Behavioural Finance Power Law vs Gaussian Distribution Analysis in Actual Stock Markets
Stock market dynamics deviate from the Efficient Market Hypothesis and the Gaussian normal distribution due to nonlinear feedback mechanisms characteristic of non-equilibrium systems. The core theoretical mechanism is defined by a Power Law probability distribution, where the frequency of extreme events scales as $x^{-\alpha}$, validating that large deviations are not vanishingly rare anomalies but intrinsic behaviors of self-referential markets. This framework belongs to behavioral finance and chaos theory, specifically replacing deterministic equilibrium models with non-equilibrium descriptions based on coupled differential equations.
Behavioural Finance Power Law vs Gaussian Distribution Analysis in Actual Stock Markets
Stock market dynamics deviate from the Efficient Market Hypothesis and the Gaussian normal distribution due to nonlinear feedback mechanisms characteristic of non-equilibrium systems. The core theore…