On Rational Bubbles and Fat Tails

TL;DR

This paper investigates the statistical properties of rational bubble-driven time series, revealing that such models produce power-law tails with exponents less than 1, which conflicts with empirical data showing exponents between 2 and 4.

Contribution

It demonstrates that rational bubble models inherently generate fat-tailed distributions with exponents less than 1, challenging their empirical relevance in financial data.

Findings

Power-law tails with exponent less than 1 predicted by rational bubbles.

Disagreement between model predictions and empirical tail exponents (2-4).

Rational bubbles are unlikely to explain observed fat tails in financial returns.

Abstract

This paper addresses the statistical properties of time series driven by rational bubbles a la Blanchard and Watson (1982), corresponding to multiplicative maps, whose study has recently be revived recently in physics as a mechanism of intermittent dynamics generating power law distributions. Using insights on the behavior of multiplicative stochastic processes, we demonstrate that the tails of the unconditional distribution emerging from such bubble processes follow power-laws (exhibit hyperbolic decline). More precisely, we find that rational bubbles predict a 'fat' power tail for both the bubble component and price differences with an exponent smaller than 1, implying absence of convergence of the mean. The distribution of returns is dominated by the same power-law over an extended range of large returns. Although power-law tails are a pervasive feature of empirical data, these numerical predictions are in disagreement with the usual empirical estimates of an exponent between 2 and 4. It, therefore, appears that exogenous rational bubbles are hardly reconcilable with some of the stylized facts of financial data at a very elementary level.