Discrete Scaling in Stock Markets Before Crashes

TL;DR

This paper models stock market crashes as critical points with discrete scaling, predicting log-periodic fluctuations in indexes, supported by empirical evidence and drawing analogies with earthquakes.

Contribution

It introduces a hierarchical system with discrete scaling to explain stock market crashes and provides empirical evidence for log-periodic fluctuations.

Findings

Evidence of log-periodic fluctuations in stock indexes.

Support for the discrete scaling model in market crashes.

Analogy with earthquake phenomena enhances understanding.

Abstract

We propose a picture of stock market crashes as critical points in a hierachical system with discrete scaling. The critical exponent is then complex, leading to log-periodic fluctuations in stock market indexes. We present ``experimental'' evidence in favor of this prediction. This picture is in the spirit of the known earthquake-stock market analogy and of recent work on log-periodic fluctuations associated with earthquakes.