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題名 COVID-19疫情期間財務資訊揭露之研究
Two Essays on Financial Information Disclosure in COVID-19 Pandemic作者 方東杰
Fang, Dong-Jie貢獻者 林士貴<br>張興華
Lin, Shih-Kuei<br>Chang, Hsing-Hua
方東杰
Fang, Dong-Jie關鍵詞 10-K & 10-Q財報
法説會
自然語言處理
盈餘慣性
有限注意力理論
Forms 10-K & 10-Q
Earnings call
Natural language processing
Post-earnings announcement drift
Limited attention theory日期 2024 上傳時間 4-Aug-2025 14:31:10 (UTC+8) 摘要 本博士學位論文規劃將包含兩篇實證論文，主要探討財務資訊揭露中非結構化文本資料對金融市場的影響。 第一篇論文探究企業在面對SARS、2008年次貸危機與COVID-19所引起之經濟衰退時的反應狀況。本文基於美國上市企業10-K、10-Q財報之管理層討論與分析（Management's Discussion and Analysis, MD&A）章節及企業法説會（earnings call）逐字稿，建立三個反應變數加以衡量：條件曝露（conditional exposure）、條件情緒（conditional sentiment）與條件風險（conditional risk）。實證結果表明，10-K、10-Q財報與企業法説會之反應變數會對事件發生後之股票持有報酬產生不同影響。本文透過三種拆解方式進一步研究造成該差異之原因。與過往研究發現不同：在談論經濟衰退時，相較於法説會中分析師的提問，市場對管理層的論述有更强烈的反應。但與此同時，分析師在質詢過程中確實提出了值得注意的風險。另一方面，管理層可能透過在法説會中掩蓋與風險相關的訊息，從而減少其對股票報酬的負面影響。 第二篇論文以COVID-19疫情為例，探討系統性衝擊下盈餘慣性（post-earnings announcement drift, PEAD）。不同於過往文獻所發現之盈餘慣性的減弱，本文發現這一異象在疫情期間仍然存在。基於有限注意力理論，本文探討該現象之成因。實證結果表明，就信號傳遞的角度而言，對於系統性衝擊的廣泛揭露導致盈餘慣性更為強烈。然而，對COVID-19的消極揭露削弱了盈餘慣性，而這可被負面偏差（Negative Bias）所解釋。另一方面，本文發現法說會的延遲召開、與10-K及10-Q財報發佈的更大時間間隔，以及兩者提及疫情時情緒表達的更不一致會透過增加投資者的信息處理成本而强化盈餘慣性。
This Ph.D. dissertation consists of two essays that primarily investigate the impact of unstructured textual data in financial information disclosure on financial markets. The first essay examines how corporates respond to economic recessions triggered by events such as SARS, the 2008 subprime crisis, and COVID-19. Based on the Management's Discussion and Analysis (MD&A) section in the 10-K and 10-Q filings and the earnings calls transcripts of listed stocks in the United States, three response variables are constructed: conditional exposure, conditional sentiment, and conditional risk. Empirical results show that the response measures in 10-K & 10-Q filings have different impacts on post-release returns from those in earnings calls. We further explore the causes of this difference through three decompositions. Different from prior research, we find that when discussing economic recessions, the market more react to management narratives than analysts' questions during earnings calls. Nevertheless, analysts do bring up significant risks during the questioning process. On the other hand, management may obscure risk-related information in earnings calls, reducing its negative impact on stock returns. The second essay examines the post-earnings announcement drift (PEAD) under the systemic shock by taking the COVID-19 pandemic as an example. Though much prior literature has proved the decline of PEAD, I find this anomaly still existed during the global pandemic. Based on the limited attention theory, I investigate the cause of such a phenomenon. From the perspective of signaling, the empirical results show that the broad disclosure of unexpected systemic shock leads to a stronger PEAD. However, firms with negative disclosure about COVID-19 have weaker PEAD due to the negative bias. On the other hand, I find that a later convening of the earnings conference, a larger time gap, and more inconsistent emotional expressions between the earnings call and Forms 10-K & 10-Q strengthen the PEAD by increasing the investors’ information processing cost.參考文獻 References of Chapter 1 Aguiar, M., Hurst, E., & Karabarbounis, L. (2013). Time use during the great recession. American Economic Review, 103(5), 1664-96. Asthana, S., Balsam, S., & Sankaraguruswamy, S. (2004). Differential response of small versus large investors to 10‐K filings on EDGAR. The Accounting Review, 79(3), 571-589. Baker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M., & Viratyosin, T. (2020). The unprecedented stock market response to COVID-19. The Review of Asset Pricing Studies, 10(4), 742-758. Ball, L. (2014). Long-term damage from the Great Recession in OECD countries. European Journal of Economics and Economic Policies: Intervention, 11(2), 149-160. Barrios, J. M., & Hochberg, Y. (2020). Risk perception through the lens of politics in the time of the COVID-19 pandemic. NBER working paper. Bissoondoyal-Bheenick, E., Do, H., Hu, X., & Zhong, A. (2021). Learning from SARS: Return and volatility connectedness in COVID-19. Finance research letters, 41, 101796. Borochin, P. A., Cicon, J. E., DeLisle, R. J., & Price, S. M. (2018). The effects of conference call tones on market perceptions of value uncertainty. Journal of Financial Markets, 40, 75-91. Bretscher, L., Hsu, A., Simasek, P., & Tamoni, A. (2020). COVID-19 and the cross-section of equity returns: Impact and transmission. The Review of Asset Pricing Studies, 10(4), 705-741. Brockman, P., Li, X., & Price, S. M. (2015). Differences in conference call tones: Managers vs. analysts. Financial Analysts Journal, 71(4), 24-42. Brockman, P., Li, X., & Price, S. M. (2017). Conference call tone and stock returns: Evidence from the Stock Exchange of Hong Kong. Asia‐Pacific Journal of Financial Studies, 46(5), 667-685. Brown, S. V., & Tucker, J. W. (2011). Large‐sample evidence on firms’ year‐over‐year MD&A modifications. Journal of Accounting Research, 49(2), 309-346. Campbell, J. L., Chen, H., Dhaliwal, D. S., Lu, H. M., & Steele, L. B. (2014). The information content of mandatory risk factor disclosures in corporate filings. Review of Accounting Studies, 19(1), 396-455. Chen, J. V., Nagar, V., & Schoenfeld, J. (2018). Manager-analyst conversations in earnings conference calls. Review of Accounting Studies, 23(4), 1315-1354. Cheng, I. H. (2020). Volatility markets underresponsed to the early stages of the COVID-19 pandemic. The Review of Asset Pricing Studies, 10(4), 635-668. Christiano, L. J., Eichenbaum, M. S., & Trabandt, M. (2015). Understanding the great recession. American Economic Journal: Macroeconomics, 7(1), 110-67. Davis, A. K., Piger, J. M., & Sedor, L. M. (2012). Beyond the numbers: Measuring the information content of earnings press release language. 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F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of general psychology, 5(4), 323-370. Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: delayed price response or risk premium?. Journal of Accounting Research, 27, 1-36. Bernard, V. L., & Thomas, J. K. (1990). Evidence that stock prices do not fully reflect the implications of current earnings for future earnings. Journal of Accounting and Economics, 13(4), 305-340. Bhushan, R. (1994). An informational efficiency perspective on the post-earnings announcement drift. Journal of Accounting and Economics, 18(1), 45-65. Brown, N.C., Elliott, W.B., Wermers, R. and White, R.M. (2022). News or noise: mobile internet technology and stock market activity. SSRN Working Paper. Brown, S. V., & Tucker, J. W. (2011). Large‐sample evidence on firms’ year‐over‐year MD&A modifications. Journal of Accounting Research, 49(2), 309-346. Campbell, D., Loumioti, M. and Wittenberg-Moerman, R. (2019). Making sense of soft information: Interpretation bias and loan quality. Journal of Accounting and Economics, 68(2-3), 101240. Campbell, J. L., Chen, H., Dhaliwal, D. S., Lu, H. M., & Steele, L. B. (2014). The information content of mandatory risk factor disclosures in corporate filings. Review of Accounting Studies, 19(1), 396-455. Chan, L. K., Jegadeesh, N., & Lakonishok, J. (1996). Momentum strategies. Journal of Finance, 51(5), 1681-1713. Chen, Z., & Kim, B. C. (2020). Fundamental Risk Sources and Pricing Factors. SSRN Working Paper. Chiu, P.C., Lourie, B., Nekrasov, A. and Teoh, S.H. (2021). Cater to thy client: Analyst responsiveness to institutional investor attention. Management Science, 67(12), 7455-7471. Choi, H.M. and Gupta-Mukherjee, S. (2022). Analysts’ Use of Industry-level and Firm-Specific Information: Implications for Information Production. SSRN Working Paper. Daniel, K., Hirshleifer, D., & Sun, L. (2020). Short-and long-horizon behavioral factors. 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The negativity bias and perceived return distributions: Evidence from a pandemic. Journal of Financial Economics, 147(3), 627-657. Stephany, F., Neuhäuser, L., Stoehr, N., Darius, P., Teutloff, O., & Braesemann, F. (2022). The CoRisk-Index: a data-mining approach to identify industry-specific risk perceptions related to Covid-19. Humanities and Social Sciences Communications, 9(1), 1-15. Taylor, D. (2012). Post-Earnings Announcement Drift and Related Anomalies. The handbook of equity market anomalies: Translating market inefficiencies into effective investment strategies, 91-115. You, H., & Zhang, X. J. (2011). Limited attention and stock price drift following earnings announcements and 10‐K filings. China Finance Review International, 1(4), 358-387. 描述 博士
國立政治大學
金融學系
108352506資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108352506 資料類型 thesis dc.contributor.advisor 林士貴<br>張興華 zh_TW dc.contributor.advisor Lin, Shih-Kuei<br>Chang, Hsing-Hua en_US dc.contributor.author (Authors) 方東杰 zh_TW dc.contributor.author (Authors) Fang, Dong-Jie en_US dc.creator (作者) 方東杰 zh_TW dc.creator (作者) Fang, Dong-Jie en_US dc.date (日期) 2024 en_US dc.date.accessioned 4-Aug-2025 14:31:10 (UTC+8) - dc.date.available 4-Aug-2025 14:31:10 (UTC+8) - dc.date.issued (上傳時間) 4-Aug-2025 14:31:10 (UTC+8) - dc.identifier (Other Identifiers) G0108352506 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158583 - dc.description (描述) 博士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 金融學系 zh_TW dc.description (描述) 108352506 zh_TW dc.description.abstract (摘要) 本博士學位論文規劃將包含兩篇實證論文，主要探討財務資訊揭露中非結構化文本資料對金融市場的影響。 第一篇論文探究企業在面對SARS、2008年次貸危機與COVID-19所引起之經濟衰退時的反應狀況。本文基於美國上市企業10-K、10-Q財報之管理層討論與分析（Management's Discussion and Analysis, MD&A）章節及企業法説會（earnings call）逐字稿，建立三個反應變數加以衡量：條件曝露（conditional exposure）、條件情緒（conditional sentiment）與條件風險（conditional risk）。實證結果表明，10-K、10-Q財報與企業法説會之反應變數會對事件發生後之股票持有報酬產生不同影響。本文透過三種拆解方式進一步研究造成該差異之原因。與過往研究發現不同：在談論經濟衰退時，相較於法説會中分析師的提問，市場對管理層的論述有更强烈的反應。但與此同時，分析師在質詢過程中確實提出了值得注意的風險。另一方面，管理層可能透過在法説會中掩蓋與風險相關的訊息，從而減少其對股票報酬的負面影響。 第二篇論文以COVID-19疫情為例，探討系統性衝擊下盈餘慣性（post-earnings announcement drift, PEAD）。不同於過往文獻所發現之盈餘慣性的減弱，本文發現這一異象在疫情期間仍然存在。基於有限注意力理論，本文探討該現象之成因。實證結果表明，就信號傳遞的角度而言，對於系統性衝擊的廣泛揭露導致盈餘慣性更為強烈。然而，對COVID-19的消極揭露削弱了盈餘慣性，而這可被負面偏差（Negative Bias）所解釋。另一方面，本文發現法說會的延遲召開、與10-K及10-Q財報發佈的更大時間間隔，以及兩者提及疫情時情緒表達的更不一致會透過增加投資者的信息處理成本而强化盈餘慣性。 zh_TW dc.description.abstract (摘要) This Ph.D. dissertation consists of two essays that primarily investigate the impact of unstructured textual data in financial information disclosure on financial markets. The first essay examines how corporates respond to economic recessions triggered by events such as SARS, the 2008 subprime crisis, and COVID-19. Based on the Management's Discussion and Analysis (MD&A) section in the 10-K and 10-Q filings and the earnings calls transcripts of listed stocks in the United States, three response variables are constructed: conditional exposure, conditional sentiment, and conditional risk. Empirical results show that the response measures in 10-K & 10-Q filings have different impacts on post-release returns from those in earnings calls. We further explore the causes of this difference through three decompositions. Different from prior research, we find that when discussing economic recessions, the market more react to management narratives than analysts' questions during earnings calls. Nevertheless, analysts do bring up significant risks during the questioning process. On the other hand, management may obscure risk-related information in earnings calls, reducing its negative impact on stock returns. The second essay examines the post-earnings announcement drift (PEAD) under the systemic shock by taking the COVID-19 pandemic as an example. Though much prior literature has proved the decline of PEAD, I find this anomaly still existed during the global pandemic. Based on the limited attention theory, I investigate the cause of such a phenomenon. From the perspective of signaling, the empirical results show that the broad disclosure of unexpected systemic shock leads to a stronger PEAD. However, firms with negative disclosure about COVID-19 have weaker PEAD due to the negative bias. On the other hand, I find that a later convening of the earnings conference, a larger time gap, and more inconsistent emotional expressions between the earnings call and Forms 10-K & 10-Q strengthen the PEAD by increasing the investors’ information processing cost. en_US dc.description.tableofcontents Chapter 1. How Do Corporates Respond to Economic Recessions? Evidence from Form 10-K, 10-Q, and Earnings Call Transcripts 1 1.1 Introduction 2 1.2 Measures and Hypotheses 8 1.2.1 Keywords lists 8 1.2.2 Response measures 9 1.2.3 Decomposition measures 11 1.2.4 Hypotheses 13 1.3 Data 15 1.4 Empirical Results 16 1.4.1 How do response measures impact the post-release holding period returns? 16 1.4.2 What causes the differences between earnings calls and Form 10-K & 10-Q? 19 1.5 Conclusion 25 References 27 Chapter 2. Post-Earnings Announcement Drift, Systemic Shock, and Limited Attention: Evidence from COVID-19 51 2.1 Introduction 52 2.2 Literature Review 55 2.2.1 Post earnings announcement drift (PEAD) 55 2.2.2 Limited attention theory 56 2.2.3 Information disclosure in earnings calls and Forms 10-K & 10-Q 57 2.3 Theoretical Foundation and Hypotheses Development 58 2.3.1 Hypotheses for systemic shock disclosure 58 2.3.2 Incomplete disclosure model 59 2.3.3 Hypotheses for incomplete disclosure 63 2.4 Data and Methodologies 64 2.4.1 Data 64 2.4.2 Measuring earnings surprise 64 2.4.3 Constructing linguistic metrics 66 2.5 Empirical Results 69 2.5.1 Descriptive statistics 69 2.5.2 Systemic shock disclosure: Information overload and negative bias 70 2.5.3 Incomplete disclosure: Information processing cost 73 2.6 Conclusion 75 References 77 Appendix A. Variable definitions 88 zh_TW dc.format.extent 1549461 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108352506 en_US dc.subject (關鍵詞) 10-K & 10-Q財報 zh_TW dc.subject (關鍵詞) 法説會 zh_TW dc.subject (關鍵詞) 自然語言處理 zh_TW dc.subject (關鍵詞) 盈餘慣性 zh_TW dc.subject (關鍵詞) 有限注意力理論 zh_TW dc.subject (關鍵詞) Forms 10-K & 10-Q en_US dc.subject (關鍵詞) Earnings call en_US dc.subject (關鍵詞) Natural language processing en_US dc.subject (關鍵詞) Post-earnings announcement drift en_US dc.subject (關鍵詞) Limited attention theory en_US dc.title (題名) COVID-19疫情期間財務資訊揭露之研究 zh_TW dc.title (題名) Two Essays on Financial Information Disclosure in COVID-19 Pandemic en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) References of Chapter 1 Aguiar, M., Hurst, E., & Karabarbounis, L. (2013). Time use during the great recession. American Economic Review, 103(5), 1664-96. Asthana, S., Balsam, S., & Sankaraguruswamy, S. (2004). 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