THE COVID-19 PANDEMIC & HERDING BEHAVIOR : EVIDENCE FROM BANGLADESH CAPITAL MARKET

Abstract

This study aims to detect herding behavior during the COVID-19 pandemic, compare investor trading behavior pre (2015 to 2019) and post (2020 to 2022) pandemic, and examine how investors react in panic and uncertainty. Current asset pricing theory states that cross-sectional returns should reflect systematic risks like stock prices, where Capital Asset Pricing Model (CAPM) betas are often viewed as return volatility, but they do not account for price volatility. To reflect the uncertainty, CAPM and Asset pricing theory are not sufficient so the gap is filled by behavioral finance that examines investors’ personalities and trading behaviors to explain market swings. It examines which stock price data influences investors’ decisions that is depicted by herding behavior. People “herd” when they do not make individual decisions. Unpredictability, worry, and panic often cause such behavior and COVID-19 epidemic worsened such factors that hurt global economy and stock markets. Financial data cannot reveal herding behavior for which two models, Cross-sectional standard deviation (CSSD) and Cross-sectional absolute deviation (CSAD), acknowledged by Christie and Huang (1995), are used to identify herding behavior in Bangladesh’s capital market during the COVID-19 pandemic. CSSD uses standard deviation to understand investor herd behavior, while CSAD uses absolute deviation. As mentioned in the literature review from the journal of Christie and Huang (1995) that the CSSD model and CSAD model will provide a conflicting result, the above finding shows the same because in CSSD model, no herding behavior is found but in the CSAD model, the herding behavior is found in the bullish markets for the year 2020 and in the bearish markets from 2015 to 2022.

DOI: https://doi.org/10.58964/JBAART02