The evolving cobweb of relations among partially rational investors

To overcome the limitations of neoclassical economics, researchers have leveraged tools of statistical physics to build novel theories. The idea was to elucidate the macroscopic features of financial markets from the interaction of its microscopic constituents, the investors. In this framework, the model of the financial agents has been kept separate from that of their interaction. Here, instead, we explore the possibility of letting the interaction topology emerge from the model of the agents’ behavior. Then, we investigate how the emerging cobweb of relationship affects the overall market dynamics. To this aim, we leverage tools from complex systems analysis and nonlinear dynamics, and model the network of mutual influence as the output of a dynamical system describing the edge evolution. In this work, the driver of the link evolution is the relative reputation between possibly coupled agents. The reputation is built differently depending on the extent of rationality of the investors. The continuous edge activation or deactivation induces the emergence of leaders and of peculiar network structures, typical of real influence networks. The subsequent impact on the market dynamics is investigated through extensive numerical simulations in selected scenarios populated by partially rational investors.为克服新古典经济学的局限性，研究者借助统计物理学工具构建了全新的理论体系。其核心思路是从微观组成单元——投资者的相互作用出发，阐明金融市场的宏观运行特征。在此前的研究框架中，金融智能体（financial agents）的模型与其相互作用模型相互分离。而本研究则探索了一种新的可能性：让相互作用拓扑结构从智能体的行为模型中自发涌现。随后，本研究探究了这种自发形成的关系蛛网结构如何影响整体市场动态。为此，本研究借助复杂系统分析与非线性动力学工具，将相互影响网络建模为描述连边演化的动力学系统的输出结果。本研究中，连边演化的驱动因素是潜在耦合智能体间的相对声誉。声誉的构建方式取决于投资者的理性程度高低。连边的持续激活与失活会催生市场领导者与特殊的网络结构——这正是真实影响力网络的典型特征。最后，本研究通过在由部分理性投资者构成的特定场景中开展大规模数值模拟，探究了该网络结构对市场动态产生的后续影响。