Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/58925
|
Title: | 運用文字探勘技術建立MD&A之 分類閱讀器 Using text-mining technology in developing a classified reader for MD&A |
Authors: | 吳詩婷 Wu, Shih Ting |
Contributors: | 周濟群 Chou, Chi Chun 吳詩婷 Wu, Shih Ting |
Keywords: | 文字性資訊 MD&A 文字探勘 Textual information MD&A text-mining |
Date: | 2012 |
Issue Date: | 2013-07-22 10:20:01 (UTC+8) |
Abstract: | 年報中富含眾多資訊,其中包含財務性資訊與文字性資訊,財務性資訊之分析方法已相當成熟,而文字性資訊受限於格式及檔案類型,而降低投資人使用或分析此類資訊之效率。管理階層討論與分析(Management’s Discussion & Analysis of Financial Condition and Results of Operations,以下簡稱MD&A)係管理階層傳達其經營決策觀點予投資人之媒介,投資人可透過閱讀MD&A取得更多資訊,過去學者之研究亦證實該項目內之文字性資訊有其重要性,由於文字性資訊缺乏通用之分類架構,因此投資人需耗費較多時間與成本分析該資訊。本研究自美國科技業上市公司,隨機選取40家企業2012年之年報作為樣本資料,藉由文字探勘技術,運用TFIDF將MD&A文字性內容分類至EBRC針對MD&A所發布之分類架構,建立分類閱讀器,使投資人可利用透過系統分類並彙整之文句,迅速取得所需之文字性資訊,以協助使用者有效率地閱讀這些非結構化之文字資訊,藉以減少資料蒐集之時間,提升文字性資訊之可使用性。 Annual reports are rich in information, which contains financial information and textual information. While the approach of analyzing financial information is common, textual information is confined by its format or the file type it is stored, thus decreasing the efficiency of analyzing this sort of information. Management’s Discussion & Analysis of Financial Condition and Results of Operations (MD&A) is the vehicle for investor to share the sight of managements’ decision making consideration, through reading MD&A investor could obtain more information. According to past researches, textual information is of importance. Due to the lack of a common framework, investors would consume more time and cost to analyze textual information. This research randomly selected 40 samples from publicly traded technology firms of the United-States. Utilizing text-mining technology and TFIDF, classify textual information of MD&A into the framework EBRC established, developing a classified reader for MD&A. To assist investors read non-constructed textual information efficiently and reduce the time of information gathering, thereby enhancing the usability of textual information. |
Reference: | 李昇暾,2011,決策支援與企業智慧系統第9版,台北市:華泰文化。 周濟群與連子杰,2011年,運用文字探勘與XBRL技術提升企業資訊擷取與整合效益之研究,當代會計,第12卷第1期(5月):85-114。 邱逸紅,2011,“管理層討論和分析”信息質量特徵體系構建,財會月刊,第11期(6月):18-20。 莊友良、曾建勛、陳君銘、李英宗與王毅新,2012,基於文字探勘技術的本體論學習方法研究─以理財相關報導為例,長庚科技學刊,第17期(12月):39-52。 陳隆昇與邱慧如,2009,植基於支撐向量機之語意導向分類器,資訊科技國際期刊,第3卷第2期(12月):15-35。 曾元顯,2004,專利文字之知識探勘:技術與挑戰,現代資訊組織與檢索研討會,台北(11月):111-123。 羅小桂,2005,矩陣奇異值分解(SVD)的應用,井岡山醫專學報,第12卷第4期(7月):133-135。 譚大純與謝德鑫,2006,知識管理,台北市:滄海書局。 Arnold V., J. C. Bedard, J. R. Phillips, and S. G. Sutton. 2009. Understanding professional and non-professional investors’ information requirements. Preliminary Working paper( February). Arnold V., J. C. Bedard, J. R. Phillips, and S. G. Sutton. 2010. Where Do Investors Prefer to Find Nonfinancial Information? Journal of Accountancy. (August 23, 2010). Available at: http://www.journalofaccountancy.com/Web/20102682.htm Arnold V., J. C. Bedard, J. R. Phillips, and S. G. Sutton. 2012. The impact of information tagging in the MD&A on investor decision making: Implications for XBRL. International Journal of Accounting Information Systems (January): 2-20. Baldwin, A., C. Brown, and B. Trinkle. 2006. XBRL: An impacts framework and research challenge. Journal of Emerging Technologies in Accounting 3: 97-116. Barron, O., C. Kile, and T. O’Keefe. 1999. MD&A quality as measured by the SEC and analysts’ earnings forecasts. Contemporary Accounting Research 16(1): 75-109. Bridges, M., E.A. Heron, C. O`Dushlaine, R. Segurado. 2011. Genetic classification of populations using supervised learning. PLoS ONE 6(May): e14802. Bryan, S. H. 1997. Incremental information content of required disclosures contained in management discussion and analysis. The Accounting Review 72(February):285-301. Clarkson, P., J. Kao, and G. Richardson. 1999. Evidence that management discussion and analysis (MD&A) is a part of a firm`s overall disclosure package. Contemporary Accounting Research 16 (1):111-134. Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. 1990. Indexing by latent semantic analysis. Journal of the American Society for Information Science 41(6): 391-407. Eccles, R. G., and S. C. Mavrinac. 1995. Improving the corporate disclosure process. Sloan Management Review 36 (4): 11-25. Enhanced Business Reporting Consortium (EBRC). 2005. The Enhanced Business Reporting Framework. New York, NY: Enhanced Business Reporting Consortium. Enhanced Business Reporting Consortium (EBRC). 2006. EBRC Framework Version 2.1. New York, NY: Enhanced Business Reporting Consortium. Enhanced Business Reporting Consortium (EBRC). 2010. Improving MD&A Reporting. New York, NY: Enhanced Business Reporting Consortium. IFAC. 2008. Financial reporting supply chain: Current perspectives and directions. New York: International Federation of Accountants. Kloptchenko, A .,T. Eklund, J. Karlsson, B. Back, H. Vanharanta, and V. Ari. 2004. Combining data and text mining techniques for analysing financial reports. Intelligent Systems in Accounting, Finance and Management 12 (January-March) :29-41. Landauer, T. K., Foltz, P. W., & Laham, D. 1998. An introduction to latent semantic analysis. Discourse Processes 25: 259-284. Laux, B. 2009. EBRC proposes new XBRL taxonomy for the MD&A. Hitachi Data Interactive.Com Available at: http://hitachidatainteractive.com/2009/04/15/ebrc-proposes-new-xbrl-taxonomy-for-the-mda/ Manning, C., and H. Schutze. 1999. Foundations of statistical natural language processing. Cambridge, MA: MIT Press. Morse, D. 1980. Asymmetrical information in securities markets and trading volume. Journal of Financial and Quantitative Analysis 15 (5): 1129-1148. Petersen, M. A. 2004. Information: hard and soft. Preliminary and Incomplete. Available at: http://www.disas.unisi.it/mat_did/gabbi/729/10.1.1.126.8246[1].pdf Rogers, R., and J. Grant. 1997. Content analysis of Information cited in reports of sell-side financial analysts. Journal of Financial Statement Analysis 3(1):17-30. Salton G., and M. J. McGill. 1983. Introduction to Modern Information Retrieval(1sted.). New York: McGraw-Hill. Schipper, K. 1991. Commentary on analysts` forecasts. Accounting Horizons 5: 105-121. Securities and Exchange Commission (SEC). 1980. Securities Act Release No. 6231(September 2). Securities and Exchange Commission (SEC). 1987. Securities Act Release No. 6711 (April 24). Securities and Exchange Commission (SEC). 1989. Securities Act Release No. 6835 (May 18). Securities and Exchange Commission (SEC). 2003. Interpretation: Commission guidance regarding management`s discussion and analysis of financial condition and results of operations. Available at: http://www.sec.gov/rules/interp/33-8350.htm Securities and Exchange Commission (SEC). 2008. SEC approves interactive data for financial reporting by public companies, mutual funds. Press Release 2008-300. Washington, DC: Securities and Exchange Commission. Securities and Exchange Commission (SEC). 2013. How the SEC protects investors, maintains market integrity, and facilitates capital formation. Available at: http://www.sec.gov/about/whatwedo.shtml Sullivan, D. 2001. Document warehousing and text mining: Techniques for improving business operations, marketing and sales(1sted.). New York, NY: John Wiley & Son, Inc. Sutton, S. G., V. Arnold, J. C. Bedard, and J. R. Phillips. 2012. Enhancing and structuring the MD&A to aid investors when using interactive data. Journal of Information Systems 26 (2): 167-188. Thomas, A. 2003. A tale of two reports. European Business Forum 16 (Winter): 79-81. Visa, A., J. Toivonen, P. Ruokonen, H. Vanharanta, and B. Back. 2000. Knowledge discovery from text documents based on paragraph maps. Proceedings of the 33rd Hawaii International Conference on System Sciences 2: 1-9. Zhou, L. 2007. Ontology learning: State of the art and open issues. Information Technology and Management8 (3): 241-252. |
Description: | 碩士 國立政治大學 會計研究所 100353057 101 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0100353057 |
Data Type: | thesis |
Appears in Collections: | [會計學系] 學位論文
|
Files in This Item:
There are no files associated with this item.
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|