Department of Psychology, Stanford University, Stanford, California 94305
Department of Psychology, Stanford University, Stanford, California 94305.
J Neurosci. 2021 Apr 7;41(14):3266-3274. doi: 10.1523/JNEUROSCI.1727-20.2021. Epub 2021 Mar 8.
Successful investing is challenging since stock prices are difficult to consistently forecast. Recent neuroimaging evidence suggests, however, that activity in brain regions associated with anticipatory affect may not only predict individual choice, but also forecast aggregate behavior out-of-sample. Thus, in two experiments, we specifically tested whether anticipatory affective brain activity in healthy humans could forecast aggregate changes in stock prices. Using functional magnetic resonance imaging, we found in a first experiment ( = 34, 6 females; 140 trials/subject) that nucleus accumbens activity forecast stock price direction, whereas anterior insula (AIns) activity forecast stock price inflections. In a second preregistered replication experiment ( = 39, 7 females) that included different subjects and stocks, AIns activity still forecast stock price inflections. Importantly, AIns activity forecast stock price movement even when choice behavior and conventional stock indicators did not (e.g., previous stock price movements), and classifier analysis indicated that forecasts based on brain activity should generalize to other markets. By demonstrating that AIns activity might serve as a leading indicator of stock price inflections, these findings imply that neural activity associated with anticipatory affect may extend to forecasting aggregate choice in dynamic and competitive environments such as stock markets. Many try but fail to consistently forecast changes in stock prices. New evidence, however, suggests that anticipatory affective brain activity may not only predict individual choice, but also may forecast aggregate choice. Assuming that stock prices index collective choice, we tested whether brain activity sampled during the assessment of stock prices could forecast subsequent changes in the prices of those stocks. In two neuroimaging experiments, a combination of previous stock price movements and brain activity in a region implicated in processing uncertainty and arousal forecast next-day stock price changes-even when behavior did not. These findings challenge traditional assumptions of market efficiency by implying that neuroimaging data might reveal "hidden information" capable of foreshadowing stock price dynamics.
成功的投资具有挑战性，因为股票价格难以持续预测。然而，最近的神经影像学证据表明，与预期情感相关的大脑区域的活动不仅可以预测个体选择，还可以预测样本外的总体行为。因此，在两项实验中，我们特别测试了健康人类的预期情感大脑活动是否可以预测股票价格的总体变化。使用功能磁共振成像，我们在第一项实验中发现（n=34，女性 6 人；每位受试者 140 次试验），伏隔核活动可以预测股票价格的方向，而前岛叶（AIns）活动可以预测股票价格的拐点。在第二项预先注册的重复实验中（n=39，女性 7 人），包括了不同的受试者和股票，AIns 活动仍然可以预测股票价格的拐点。重要的是，即使在选择行为和传统股票指标没有（例如，之前的股票价格走势）的情况下，AIns 活动仍然可以预测股票价格的走势，分类器分析表明基于大脑活动的预测应该可以推广到其他市场。通过证明 AIns 活动可能是股票价格拐点的领先指标，这些发现意味着与预期情感相关的神经活动可能会扩展到预测股票市场等动态和竞争环境中的总体选择。许多人试图预测股票价格的变化，但都以失败告终。然而，新的证据表明，预期情感大脑活动不仅可以预测个体选择，还可以预测总体选择。假设股票价格指数代表集体选择，我们测试了在评估股票价格期间采样的大脑活动是否可以预测这些股票价格的后续变化。在两项神经影像学实验中，之前的股票价格走势和一个涉及处理不确定性和兴奋的区域的大脑活动的组合预测了次日的股票价格变化——即使行为没有预测。这些发现通过暗示神经影像学数据可能揭示出能够预示股票价格动态的“隐藏信息”，挑战了市场效率的传统假设。
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