We show that geographical variation in the level of investor sophistication influences local asset prices. Investors in less sophisticated regions exhibit stronger trading correlations, and correspondingly, the returns of firms headquartered in less sophisticated areas are more strongly correlated, especially when local economic conditions are unusually bad or good. Further, we show that local economic conditions have a greater ability to predict local stock returns in U.S. states with less sophisticated retail investors. This evidence of predictability is stronger in regions with strong local bias. A trading strategy that exploits the predictive ability of local economic indicators earns 5-7% higher risk-adjusted returns in U.S. regions with less sophisticated investors. These asset pricing results are driven by the sophistication of actual local investors, and not by the characteristics of the broader local population. Our results disappear when we use population-wide measures of sophistication. Collectively, these results provide evidence of investor sophistication-induced segmentation in U.S. capital markets.

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投资者成熟度和资产价格

我们表明，投资者成熟度的地域差异会影响当地资产价格。较不成熟地区的投资者表现出更强的交易相关性，相应地，总部位于较不成熟地区的公司的回报相关性更强，尤其是当当地经济状况异常糟糕或异常时。此外，我们还表明，当地经济状况更能预测美国各州的本地股票回报，而散户投资者并不那么成熟。在具有强烈局部偏差的区域中，这种可预测性的证据更强。一种利用当地经济指标预测能力的交易策略，在美国地区投资人不太成熟的地区，风险调整后的回报会高出 5-7%。这些资产定价结果是由实际本地投资者的成熟度所驱动，而不是由更广泛的本地人口的特征所驱动。当我们使用全人群的复杂性衡量标准时，我们的结果就会消失。总的来说，这些结果提供了美国资本市场中投资者复杂性引起的细分的证据。