COVID-19 and REITs crash: predictability and market conditions

Kwangwon Ahn, Hanwool Jang*, Jinu Kim, Inug Ryu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1159-1172
Number of pages14
JournalComputational Economics
Volume63
Early online date9 Nov 2023
DOIs
Publication statusPublished - Mar 2024

Keywords

  • COVID-19
  • Crash
  • Herding behavior
  • Market efficiency
  • REITs

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'COVID-19 and REITs crash: predictability and market conditions'. Together they form a unique fingerprint.

Cite this