The Influence of Confidence and Social Networks on an Agent-Based Model of Stock Exchange

Author(s)

Bertella, Mario A. ^{[1, 2]} ; Silva, Jonathas N. ^[1] ; Correa, Andre L. ^[1] ; Sornette, Didier ^[2]

Affiliation

^[1] Sao Paulo State Univ UNESP, Dept Econ, BR-14800901 Araraquara, SP - Brazil

^[2] Swiss Fed Inst Technol, Dept Management Technol & Econ, CH-8092 Zurich - Switzerland

• Document type: Journal article
• Source: COMPLEXITY; v. 2021, JUL 19 2021.
• Web of Science Citations: 0

Abstract

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: Barabasi, 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 Barabasi and small-world topologies; and (iii) an unequal distribution and more significant relative wealth gains occur in the Barabasi network. (AU)

• FAPESP's process: 18/22562-4 - Behavioral Finance, Agent-Based Models and Social Network
• Grantee: Mario Augusto Bertella
• Support Opportunities: Scholarships abroad - Research