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Title:	UK Annual report narrative disclosure scores
Keywords:	TEXTUAL ANALYSIS LINGUISTICS ANNUAL REPORTS DOCUMENT EXTRACTION CHAIRMAN'S STATEMENTS REMUNERATION REPORTS GOVERNANCE STATEMENTS 2016
Description:	In the CFIE project we analysed more than 10,000 annual reports for a variety of factors as described in the explanatory notes. The analysis results in this spreadsheet. For more details, see the papers listed on the project website: http://ucrel.lancs.ac.uk/cfie/<p>This is an interdisciplinary project involving researchers from three leading Accounting groups (MBS, LUMS, and LSE), and Lancaster’s University Centre for Computer Corpus Research on Language. The project will combine state of the art Natural Language Processing with Market Based Accounting Research methods, to study the role of annual report narratives, Interim Management Statements, and financial media reports in the Corporate Financial Information Environment. It will aim to make available computer based tools suitable for large scale content analysis of annual report narratives.This work will focus on scoring various narratives such as tone, complexity, and forward looking statements. The team will study both the causes and effects of corporate financial disclosures. Controlling for financial statement quality the team will test the effects of narrative disclosures on capital market outcomes such as the cost of capital. Most of the research is based on archival data, so no ethical issues arise. The planned interviews of consenting professionals will be subject to the regulations of the University of Manchester Research Ethics Committee and the ESRC Ethics Code 2010. </p>
URI:	https://t2-4.bsc.es/jspui/handle/123456789/60954
Other Identifiers:	10.5255/UKDA-SN-851859 851859 https://doi.org/10.5255/UKDA-SN-851859
Appears in Collections:	Cessda

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