网络复杂性与金融行为——金融市场的量价分布

Leilei Shi, Bingtuan Wang
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引用次数: 1

摘要

目前的研究表明,在研究社会互动结构的网络复杂性方面,是时候从行为金融学转向社会金融学了。一些经济学和金融学的先驱学者已经提供了大量的经验证据,证明金融思想是如何传播、传播和演变的,以及社会过程是如何影响金融结果的。然而,要在社会金融中找到一个被广泛接受的理论是一个很大的挑战。在简要回顾了从网络理论到复杂网络的历史发展之后,我们将重点讨论网络理论在金融领域的应用。我们用一种新的数学方法,从施的波动方程出发,提出了一个统一的理论和两套显式的价格范围内的体积分布模型。对非线性v型价格压力效用的实证研究也证明了该理论的有效性。预测了针对COVID-19大流行的隔离和戴口罩政策的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network Complexity and Financial Behavior – Volume Distribution over Price in Financial Market
Current study has revealed that it is time to move beyond behavioral finance to social finance in network complexity, which studies the structure of social interactions. Some pioneering scholars in economics and finance have provided a considerable number of empirical evidences of how financial ideas transmit, spread and evolve, and how social processes affect financial outcomes. However, there is big challenge to have a widely acceptable theory in the social finance. After a brief perspective on the historical development from network theories to complex networks, here we focus on the application in finance. We propose a unified theory and two sets of explicit volume distribution models over a price range from Shi’s wave equation in a new mathematical method. The theory is also evidenced validity by the empirical evidence on nonlinear V-shaped price pressures utility. It predicts the policies effective about quarantine and mask wearing against COVID-19 pandemics.
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