We propose a quantum harmonic oscillator as a model for the market force which draws a stock return from short-run fluctuations to the long-run equilibrium. The stochastic equation governing our model is transformed into a Schrodinger equation, the solution of which features "quantized" eigenfunctions. Consequently, stock returns follow a mixed. distribution, which describes Gaussian and non-Gaussian features. Analyzing the Financial Times Stock Exchange (FTSE) All Share Index, we demonstrate that our model outperforms traditional stochastic process models, e.g., the geometric Brownian motion and the Heston model, with smaller fitting errors and better goodness-of-fit statistics. In addition, making use of analogy, we provide an economic rationale of the physics concepts such as the eigenstate, eigenenergy, and angular frequency, which sheds light on the relationship between finance and econophysics literature. Copyright (C) EPLA, 2018

This study investigates the effects of stock market uncertainty on economic fundamentals, represented by economic activities and systemic risk, in China. To capture the uncertainty in the Chinese stock market precisely, we use the entropy measure through symbolic time-series analysis. The empirical findings reveal strong spillover effects from stock market uncertainty to economic fundamentals. Specifically, an uncertainty shock generates (i) a short-term decline in industrial production, (ii) a rapid drop and rebound in the composite leading indicator, and (iii) an increase in systemic risk. To understand these findings, we suggest and validate the transmission channel through changes in consumption and investment.

This study examines whether the Bitcoin market satisfies the (weak-form) efficient market hypothesis using a quantum harmonic oscillator, which provides the state-specific probability density functions that capture the superimposed Gaussian and non-Gaussian states of the log return distribution. Contrasting the mixed evidence from a variance ratio test, the high probability allocated to the ground state suggests a near-efficient Bitcoin market. Findings imply that as Bitcoin evolves into an efficient market, speculators might encounter difficulty in exploiting profitable trading strategies. Furthermore, when policymakers initiate tight regulations to control the market, they should closely monitor market efficiency as an index of price distortion.