Increased stock price clustering during the COVID-19 market crash: Evidence from U.S. stocks
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School of Business |
Bachelor's thesis
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Authors
Date
2022
Department
Major/Subject
Mcode
Degree programme
Rahoitus
Language
en
Pages
24 + 5
Series
Abstract
Price clustering refers to a phenomenon in which securities are traded unusually frequently at round prices or prices that are divisible by five. This results in a distribution of security prices that is not uniform as suggested by the Random Walk theory. The magnitude of the phenomenon varies between markets and across time, which provides motivation to study it during market crashes. This study provides evidence for an increase in price clustering in U.S. stocks during the COVID19 market crash. A sample of around 2 million daily observations from 3,796 firms was analyzed in uni- and multivariate settings, and the results show a 0.55 percentage point increase in price clustering during the market crash and a subsequent 0.69 percentage point decrease after the initial crash. A multivariate regression provides evidence for 0.8% higher probability of price clustering during the market crash while controlling for explanatory variables that are backed by the price clustering theories.Description
Thesis advisor
Keloharju, MattiKeywords
stock price lustering, market efficiency, market crash, panic selling