金融市场价格预测的量子模型

J. Subias
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引用次数: 1

摘要

本文描述了一个实际的例子,其中股票市场蓝筹股价格的概率分布被计算为限制在势阱中的量子粒子的波函数。这个模型可以很自然地解释技术分析师使用的几个经验法则的运作。基于布朗粒子运动的模型不能解释金融市场的基本方面。这是因为布朗粒子是一种经典粒子,而股票市场的价格表现得更像量子粒子。当一个经典粒子遇到障碍或潜在障碍时,它可能反弹或克服障碍,但不是同时发生这两种情况。只有量子粒子能够在势垒上同时反射和传输自身。这正是股市价格在发现阻力位时所模仿的:它们部分反弹,部分克服阻力位。这只能通过承认价格表现为量子而不是经典粒子来解释。提出的量子模型不仅为上述事实,而且为其他经验上众所周知的事实,如波动性的突然变化、价格的非高斯分布等,找到了自然的理由。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum model for price forecasting in financial markets
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.
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