Agent-Based Market Model of Momentum and Investor Imitation
Summary
This study uses an agent-based model to examine how investor behavior can shape simulated stock-market returns and wealth. Investors occupy a small-world network, have imitation, anti-imitation, or random profiles, and choose actions using either information from trusted neighbors or a momentum signal based on the market index.
The analysis compares index fluctuations, return distributions, and investor wealth across psychological profiles. It also varies the profile assigned to a network hub and reports conditions in which anti-imitation is the more profitable approach. The authors describe an asymmetry in simulated return rates and say it persists under a different decision algorithm. These are model-based findings; the excerpt provides no empirical market validation or quantitative results, and its conclusions depend on the network and behavioral assumptions.
Key ideas
- The model connects investors through a small-world network and assigns each a behavioral profile.
- Agents make decisions using trusted-neighbor information or market-index momentum.
- The analysis compares market fluctuations, wealth, and returns across behavioral profiles.
- Changing the hub's profile affects which strategy is most profitable in the simulation.
- The reported return-rate asymmetry persists when a different decision algorithm is used.
Tags
Full text
# 1711.08282 # Asymmetric return rates and wealth distribution influenced by the introduction of technical analysis into a behavioral agent based model Behavioral Finance has become a challenge to the scientific community. Based on the assumption that behavioral aspects of investors may explain some features of the Stock Market, we propose an agent based model to study quantitatively this relationship. In order to approximate the simulated market to the complexity of real markets, we consider that the investors are connected among them through a small world network; each one has its own psychological profile (Imitation, Anti-Imitation, Random); two different strategies for decision making: one of them is based on the trust neighborhood of the investor and the other one considers a technical analysis, the momentum of the market index technique. We analyze the market index fluctuations, the wealth distribution of the investors according to their psychological profiles and the rate of return distribution. Moreover, we analyze the influence of changing the psychological profile of the hub of the network and report interesting results which show how and when anti-imitation becomes the most profitable strategy for investment. Besides this, an intriguing asymmetry of the return rate distribution is explained considering the behavioral aspect of the investors. This asymmetry is quite robust being observed even when a completely different algorithm to calculate the decision making of the investors was applied to it, a remarkable result which, up to our knowledge, has never been reported before.
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