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COVID-19 and REITs Crash: Predictability and Market Conditions

Author

Listed:
  • Kwangwon Ahn

    (Yonsei University)

  • Hanwool Jang

    (Glasgow Caledonian University)

  • Jinu Kim

    (Yonsei University)

  • Inug Ryu

    (Korea Exchange)

Abstract

This study examines the applicability of the log-periodic power law (LPPL) model for the real estate investment trust (REIT) market in the early stages of the coronavirus disease 2019 (COVID-19) pandemic. Our results indicate that unlike in the 2008 global financial crisis, the market conditions were unsuitable for applying LPPL for predicting the COVID-19-induced critical time in the REIT market. Before the pandemic, investors’ herding behavior was extremely weak, and market efficiency was improving, indicating a low probability of the formation of endogenous bubbles. Thus, policymakers should use this bubble-based model while carefully considering market conditions, including investors’ herding behavior and market efficiency. For this purpose, the power law exponent and Hurst exponent can be used to gauge market conditions along with comprehensive market information regarding the appropriateness of applying the LPPL model.

Suggested Citation

  • Kwangwon Ahn & Hanwool Jang & Jinu Kim & Inug Ryu, 2024. "COVID-19 and REITs Crash: Predictability and Market Conditions," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1159-1172, March.
    • Handle: RePEc:kap:compec:v:63:y:2024:i:3:d:10.1007_s10614-023-10431-1
    DOI: 10.1007/s10614-023-10431-1
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