The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach

ABSTRACT This paper examines the information content of the forward‐looking statements (FLS) in the Management Discussion and Analysis section (MD&A) of 10‐K and 10‐Q filings using a Naïve Bayesian machine learning algorithm. I find that firms with better current performance, lower accruals, smaller size, lower market‐to‐book ratio, less return volatility, lower MD&A Fog index, and longer history tend to have more positive FLSs. The average tone of the FLS is positively associated with future earnings even after controlling for other determinants of future performance. The results also show that, despite increased regulations aimed at strengthening MD&A disclosures, there is no systematic change in…