2025/05/23 by Qingwen Liang, Liang, Qingwen, Kind, Matias Carrasco
Business, Management and Accounting · Decision Sciences · Economics, Econometrics and Finance · #Auditing, Earnings Management, Governance #FOS: Economics and business #Forecasting Techniques and Applications #General Economics (econ.GN) #Insurance and Financial Risk Management
paper · pdf · doi:10.48550/arxiv.2505.18419
openalex publication_date 2025/05/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper examines the impact of managers' non-responses (NORs) during quarterly earnings calls on analyst forecast behavior by developing a novel measure of NORs using two large language models: ChatGPT-4 and LLaMA 3.3. We adopt a three step prompting approach including identification, classification, and evaluation, to extract NORs from earnings call transcripts of S&P 500 firms. We find that a higher incidence of NORs is significantly associated with greater analyst forecast errors, dispersion, and uncertainty. These effects are more pronounced among firms with high institutional ownership, greater R&D expenditures, operations across multiple industries, and earnings calls held during the COVID-19 period. Further analysis shows that NORs are followed by greater post-earnings announcement drift, higher return volatility, increased trading volume, and wider bid-ask spreads, suggesting that NORs raise information processing costs and exacerbate uncertainty. Overall, our findings indicate that managers' non-responses during earnings calls impair the information environment for analysts and investors.