeting in Economics 2019

Volume: 9

Issue: 3

Pages: 178-188

Type: Article

DOI: 10.17811/EBL.9.3.2020.178-188 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

More publications in: Economics and Business Letters

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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.

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