Unveiling herd behavior in financial markets

Herd behavior is a powerful source of growth in financial markets. However, as available energy resources limit exponential growth, we should expect periods where an upward trend is balanced toward equilibrium or reverse its direction toward decline. This paper proposes a novel approach for modeling herd behavior and predicting a trend reversal in financial markets. Our approach relies on two key metrics: asymmetry and 'steps to symmetry.' We use Machine Learning to identify hidden patterns in the fluctuations of these metrics and use the patterns for predicting a transition from exponential growth. Analyzing three datasets of stock prices, we present solid empirical evidence supporting the proposed approach.