We examine disagreement between management and Thomson Datastream over the persistence of earnings components. Using income statement and footnote disclosures, we identify the source and properties of disputed items. Disagreements typically reflect opaque reporting practices (for example, in the...

Non-GAAP earnings reporting has been linked with both informative and strategic incentives. We seek to disentangle these conflicting effects by examining the association between non-GAAP earnings disclosure and transitory items in GAAP earnings, conditional on managers' reporting incentives. We...

We provide a methodological contribution by developing, describing and evaluating a method for automatically retrieving and analysing text from digital PDF annual report files published by firms listed on the London Stock Exchange (LSE). The retrieval method retains information on document...

We critically assess mainstream accounting and finance research applying methods from computational linguistics (CL) to study financial discourse. We also review common themes and innovations in the literature and assess the incremental contributions of work applying CL methods over manual...

We compare the performance of machine learning algorithms and wordlists at replicating manual coding of sentence-level tone and attribution in earnings press releases. We train learning algorithms on a sample of manually annotated performance sentences and assess accuracy using a separate...

We measure annual report commentary articulating entities' business model and strategy, and then examine the capital market effects of enhancing such disclosure. Our empirical disclosure proxy is based on n-grams drawn from popular strategy textbooks and the academic strategy literature....