Trends, reversion, and critical phenomena in financial markets

Abstract

Financial markets across all asset classes are known to exhibit trends, which have been exploited by traders for decades. However, a closer look at the data reveals that those trends tend to revert when they become too strong. Here, we empirically measure the interplay between trends and reversion in detail, based on 30 years of daily futures prices for equity indices, interest rates, currencies and commodities.We find that trends tend to revert before they become statistically significant. Our key observation is that tomorrow’s expected return follows a cubic polynomial of today’s trend strength. The positive linear term of this polynomial represents trend persistence, while its negative cubic term represents trend reversal. Their precise coefficients determine the critical trend strength, beyond which trends tend to revert.These coefficients are small but statistically highly significant, if decades of data for many different markets are combined. We confirm this by bootstrapping and out-of-sample testing. Moreover, we find that these coefficients are universal across asset classes and have a universal scaling behavior, as the trend’s time horizon runs from a few days to several years. We also measure the rate, at which trends have become less persistent, as markets have become more efficient over the decades.Our empirical results point towards a potential deep analogy between financial markets and critical phenomena. In this analogy, the trend strength plays the role of an order parameter, whose dynamics is described by a Langevin equation. The cubic polynomial is the derivative of a quartic potential, which plays the role of the energy. This supports the conjecture that financial markets can be modeled as statistical–mechanical systems near criticality, whose microscopic constituents are Buy/Sell orders.