走向进化：基于市场生态主体的US股票型基金II模型
Towards Evology: a Market Ecology Agent-Based Model of US Equity Mutual Funds II
摘要：
基于Agent的模型（ABM）适合于对金融市场等异构、交互系统进行建模。我们介绍了Evology的最新进展：美国股市的一个异质的，经验校准的市场生态代理模型。价格内生于具有不同投资行为的市场参与者的相互作用及其对基本面的反应。这种方法允许测试交易策略，同时考虑该策略与其他市场参与者和条件的相互作用。这些早期结果鼓励ABM和ML算法之间更紧密的联系，以使用机器学习算法测试和优化投资策略。
英文摘要：
Agent-based models (ABMs) are fit to model heterogeneous, interacting systems like financial markets. We present the latest advances in Evology: a heterogeneous, empirically calibrated market ecology agent-based model of the US stock market. Prices emerge endogenously from the interactions of market participants with diverse investment behaviours and their reactions to fundamentals. This approach allows testing trading strategies while accounting for the interactions of this strategy with other market participants and conditions. Those early results encourage a closer association between ABMs and ML algorithms for testing and optimising investment strategies using machine learning algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
