In a factor timing context, academic research has focused on identifying a set of predictors that can explain the dynamics of factor portfolios. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce the number of both predictors and portfolios to predict. Characteristic-based models outperform existing methods in terms of exact predictability, as well as investment performance.

We propose a new approach to examine sell-side analysts’ career concerns by relating their forecast boldness to their employers’ news flows. Specifically, we use banking sector news to proxy for the severity of career concerns. Analysts follow more closely the consensus forecast when the prospects of the banking sector are negative (and vice versa). The effect is both economically and statistically significant after controlling for various firm, analyst, brokerage house, and forecasting characteristics, as well as sector and economy wide effects. The more established analysts, in terms of reputation and experience, are generally unaffected by banking sector news. In contrast, their less established peers tend to cluster their forecasts near the consensus after a sequence of negative news flows for banks. Collectively, our results support the notion that during banking stresses when job security is low analysts’ tendency to imitate others increases.