Bao et al. (2017) show that in laboratory subjects have problems with both trading an experimental asset and forecasting its price. In this paper I explore these experimental results, by investigating a model in which financial traders individually learn how to use forecasting and/or trading anchor and adjustment heuristics, by updating them with Genetic Algorithms. The model replicates main outcomes of the Bao et al. (2017) experiment, and shows that both forecasters and traders coordinate on asset price oscillations, albeit the trading markets generate larger cycles. Both forecasters and traders learn to chase market trends, and this behavior is reinforced when agents have to perform both tasks. As a result, the famous positive feedback between financial expectations and price trends becomes enhanced and markets generate prices that oscillate between $10\%$ and $350\%$ of the fundamental value.

鲍等人。(2017) 表明，在实验室中，受试者在交易实验资产和预测其价格方面都存在问题。在本文中，我通过研究一个模型来探索这些实验结果，在该模型中，金融交易者通过使用遗传算法更新它们来单独学习如何使用预测和/或交易锚点和调整启发式方法。该模型复制了 Bao 等人的主要结果。(2017) 实验，并表明预测者和交易者都在资产价格波动上进行协调，尽管交易市场会产生更大的周期。预测者和交易者都学会追逐市场趋势，当代理必须执行这两项任务时，这种行为就会得到加强。结果，著名的财务预期与价格趋势之间的正反馈增强了 和市场产生的价格在 $10\%$ 和 $350\%$ 的基本价值。