Measuring Multidimensional Investment Opportunity Sets with 10-K Text

Abstract

We show that firms’ investment opportunity sets (IOS) are multidimensional. Analyzing Form 10-K texts, we identify 445 unique keywords that predict firms’ future investments during 1995-2009 and combine them into 43 underlying factors. Industry-specific factors include Bio-Pharma, Banking, Information Technology, Oil & Gas and Retail Stores, while more general factors include Equity Intensity, Debt Intensity, Lease, Going Concern and Acquisition. These factors form our multidimensional measures of IOS. They outperform Tobin’s Q and/or industry fixed effects, in predicting out-of-sample (2010-15) investments and related corporate policies, and even inform incrementally over lagged dependent variables. We trace the factors’ improved predictive power to their multidimensional nature, which captures IOS-related variation within and between industries, and stability in IOS that allows 10-K texts to be more informative.

Keywords: Investment Opportunities, IOS, Textual Analysis, Tobin’s Q, Corporate Policies, Lasso

JEL Classification: G31, G32, G35, M41, M21