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題名 探討美國上市公司MD&A揭露與財務表現一致性之決定因素
Explore the Determinants of the Consistency between US Listed Companies’ MD&A Disclosure and Financial Performance
作者 李宸昕
Lee, Chen Hsin
貢獻者 周濟群
Chou, Chi Chun
李宸昕
Lee, Chen Hsin
關鍵詞 MD&A
K-Means
文字探勘
MD&A
K-Means
text mining
日期 2015
上傳時間 24-Aug-2015 09:53:05 (UTC+8)
摘要 本研究透過文字探勘對美國企業2004年至2014年的MD&A資訊進行分析，並搭配財務資訊相互比較，分析美國企業所揭露的MD&A語調一致性，接著透過實證研究分析造成美國企業MD&A語調一致性結果的原因。MD&A非量化資訊運用Loughran and McDonald正負向詞典、TFIDF、K-Means等技術進行分析，並結合財務資訊分析，分析美國企業2004年至2014年的MD&A資訊；再利用企業績效變異度、企業規模與企業成立年數等變數，來分析影響公司MD&A揭露誇大與否的因素。\n研究結果顯示，企業規模、企業風險程度、分析師追蹤人數與企業成立年\n數皆會深深影響MD&A語調的一致性。除了主要實證分析結果外，另外搭配三組穩健性測試來測試模型的敏感性。本研究希望讓資訊使用者運用企業所揭露的MD&A資訊時，能做更多適當的調整，考慮公司MD&A的揭露是否有過度樂觀誇大或是過度悲觀的情勢，並且可以藉此做出正確的經濟決策。
This study presented a way to analyze the MD&A information of US listed companies from 2004 to 2014 via text mining techniques such as Loughran and McDonald Word Count and TFIDF. Then I cross compare a company’s MD&A information with its financial information using K-Means and establish an index to capture the consistency between the two types of information. Finally, I develop empirical model with explanatory variables such as volatility of earnings, company scale, company’s age, etc. for the consistency index.\nAccording to the empirical results, company scale, company operating risks, analyst coverage, and company’s age are significantly related to the MD&A consistency. Three robustness checks demonstrate the similar results. The results suggest investors an additional way of using MD&A other than merely reading it. Investors should consider whether the MD&A is overstated or understated while using it in their investment decisions.
參考文獻 邱逸紅，2011，“管理層討論和分析”信息質量特徵體系構建，財會月 \n 刊，第11期（6月）：18-20。\nAbrahamson, E. and E. Amir. 1996. The information content \n of the president ‘s letter to shareholders. Journal of \n Business Finance and Accounting 23(8): 1157-1182.\nAmir, E. and B. Lev. 1996. Value relevance of \n nonfinancial information: The wireless \n telecommunications industry. Journal of Accounting and \n Economics 22(1-3): 3-30.\nAntweiler, W., and M. Z. Frank. 2004. Is all that talk \n just noise? The information content of internet stock \n message boards. The Journal of Finance 59(3): \n 1259-1294.\nArnold V., J. C. Bedard, J. R. Phillips, and S. G. \n Sutton. 2012. The impact of information tagging in the \n MD&A on investor decision making: Implications for \n XBRL. International Journal of Accounting Information \n Systems (January): 2-20.\nBack, B., J. Toivonen, H. Vanharanta, and A. Visa. 2001. \n Comparing numerical data and text information from \n annual reports using self-organizing maps.Accounting \n Information Systems：249-269.\nBrown, S. V., and J. W. Tucker. 2011. Large-Sample \n Evidence on Firms’ Year-over-Year MD&A Modifications. \n Journal of Accounting Research 49(2): 309-346.\nBryan, S. H. 1997. Incremental information content of \n required disclosures contained in management \n discussion and analysis. The Accounting Review 72 (2): \n 285-301.\nClarkson, P. M., J. Kao, and G. D. Richardson. 1994. The \n Voluntary Inclusion of Forecasts in the MD&A Section \n of Annual Reports. Contemporary Accounting Research \n 11(1): 423-450.\nCole, C. and Jones C. L. 2004. The Usefulness of MD&A \n Disclosures in the Retail Industry. Journal of \n Accounting, Auditing ,and Finance 19: 361-388.\nErnstberger, J. and G. Michael. 2013. How do firm- and \n country-level governance mechanisms affect firms’ \n disclosure? Journal of Accounting Public Policy 32(3): \n 50-67.\nForker, J. J.1992. Corporate governance and disclosure \n quality. Accounting and Business Research, Vol. 22, \n No. 86: 111-124.\nFrazier, K. B., R. W. Ingram, and B. M. Tennyson.1984. A \n Methodology for the Analysis of Narrative Accounting \n Disclosures. Journal of Accounting Research 22(1): \n 318-331.\nHealy, P. M. and K. G. Palepu. 2001. Information \n asymmetry, corporate disclosure, and the capital \n markets A review of the empirical disclosure \n literature. Journal of Accounting and Economics \n 31(1-3): 405-440.\nHildebrandt, H. W. and R. D. Snyder. 1981. The pollyanna \n hypothesis in business writing: Initial results, \n suggestions for research. Journal of Business \n Communication 18(1): 5-15.\nLi, F. 2010. The information content of forward-looking \n statements incorporate filings - A naïve Bayesian \n learning approach. Journal of Accounting Research \n 48(5): 1049–1102.\nNaser, k. 1998. Comprehensive of disclosure of non-\n financial companies listed on the Amman financial \n market. International Journal of Commerce and \n management vol2(8):pp.88-119.\nPetersen, M. A. 2004. Information : hard and soft. \n Northwestern University. Unpublished.\nPrevits, G., R. Bricker, T. Robinson and S. Young. 1994. \n A Content Analysis of Sell-Side Financial Analyst \n Company Reports. Accounting Horizons 8(2): 55-70.\nQiu, X. Y., P. Srinivasan and N. Street. 2006. Exploring \n the forecasting potential of company annual reports. \n Proceedings of the American Society for Information \n Science and Technology 43(1)：1-15\nRogers, J. L. and A. V. Buskirk. 2009. Shareholder \n litigation and changes in disclosure behavior. Journal \n of Accounting and Economics 47(1-2): 136-156.\nRogers, R., and J. Grant. 1997. Content analysis of \n information cited in reports of sell-side financial \n analysts. Journal of Financial Statement Analysis \n 3(1): 17-30.\nSchipper, K. 1991. Commentary on analysts` forecasts. \n Accounting Horizons 5:105-121.\nSchroeder, N. and C. Gibson. 1990. Readabilities of \n management’s discussion and analysis. Accounting \n Horizons (Dec.): 78-87.\nSullivan, D. 2001. Document Warehousing and Text Mining: \n Techniques for Improving Business Operations, \n Marketing, and Sales.\nVisa, A., J. Toivonen, P. Ruokonen, H. Vanharanta, and B. \n Back. 2000. Knowledge discovery from text documents \n based on paragraph maps. Proceedings of the 33rd \n Hawaii International Conference on System Sciences - \n 2000.\nZhou, L. 2007. Ontology learning: State of the art and \n open issues. Information Technology and Management8 \n (3): 241-252.
描述 碩士
國立政治大學
會計研究所
101353053
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0101353053
資料類型 thesis
dc.contributor.advisor 周濟群zh_TW
dc.contributor.advisor Chou, Chi Chunen_US
dc.contributor.author (Authors) 李宸昕zh_TW
dc.contributor.author (Authors) Lee, Chen Hsinen_US
dc.creator (作者) 李宸昕zh_TW
dc.creator (作者) Lee, Chen Hsinen_US
dc.date (日期) 2015en_US
dc.date.accessioned 24-Aug-2015 09:53:05 (UTC+8)-
dc.date.available 24-Aug-2015 09:53:05 (UTC+8)-
dc.date.issued (上傳時間) 24-Aug-2015 09:53:05 (UTC+8)-
dc.identifier (Other Identifiers) G0101353053en_US
dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=86889-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 會計研究所zh_TW
dc.description (描述) 101353053zh_TW
dc.description.abstract (摘要) 本研究透過文字探勘對美國企業2004年至2014年的MD&A資訊進行分析，並搭配財務資訊相互比較，分析美國企業所揭露的MD&A語調一致性，接著透過實證研究分析造成美國企業MD&A語調一致性結果的原因。MD&A非量化資訊運用Loughran and McDonald正負向詞典、TFIDF、K-Means等技術進行分析，並結合財務資訊分析，分析美國企業2004年至2014年的MD&A資訊；再利用企業績效變異度、企業規模與企業成立年數等變數，來分析影響公司MD&A揭露誇大與否的因素。\n研究結果顯示，企業規模、企業風險程度、分析師追蹤人數與企業成立年\n數皆會深深影響MD&A語調的一致性。除了主要實證分析結果外，另外搭配三組穩健性測試來測試模型的敏感性。本研究希望讓資訊使用者運用企業所揭露的MD&A資訊時，能做更多適當的調整，考慮公司MD&A的揭露是否有過度樂觀誇大或是過度悲觀的情勢，並且可以藉此做出正確的經濟決策。zh_TW
dc.description.abstract (摘要) This study presented a way to analyze the MD&A information of US listed companies from 2004 to 2014 via text mining techniques such as Loughran and McDonald Word Count and TFIDF. Then I cross compare a company’s MD&A information with its financial information using K-Means and establish an index to capture the consistency between the two types of information. Finally, I develop empirical model with explanatory variables such as volatility of earnings, company scale, company’s age, etc. for the consistency index.\nAccording to the empirical results, company scale, company operating risks, analyst coverage, and company’s age are significantly related to the MD&A consistency. Three robustness checks demonstrate the similar results. The results suggest investors an additional way of using MD&A other than merely reading it. Investors should consider whether the MD&A is overstated or understated while using it in their investment decisions.en_US
dc.description.tableofcontents 壹、 緒論 1\n一、 研究背景與動機 1\n二、 研究問題與目的 3\n三、 論文架構 4\n貳、 文獻探討及相關工具介紹 6\n一、 探討量化及非量化資訊之相關文獻 6\n二、 年報使用者運用MD&A資訊之相關文獻 8\n三、 MD&A資訊之相關文獻 10\n四、 群集分析工具K-Means 12\n五、 文字探勘工具 14\n參、 研究方法 18\n一、 研究方法架構 18\n二、 研究樣本 20\n三、 MD&A資料處理 20\n四、 財務資料處理 22\n五、 MD&A資料與財務資料分群一致性分析 23\n六、 建立實證研究模型 24\n肆、 實作結果與分析 32\n一、 蒐集研究樣本 32\n二、 MD&A資料分析 32\n三、 財務資料分析 33\n四、 MD&A資料與財務資料分群一致性分析 34\n五、 實證結果分析 36\n伍、 結論與建議 47\n一、 研究結論 47\n二、 研究限制 49\n三、 研究建議 49\n陸、 參考文獻 50\n一、 文獻 50\n二、 其他資料 52zh_TW
dc.format.extent 1162116 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0101353053en_US
dc.subject (關鍵詞) MD&Azh_TW
dc.subject (關鍵詞) K-Meanszh_TW
dc.subject (關鍵詞) 文字探勘zh_TW
dc.subject (關鍵詞) MD&Aen_US
dc.subject (關鍵詞) K-Meansen_US
dc.subject (關鍵詞) text miningen_US
dc.title (題名) 探討美國上市公司MD&A揭露與財務表現一致性之決定因素zh_TW
dc.title (題名) Explore the Determinants of the Consistency between US Listed Companies’ MD&A Disclosure and Financial Performanceen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 邱逸紅，2011，“管理層討論和分析”信息質量特徵體系構建，財會月 \n 刊，第11期（6月）：18-20。\nAbrahamson, E. and E. Amir. 1996. The information content \n of the president ‘s letter to shareholders. Journal of \n Business Finance and Accounting 23(8): 1157-1182.\nAmir, E. and B. Lev. 1996. Value relevance of \n nonfinancial information: The wireless \n telecommunications industry. Journal of Accounting and \n Economics 22(1-3): 3-30.\nAntweiler, W., and M. Z. Frank. 2004. Is all that talk \n just noise? The information content of internet stock \n message boards. The Journal of Finance 59(3): \n 1259-1294.\nArnold V., J. C. Bedard, J. R. Phillips, and S. G. \n Sutton. 2012. The impact of information tagging in the \n MD&A on investor decision making: Implications for \n XBRL. International Journal of Accounting Information \n Systems (January): 2-20.\nBack, B., J. Toivonen, H. Vanharanta, and A. Visa. 2001. \n Comparing numerical data and text information from \n annual reports using self-organizing maps.Accounting \n Information Systems：249-269.\nBrown, S. V., and J. W. Tucker. 2011. Large-Sample \n Evidence on Firms’ Year-over-Year MD&A Modifications. \n Journal of Accounting Research 49(2): 309-346.\nBryan, S. H. 1997. Incremental information content of \n required disclosures contained in management \n discussion and analysis. The Accounting Review 72 (2): \n 285-301.\nClarkson, P. M., J. Kao, and G. D. Richardson. 1994. The \n Voluntary Inclusion of Forecasts in the MD&A Section \n of Annual Reports. Contemporary Accounting Research \n 11(1): 423-450.\nCole, C. and Jones C. L. 2004. The Usefulness of MD&A \n Disclosures in the Retail Industry. Journal of \n Accounting, Auditing ,and Finance 19: 361-388.\nErnstberger, J. and G. Michael. 2013. How do firm- and \n country-level governance mechanisms affect firms’ \n disclosure? Journal of Accounting Public Policy 32(3): \n 50-67.\nForker, J. J.1992. Corporate governance and disclosure \n quality. Accounting and Business Research, Vol. 22, \n No. 86: 111-124.\nFrazier, K. B., R. W. Ingram, and B. M. Tennyson.1984. A \n Methodology for the Analysis of Narrative Accounting \n Disclosures. Journal of Accounting Research 22(1): \n 318-331.\nHealy, P. M. and K. G. Palepu. 2001. Information \n asymmetry, corporate disclosure, and the capital \n markets A review of the empirical disclosure \n literature. Journal of Accounting and Economics \n 31(1-3): 405-440.\nHildebrandt, H. W. and R. D. Snyder. 1981. The pollyanna \n hypothesis in business writing: Initial results, \n suggestions for research. Journal of Business \n Communication 18(1): 5-15.\nLi, F. 2010. The information content of forward-looking \n statements incorporate filings - A naïve Bayesian \n learning approach. Journal of Accounting Research \n 48(5): 1049–1102.\nNaser, k. 1998. Comprehensive of disclosure of non-\n financial companies listed on the Amman financial \n market. International Journal of Commerce and \n management vol2(8):pp.88-119.\nPetersen, M. A. 2004. Information : hard and soft. \n Northwestern University. Unpublished.\nPrevits, G., R. Bricker, T. Robinson and S. Young. 1994. \n A Content Analysis of Sell-Side Financial Analyst \n Company Reports. Accounting Horizons 8(2): 55-70.\nQiu, X. Y., P. Srinivasan and N. Street. 2006. Exploring \n the forecasting potential of company annual reports. \n Proceedings of the American Society for Information \n Science and Technology 43(1)：1-15\nRogers, J. L. and A. V. Buskirk. 2009. Shareholder \n litigation and changes in disclosure behavior. Journal \n of Accounting and Economics 47(1-2): 136-156.\nRogers, R., and J. Grant. 1997. Content analysis of \n information cited in reports of sell-side financial \n analysts. Journal of Financial Statement Analysis \n 3(1): 17-30.\nSchipper, K. 1991. Commentary on analysts` forecasts. \n Accounting Horizons 5:105-121.\nSchroeder, N. and C. Gibson. 1990. Readabilities of \n management’s discussion and analysis. Accounting \n Horizons (Dec.): 78-87.\nSullivan, D. 2001. Document Warehousing and Text Mining: \n Techniques for Improving Business Operations, \n Marketing, and Sales.\nVisa, A., J. Toivonen, P. Ruokonen, H. Vanharanta, and B. \n Back. 2000. Knowledge discovery from text documents \n based on paragraph maps. Proceedings of the 33rd \n Hawaii International Conference on System Sciences - \n 2000.\nZhou, L. 2007. Ontology learning: State of the art and \n open issues. Information Technology and Management8 \n (3): 241-252.zh_TW