We find that mutual funds holding a larger concentration of high gross profitability stocks generate better future performance. The outperformance of these funds is not driven by a profitability-related risk premium and is not a byproduct of fund managers' exploitation of other well-known...

We use unsupervised machine learning techniques of natural language processing to measure the semantic relatedness of firms’ narrative risk disclosures (NRD) in the “risk factor” section of their annual reports. We find strong return predictability among firms with overlapping NRD. This...

Based on 10-K textual analysis, we assemble firm-level offshore sales networks (OSN) and find strong return predictability among industry participants that have overlapping offshore sales activities. This intra-industry return predictability based on offshore sales networks is distinct from that...

We study how mutual fund managers gain an edge in selecting stocks in an era of globalization. We use textual analysis to construct a new measure that captures a mutual fund's offshore exposure concentration through holding U.S. multinational firms. The proposed offshore concentration index...

This paper analyzes the roles of idiosyncratic risk and firm-level conditional skewness in determining cross-sectional returns. It is shown that the traditional EGARCH estimates of conditional idiosyncratic volatility may bring significant finite sample estimation bias in the presence of...