This paper aims to investigate the influence of investors’ confidence in their portfolio holding relative to their social group and of various social network topologies on the dynamics of an artificial stock exchange. An investor’s confidence depends on the growth rate of his or her wealth relative to his or her social group’s average wealth. If the investor’s confidence is low, the agent will change his or her asset allocation; otherwise, he or she will maintain it. We consider three types of social networks: Barabási, small-world, and random. The actual stock markets’ properties are recovered by this model: high excess kurtosis, skewness, volatility clustering, random walk prices, and stationary return rates. The networks’ topologies are found to impact both the structuration of investors in the space of strategies and their performance. Among other characteristics, we find that (i) the small-world networks show the highest degree of homophily; (ii) as investors can switch to more profitable strategies, the best approach to make profitable investments is the chartist one in Barabási and small-world topologies; and (iii) an unequal distribution and more significant relative wealth gains occur in the Barabási network.

中文翻译：

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信心和社交网络对基于代理的证券交易所模型的影响

本文旨在调查投资者对其相对于其社会群体持有的投资组合的信心以及各种社交网络拓扑对人工证券交易所动态的影响。投资者的信心取决于其财富相对于其社会群体平均财富的增长率。如果投资者信心低下，代理人会改变其资产配置；否则，他或她将维护它。我们考虑三种类型的社交网络：Barabási、小世界和随机。通过该模型可以恢复实际股票市场的属性：高超峰度、偏度、波动性聚类、随机游走价格和平稳回报率。发现网络的拓扑结构会影响投资者在策略空间中的结构及其表现。在其他特征中，我们发现 (i) 小世界网络表现出最高程度的同质性；(ii) 由于投资者可以转向更有利可图的策略，因此进行有利可图的投资的最佳方法是 Barabási 和小世界拓扑中的图表策略；(iii) Barabási 网络中出现分配不均和更显着的相对财富收益。