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动量与投资者模仿的基于智能体市场模型

文章 arXiv papers · 作者: F. M. Stefan et al.
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总结

本研究使用基于智能体的模型，考察投资者行为如何影响模拟股票市场的收益和财富。投资者分布在小世界网络中，具有模仿、反模仿或随机行为特征，并根据可信邻居的信息或基于市场指数的动量信号来选择行动。

分析比较了不同心理特征下的指数波动、收益分布和投资者财富。研究还改变了网络枢纽节点的行为特征，并报告了反模仿策略更有利可图的条件。作者描述了模拟收益率中的不对称性，并称这种不对称性在采用另一种决策算法后仍然存在。这些发现基于模型；摘录没有提供市场实证验证或定量结果，结论取决于网络和行为假设。

核心观点

  • 该模型通过小世界网络连接投资者，并为每位投资者设定一种行为特征。
  • 智能体使用可信邻居的信息或市场指数动量作出决策。
  • 分析比较了不同投资者行为特征下的市场波动、财富和收益。
  • 在模拟中，改变枢纽节点的行为特征会影响哪种策略最有利可图。
  • 采用不同决策算法后，报告的收益率不对称性仍然存在。

标签

股票动量统计学
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# 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.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。