RT Journal Article
SR Electronic
T1 When Do Investors Freak Out? Machine Learning Predictions of Panic Selling
JF The Journal of Financial Data Science
FD Institutional Investor Journals
SP 11
OP 39
DO 10.3905/jfds.2021.1.085
VO 4
IS 1
A1 Daniel Elkind
A1 Kathryn Kaminski
A1 Andrew W. Lo
A1 Kien Wei Siah
A1 Chi Heem Wong
YR 2022
UL https://pm-research.com/content/4/1/11.abstract
AB Using a novel dataset of 653,455 individual brokerage accounts belonging to 298,556 households, the authors document the frequency, timing, and duration of panic sales, which they define as a decline of 90% of a household account’s equity assets over the course of one month, of which 50% or more is due to trades. The authors find that a disproportionate number of households make panic sales when there are sharp market downturns, a phenomenon they call freaking out. The authors also show that panic selling and freak-outs are predictable and fundamentally different from other well-known behavioral patterns such as overtrading or the disposition effect.