We develop a multi-country model with moral hazard and noise traders and show that investor sentiment should affect employment growth both domestically and abroad. Using a large sample of international industry-level data, we find strong support for the model’s predictions. We show that U.S. investor sentiment has a positive association with labor market conditions around the world, due to spillover effects as well as foreign direct investments from the United States. We also find that U.S. sentiment amplifies the negative effect of local financial crises on job losses, which supports the idea that financial development has a “dark side.”

This paper examines the style-based feedback trading behavior of U.S. mutual fund managers. We provide an empirical version of Barberis and Shleifer’s style-switching model. We find style-based feedback trading for 77% of the funds, half of which is positive (negative) feedback trading. There is evidence for “twin style” switching, where capital is channeled between value and growth, and between large- and small-cap. Growth (value) funds apply more positive (negative) feedback trading. Funds that switch more aggressively are younger and have higher expense ratios. Finally, we find that positive (negative) feedback trading yields positive (negative) alpha.

Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time. We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate. Out-of-sample tests show that the forecasts made by this rule significantly beat a random walk for 5 out of 10 currencies. Furthermore, the currency forecasts generate meaningful investment profits. We demonstrate that the strong performance of the model selection rule is driven by time-varying weights attached to a small set of fundamentals, in line with theory.