MEASURING TIMELINESS OF ANNUAL REPORTS FILING BY JUMP ADDITIVE MODELS

• 成果类型: Article
• 署名作者: Kang, Yicheng
• 署名单位: Bentley University
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/20-AOAS1365
• 发表日期: 2020
• 页码: 1604-1621
• 关键词: trading volume reaction; Change-point Detection; bandwidth selection; earnings reconciliation; information-content; regression; 10-k; inference; IFRS

摘要

Foreign public issuers (FPIs) are required by the Securities and Exchanges Commission (SEC) to file Form 20-F as comprehensive annual reports. In an effort to increase the usefulness of 20-Fs, the SEC recently enacted a regulation to accelerate the deadline of 20-F filing from six months to four months after the fiscal year-end. The rationale is that the shortened reporting lag would improve the informational relevance of 20-Fs. In this work we propose a jump additive model to evaluate the SEC's rationale by investigating the relationship between the timeliness of 20-F filing and its decision usefulness using the market data. The proposed model extends the conventional additive models to allow possible discontinuities in the regression functions. We suggest a two-step jump-preserving estimation procedure and show that it is statistically consistent. By applying the procedure to the 20-F study, we find a moderate positive association between the magnitude of the market reaction and the filing timeliness when the acceleration is less than 17 days. We also find that the market considers the filings significantly more informative when the acceleration is more than 18 days and such reaction tapers off when the acceleration exceeds 40 days.