Refining Human Decision-Making Models with Biological Data and Financial Markets

神经科学的最新发展促使人们对迄今为止在经济学中使用的风险下的决策模型进行了修订，这些模型基于公理化定义的理性假设，并促使人们构建新的、更现实的有限理性决策模型。本研究试图通过使用生物数据来改进决策模型，并为金融市场中观察到的决策模型提供市场基础。首先，我们进行了实验，并描述了一种改进现有学习模型的交易行为。接下来，我们进行了一个基于代理人的模拟，使用人工市场模型的选择压力，以检查所观察到的有限理性是否可以有一个进化的基础。

Recent development of neuroscience has spurred revision of models of decision-making under risk, as have been used thus far in economics, based on assumptions of axiomatically defined rationality and prompted the construction of new, more realistic models of bounded rationality decision-making. This study tries to refine decision-making models by using biological data and provide a market foundation for the decision-making model observed in financial markets.First, we conducted experiments and described a trade behavior which refines existing learning-models. Next, we conducted an agent-based simulation using an artificial market model with selection pressures in order to check whether the observed bounded rationality could have an evolutionary basis.