Projects

Title: The Corporate Financial Information Environment.
Start date: December 2012. End date: January 2020. Funder: ESRC. Amount: £424,390.
URL: CFIE Project
Abstract:The quality of information provided to investors by corporate management in publicly traded companies is a matter of central importance to financial market participants. Narrative commentaries represent an increasingly significant component of financial communications. While financial narratives in the UK are shaped in part by prevailing regulations, senior management enjoys significant discretion over the content, structure and presentation of these disclosures. The informativeness of financial narrative disclosures and the way management apply their reporting discretion are key questions for academics and policymakers. Partnering with the UK body responsible for promoting high quality corporate governance and financial reporting - the Financial Reporting Council (FRC) - this interdisciplinary project will combine expertise from accounting with state-of-the-art methods from computational linguistics to examine two key elements of financial disclosure. The first aspect is preliminary earnings announcements (PEAs), which arguably represent the most important disclosure in UK firms' annual reporting calendar. The second aspect is the annual report to shareholders, which forms the largest single recurring disclosure commitment for management. Two opposing perspectives exist on corporate narrative disclosures. On the one hand, proponents argue that narratives provide information beyond that contained in financial data. On the other hand, opponents claim that management exploit the discretion embedded in narrative reporting to obfuscate or present a biased representation of actual performance. While extant work on UK annual report and PEA narrative disclosures provides evidence consistent with both perspectives, both the scope of the research and the generalizeability of findings is compromised because conclusions rely on manual coding methods applied to small samples. This project will develop and use state-of-the-art computerized textual analysis methods to study the properties and usefulness of financial narratives for a comprehensive sample of UK disclosures published between 2003 and 2016. While researchers are already using these methods to study disclosures made by US companies, problems accessing digital PEAs and annual reports coupled with inconsistent document structure has hindered computerized analysis of UK financial narratives and skewed research agendas away from studying UK reporting outcomes. This project will shine much needed light on two key aspects of UK narrative reporting. The work will provide the first large sample analysis of PEAs narratives. The project will also examine a set of contemporary policy-relevant themes relating to the content and structure of UK annual reports. Software tools and datasets from the project will also create new opportunities for the research community. Policymakers are facing pressure to adopt evidenced-based approaches to regulation. While the FRC is committed to conducting impact and evaluation analyses, it is reliant on a relatively small team of research staff to undertake such work, much of which involves manual collection and analysis of unstructured data. The labour-intensive nature of the work inevitably yields results that are hard to generalize and constrains the scope of the FRC's work. As well as examining novel and policy-relevant research questions, this project will embed computerized text analytics methods in the FRC's formal policymaking processes. The methods will complement existing approaches by facilitating lower cost and more comprehensive assessments of regulatory changes and emerging issues in narrative reporting.

Title: The Corporate Financial Information Environment.
Start date: August 2016. End date: March 2019. Funder: Welcome Trust. Amount: £200,000.
URL: BioTM Project
Abstract:This Biomedical Text Mining (BTM) website is used to record information about interdisciplinary research activities at Lancaster University related to explorations of biomedical literature and data using Natural Language Processing and Corpus Linguistics methodologies.