Lion over Elephant: The Power of Structured Volume Disclosure in Explaining the
Capitalization of Firm-Specific Information
Dr. Agnes Cheng
Head and Chair Professor
The Hong Kong Polytechnic University
Date: Friday, June 24
Time: 10:00 - 11:30 a.m.
Location: Royal Bank Room, Scurfield Hall 310
Research has shown that a high volume of disclosures (e.g., the number of words and the file size of financial reports) obscures critical information and reduces the informativeness of disclosures in financial reports. This study proposes a structured disclosure volume measure based on the number of financial items disclosed (NFID) as a simple measure of firm-specific information provided by a firm. We utilize stock price asynchronicity to measure the capitalization of firm-specific information, and find that asynchronicity is positively related to NFID. We also investigate the components of this volume measure, and find that the NFID related to income statements (NFID_IS) drives the capitalization of firm-specific information. This finding is consistent with conventional thinking regarding income statements providing the most value-relevant information. We control for many competing measures of disclosure volume/quality, and our results maintain their strength. Furthermore, our findings are robust to various endogeneity checks, alternative measures, and alternative model specifications.