How to quantify the informational content of analyst reports? In this short methodological paper, we propose a measure of information contribution (IC), defined in the spirit of Shapley values. We use natural language processing to identify topics for over 90,000 analyst reports for S&P 500...

We document that the relative placement of analysts' target price within their subjective distribution of scenario-based valuations for the covered firm (i.e., tilt) is informative to investors. When analysts forecast price appreciation, tilt incrementally predicts ex post valuation errors and...

We use a dataset of sell-side analysts' scenario-based equity valuation estimates to examine whether analysts can assess the state-contingent risk surrounding a firm's fundamental value. We find that the spread in analysts' scenario-based valuations captures the riskiness of operations and...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

Using a novel database, we show that the stock-price impact of analyst trade ideas is at least as large as the impact of stock recommendation, target price, and earnings forecast changes, and that investors following trade ideas can earn significant abnormal returns. Trade ideas triggered by...

Analysts often update their recommendations following corporate news. Questions have been raised regarding analysts' ability to generate new information beyond recent corporate events. Employing a comprehensive database on corporate news we show that only a small minority of 27.9% of all...

Following the Global Settlement, analysts extensively use a top pick designation to highlight their highest conviction best ideas. Such a designation enables analysts to provide greater granularity of information, but it can potentially be influenced by conflicts of interest. Examining a...

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...

We document that investors can actually profit from the contemporaneous link between earnings accuracy and recommendation profitability (Loh and Mian (2006)). Differentiating between "able" and "lucky" analysts we suggest an implementable, i.e. look-ahead bias free, trading strategy that yields...