The 'COVID' Crash of the 2020 U.S. Stock Market
Min Shu, Ruiqiang Song, Wei Zhu

TL;DR
This study uses the LPPLS methodology to analyze the 2020 U.S. stock market crash, revealing it was driven by endogenous systemic instability and identifying bubble patterns starting in 2018 across different market caps.
Contribution
It applies the LPPLS approach to systematically detect bubble patterns and endogenous causes of the 2020 crash across multiple market segments, offering a new real-time detection pipeline.
Findings
All indexes lost over a third of their value within five weeks.
Bubble patterns were evident before the crash, starting as early as September 2018.
The crash was endogenous, not solely caused by COVID-19.
Abstract
We employed the log-periodic power law singularity (LPPLS) methodology to systematically investigate the 2020 stock market crash in the U.S. equities sectors with different levels of total market capitalizations through four major U.S. stock market indexes, including the Wilshire 5000 Total Market index, the S&P 500 index, the S&P MidCap 400 index, and the Russell 2000 index, representing the stocks overall, the large capitalization stocks, the middle capitalization stocks and the small capitalization stocks, respectively. During the 2020 U.S. stock market crash, all four indexes lost more than a third of their values within five weeks, while both the middle capitalization stocks and the small capitalization stocks have suffered much greater losses than the large capitalization stocks and stocks overall. Our results indicate that the price trajectories of these four stock market indexes…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Market Dynamics and Volatility · Financial Risk and Volatility Modeling
