| 摘要(英) |
In the past, most of the research was to detect risks with financial information, and less to explore with non-financial information. At present, there is a few relevant research in the United States, and there is no relevant research in Taiwan, so this paper intends to explore the influence of different financial status companies on the characteristics of shareholder reports. After collecting 9 companies with fraud and 7 companies with crisis, and matching them with the same size and leading companies according to their industry search, the final sample number is a total of 53 companies. Take t-2 to t+2 for a total of five years for a comparison. The M-Score proposed by the Beneish (1999) and the Z-Score model proposed by Altman (1968) are used to assist in the detection of fraud and crisis companies, and observe whether the content of the shareholders’ report has changed when the company is facing different financial conditions.
After training the shareholder report of the leading company into a module, the five consecutive years of the shareholder report of other companies are put into the module, the cosine and European distance are quantified, and is drawn as a scatter map for observation. The results show two extreme cases that one is the change of cosine of fraudulent companies and crisis companies is larger than that of leading companies and the other is companies of the same size, the other is the cosine and European are almost unchanged, that is, the content is almost copied and pasted. Unexpectedly , it is also found that leading company’s European distance changes more , compared with other companies with different financial status. |
| 參考文獻 |
[1] 余清祥, & 葉昱廷. (2020). 以文字探勘技術分析臺灣四大報文字風格. 數位典藏與數位人文, (6), 69-96.
[2] 陳予得. (2021). 應用遷移學習與文字探勘分析致股東報告書.
[3] Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The journal of finance, 23(4), 589-609.
[4] Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24-36.
[5] Bhavani, G., & Amponsah, C. T. (2017). M-Score and Z-Score for detection of accounting fraud. Accountancy Business and the Public Interest, 1(1), 68-86.
[6] 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.
[7] Caserio, C., Panaro, D., & Trucco, S. (2016). Management discussion and analysis in the US financial companies: A data mining analysis. In Strengthening Information and Control Systems (pp. 43-57). Springer, Cham.
[8] Clatworthy, M. A., & Jones, M. J. (2006). Differential patterns of textual characteristics and company performance in the chairman′s statement. Accounting, Auditing & Accountability Journal.
[9] Dalnial, H., Kamaluddin, A., Sanusi, Z. M., & Khairuddin, K. S. (2014). Accountability in financial reporting: detecting fraudulent firms. Procedia-Social and Behavioral Sciences, 145, 61-69.
[10] Davis, A. K., & Tama‐Sweet, I. (2012). Managers’ use of language across alternative disclosure outlets: Earnings press releases versus MD&A. Contemporary Accounting Research, 29(3), 804-837.
[11] Feldman, R., Govindaraj, S., Livnat, J., & Segal, B. (2010). Management’s tone change, post earnings announcement drift and accruals. Review of Accounting Studies, 15(4), 915–953.
[12] Herawati, N. (2015). Application of Beneish M-Score models and data mining to detect financial fraud. Procedia-Social and Behavioral Sciences, 211, 924-930.
[13 ]Li, F. (2010). The information content of forward-looking statements in corporate filings – A naïve Bayesian machine learning approach. Journal of Accounting Research, 48(5), 1049–1102.
[14] MacCarthy, J. (2017). Using Altman Z-score and Beneish M-score models to detect financial fraud and corporate failure: A case study of Enron Corporation. International Journal of Finance and Accounting, 6(6), 159-166.
[15] Wen, P. C., Tsai, Y. L., & Tsai, R. T. H. (2015, October). 基於 Word2Vec 詞向量的網路情緒文和流行音樂媒合方法之研究 (Matching Internet Mood Essays with Pop-Music Based on Word2Vec)[In Chinese]. In Proceedings of the 27th Conference on Computational Linguistics and Speech Processing (ROCLING 2015) (pp. 167-179).
[16] Xiao, X., Ye, S. Z., Yu, L. C., & Lai, K. R. (2017, November). 應用詞向量於語言樣式探勘之研究 (Mining Language Patterns Using Word Embeddings)[In Chinese]. In Proceedings of the 29th Conference on Computational Linguistics and Speech Processing (ROCLING 2017) (pp. 230-243). |
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
至系統瀏覽論文 (2027-6-30以後開放)
plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit