Quantum model for price forecasting in financial markets

TL;DR

This paper introduces a quantum physics-inspired model to explain stock price behaviors, capturing phenomena like resistance levels and volatility changes that classical models fail to address.

Contribution

The paper presents a novel quantum model for stock prices, providing a more accurate explanation of market phenomena than traditional classical models.

Findings

Quantum model explains resistance levels as partial reflection and transmission.

Model accounts for non-Gaussian price distributions.

Captures sudden volatility changes in markets.

Abstract

The present paper describes a practical example in which the probability distribution of the prices of a stock market blue chip is calculated as the wave function of a quantum particle confined in a potential well. This model may naturally explain the operation of several empirical rules used by technical analysts. Models based on the movement of a Brownian particle do not account for fundamental aspects of financial markets. This is due to the fact that the Brownian particle is a classical particle, while stock market prices behave more like quantum particles. When a classical particle meets an obstacle or a potential barrier, it may either bounce or overcome the obstacle, yet not both at a time. Only a quantum particle can simultaneously reflect and transmit itself on a potential barrier. This is precisely what prices in a stock market imitate when they find a resistance level: they partially bounce against and partially overcome it. This can only be explained by admitting that prices behave as quantum rather than as classic particles. The proposed quantum model finds natural justification not only for the aforementioned facts but also for other empirically well-known facts such as sudden changes in volatility, non-Gaussian distribution in prices, among others.