了解前所未有的事件:基于代理的建模和COVID-19对股票市场的影响
Davide Bazzana1,2, Michele Colturato3, Roberto Savona4
1Department of Economics and Management, University of Brescia, via San Faustino 74/b, 25122 Brescia, Italy.
概括
在COVID-19等极端市场事件期间,交易者对新闻变得更加敏感,转向理性行为. 在这种前所未有的金融冲击之后,不太代表性的信息的影响力显著减少.
科学领域:
- 行为经济学是一种行为经济学.
- 金融市场 金融市场
- 计算金融是指计算金融.
背景情况:
- 由于COVID-19大流行,全球股市出现了前所未有的波动.
- 了解极端事件期间的交易者行为对于金融稳定至关重要.
- 有限理性模型提供了对不确定性下的投资者决策的洞察力.
研究的目的:
- 在COVID-19大流行期间模拟市场交易员的学习过程和决策.
- 调查极端市场事件如何影响交易者的理性和新闻敏感性.
- 分析代表性在金融危机期间交易者行为中的作用.
主要方法:
- 开发一个异质代理模型,结合有限的理性和代表性纠正机制.
- 使用STOXX欧洲600指数数据对模型进行校准,重点关注单日百分比下降幅度最大的时期.
- 模拟极端市场事件后的代理行为.
主要成果:
- 在极端事件发生后,特工对积极和消极的新闻都表现出高度的敏感性.
- 交易者行为转向更合理的后危机状态.
- 发现不太代表性的新闻的通缩效应在极端市场事件发生后会消失.
结论:
- 极端市场事件从根本上改变了交易员的学习和决策过程.
- 代表性是有限理性的关键因素,受到前所未有的冲击的重大影响.
- 这些发现为危机期间的市场动态提供了新的视角,并为未来的行为金融模型提供了信息.
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