Large financial crashes
Didier Sornette, Anders Johansen

TL;DR
This paper models large stock market crashes as critical phenomena with log-periodic oscillations, extending previous physics-inspired models to include non-linear corrections and testing them on historical crashes.
Contribution
It introduces a non-linear correction to the renormalization group model of stock market crashes, predicting a log-frequency shift in pre-crash oscillations and validating it with historical data.
Findings
Good fit of the model to 1929 and 1987 crashes
Parameter consistency across different crashes
Supports collective behavior as crash origin
Abstract
We propose that large stock market crashes are analogous to critical points studied in statistical physics with log-periodic correction to scaling. We extend our previous renormalization group model of stock market prices prior to and after crashes [D. Sornette et al., J.Phys.I France 6, 167, 1996] by including the first non-linear correction. This predicts the existence of a log-frequency shift over time in the log-periodic oscillations prior to a crash. This is tested on the two largest historical crashes of the century, the october 1929 and october 1987 crashes, by fitting the stock market index over an interval of 8 years prior to the crashes. The good quality of the fits, as well as the consistency of the parameter values obtained from the two crashes, promote the theory that crashes have their origin in the collective ``crowd'' behavior of many interacting agents.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
