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題名 基金淨值波動與財務預警-數據分析觀點
Mutual fund`s net asset volatility and financial warning - a data analytics perspective作者 陳羽謙
Chen, Yu-Chien貢獻者 諶家蘭
陳羽謙
Chen, Yu-Chien關鍵詞 基金淨值波動
情緒分析
財務預警
文字探勘
Mutual fund`s net asset volatility
Sentiment analysis
Financial warning
Textual mining日期 2018 上傳時間 20-Jul-2018 17:36:01 (UTC+8) 摘要 不論投資人從哪裡取得財經新聞，新聞的內容和用字偏向正面或負面的寫法，意即情緒分析，都會成為投資人作投資決策的依據。除了直接在資本市場上交易股票的投資人之外，也有不少投資人選擇將錢投入共同基金，交由專業經理人操盤，而這些經理人可能會選擇將投資大眾的錢拿去買股票。因此，投資標的公司股價的漲跌幅也會影響到特定基金的淨值。本研究的目的為探討報導某特定基金或某特定基金之標的公司的新聞情緒分析是否也會影響到基金淨值波動的程度。本文以我國境內133支股票型基金及74家主要的投資標的公司為研究對象，研究期間為2007年至2017年。實證結果顯示，基金淨值的波動與新聞變數有顯著相關，且波動性會受到當天、昨天和前天新聞的影響。實證結果也顯示波動性和正面字詞的字數呈負相關；和負面字詞的字數呈正相關；和新聞的情緒分數呈負相關；和新聞的數量則呈正相關。
Regardless of where investors obtain financial news, the content of the news narrative and the use of words in favor of positive or negative writing, that is, sentiment analysis, will become the basis for investors to make decisions. In addition to the investors who directly trade stocks in the capital market, there are also many investors who choose to invest in mutual funds which are handled by professional managers. The managers may choose to invest the public funds to the stock. Therefore, the rise and fall in the stock price will also affect the net value of the specific fund. The purpose of this study is to investigate whether news media sentiment which report a particular fund or a particular invested company would influence the volatility of the fund`s net value.This study uses 133 domestic equity funds and 74 major invested companies as the research object. The research period is 2007~2017. The empirical results show that the fluctuation of the fund`s net value is significantly related to the news variables, and the volatility will be affected by the news of the day, yesterday, and the day before yesterday. The empirical results also show that volatility is negatively correlated with the number of positive words; positively correlated with the number of negative words; negatively correlated with news sentiment scores; and the number of news stories is positively correlated.參考文獻 中文文獻1.王凱仁，2003，建設公司財務危機動態預警模型之研究，國立交通大學土木工程系研究所碩士論文。2.李明峰，2001，銀行業對企業授信「信用評等表」財務比率預警有效性之實驗分析，國立中山大學財務管理學系研究所碩士論文。3.池祥萱、林煜恩、周賓凰，2007，基金績效持續與聰明錢效果：台灣實證，管理學報，第二十四卷第三期，頁307-330。4.邱顯比、林清珮，1999，共同基金分類與基金績效持續性之研究，中國財務學刊，第七卷第二期，頁63-88。5.林宜萱，2013，財經領域情緒辭典之建置與其有效性之驗證-以財經新聞為元件，國立臺灣大學會計學研究所學位論文。6.林思瑢，2001，以財務及非財務性指標評估建築投資業經營績效之研究，國立中央大學土木工程研究所碩士論文。7.范宏書，2001，建立公營事業之財務預警制度，行政院主計處委託之研究報告。8.洪湘綺，2016，首次公開發行公司股票之初始報酬率與新聞情緒分析之關聯性研究，國立政治大學會計學研究所碩士論文。9.徐清俊、姜志堅，2003，基金績效持續性與基金類型之相關性研究，遠東學報，第二十卷第四期，頁45-58。10.陳安琳、洪嘉苓、李文智，2001，共同基金經理團隊屬性與基金績效之研究，證券市場發展季刊，第十三卷第三期，頁1-27。11.陳肇榮，1983，運用財務比率預測企業財務危機之實證研究，國立政治大學財政研究所博士論文。12.張淵智，1998，金融產業股價泡沫檢定之研究，東吳大學企業管理研究所，未出版碩士論文。13.許馨予，2016，股票價格波動性與新聞情緒分析之關聯性研究，國立政治大學會計學研究所碩士論文。14.鄧志豪、沈中華，2000，銀行及投資人如何由財務報表偵測地雷公司，存款保險資訊季刊，56-79。15.黃耀銜等，2013，企業經營危機預警模型－強調現金流量分析，當代財政，025 期，頁86-95。16.鄭碧月，1997，上市公司營運危機預測模式之研究，朝陽技術學院財務金融研究所碩士論文。17.諶家蘭，2017，科技部之創新行動金融商務科技之跨領域整合研究，結案報告。18.薛麗蘭，2008，國內中小企業財務危機預警模式之探討，國立高雄應用科技大學金融資訊研究所碩士論文。英文文獻19.Akhtar, S., Faff, R., Oliver, B., and Subrahmanyam, A. 2011. The power of bad: the negativity bias in Australian consumer sentiment announcements on stock returns. Journal of Banking & Finance, 35, 1239-1249.20.Altman, I. E. 1968. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.21.Beaver, W. H. 1966. Financial Ratios as predictiors of failure. Journal of Accounting Research, 4, 71-111.22.Blum, M. 1974. Failing company discriminate analysis. Journal of Accounting Research, 12, 72-102.23.Brad, M. B., T. Odean and L. Zheng. 2005. Out of sight, out of mind: the effects of expense on mutual fund flows. Journal of Business, 78, 2095-2119.24.Chen, H., De, P., Hu, Y., and Hwang, B. H. 2014. Wisdom of crowds: the value of stock opinions transmitted through social media. The Review of Financial Studies, 27(5), 1367-1403.25.Chen, Y. J., Wu, C. H., Chen, Y. M., Li, H. Y., and Chen, H. K. 2016. Enhancement of fraud detection for narratives in annual reports. International Journal of Accounting Information Systems, 26, 32-45.26.Deakin, E. B. 1972. A discriminiant analysis of predictors of business failure. Journal of Accounting Research, 167-179.27.Dellavigna, S., Pollet, J. M. 2009. Investor inattention and Friday earnings announcements. The Journal of Finance.28.Fang, L., Peress, J. 2009. Media coverage and the cross-section of stock returns. The Journal of Finance, 5.29.Ferguson, N. J., Philip, D., Lam, H. Y. T., and Guo, J. M. 2015. Media content and stock returns: the predictive power of press. Multinational Finance Journal, 19(1), 1-31.30.Gruber, M. J., 1996, Another puzzle: The growth in actively managed mutual funds, Journal of Finance, 51(2), 783– 810.31.Gurun, U. G., Butler, A. W. 2011. Don’t believe the hype: local media slant, local advertising, and firm value. Journal of Finance, 1-48.32.Henry, E. 2008. Are investors influenced by how earnings press releases are written? Journal of Business Communication, 45(4), 363-407.33.Laitinen, E. K. 1998. Financial ratios and different failure processes. Journal of Business Finance and Accounting, 18(5), 649-673.34.Liu, B. 2012. Sentiment analysis and opinion mining. Morgan & Claypool Publishers.35.Loughran, T., McDonald, B. 2011. When is a liability not a liability? Textual Analysis, dictionaries, and 10-Ks. The Journal of Finance, 1.36.Malkiel, B., 1995, Returms from investing in equity mutual funds 1971 to 1991, Journal of Finance, 50(2), 549-572.37.Mark, M. Carhart., 1997, On persistence in mutual fund performance, Journal of Finance, 52(1), 57-82.38.Meschke, F., Kim, Y. H. 2011. CEO interniews on CNBC. Fifth Singapore International Conference on Finance 2011. 1-64.39.Stephen, J. Brown., Goetzmann, William N., 1995, Performance persistence, Journal of Finance, 50(2), 679-698.40.Sharpe, William F., 1966, Mutual fund performance, Journal of Business, 39(1), 119-138.41.Tetlock, P. C. 2007. Giving content to investor sentiment: the role of media in the stock market. Journal of Finance, 62(3), 1139-1168.42.Tetlock, P. C., Saar-Tsechansky, M., and Macskassy, S. 2008. More than words: quantifying language to measure firms’ fundamentals. The Journal of Finance, 63(3), 1437-1467.43.Wei, S. X., C. Zhang. 2004. Why did individual stocks become more volatile? Journal of Business, 79(1), 259-292.44.Yu, Y., Duan, W., and Cao, Q. 2013. The impact of social and conventional media on firm equity value: a sentiment analysis approach. Decision Support Systems, 55(4), 919-926. 描述 碩士
國立政治大學
會計學系
105353041資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105353041 資料類型 thesis dc.contributor.advisor 諶家蘭 zh_TW dc.contributor.author (Authors) 陳羽謙 zh_TW dc.contributor.author (Authors) Chen, Yu-Chien en_US dc.creator (作者) 陳羽謙 zh_TW dc.creator (作者) Chen, Yu-Chien en_US dc.date (日期) 2018 en_US dc.date.accessioned 20-Jul-2018 17:36:01 (UTC+8) - dc.date.available 20-Jul-2018 17:36:01 (UTC+8) - dc.date.issued (上傳時間) 20-Jul-2018 17:36:01 (UTC+8) - dc.identifier (Other Identifiers) G0105353041 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/118776 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 會計學系 zh_TW dc.description (描述) 105353041 zh_TW dc.description.abstract (摘要) 不論投資人從哪裡取得財經新聞，新聞的內容和用字偏向正面或負面的寫法，意即情緒分析，都會成為投資人作投資決策的依據。除了直接在資本市場上交易股票的投資人之外，也有不少投資人選擇將錢投入共同基金，交由專業經理人操盤，而這些經理人可能會選擇將投資大眾的錢拿去買股票。因此，投資標的公司股價的漲跌幅也會影響到特定基金的淨值。本研究的目的為探討報導某特定基金或某特定基金之標的公司的新聞情緒分析是否也會影響到基金淨值波動的程度。本文以我國境內133支股票型基金及74家主要的投資標的公司為研究對象，研究期間為2007年至2017年。實證結果顯示，基金淨值的波動與新聞變數有顯著相關，且波動性會受到當天、昨天和前天新聞的影響。實證結果也顯示波動性和正面字詞的字數呈負相關；和負面字詞的字數呈正相關；和新聞的情緒分數呈負相關；和新聞的數量則呈正相關。 zh_TW dc.description.abstract (摘要) Regardless of where investors obtain financial news, the content of the news narrative and the use of words in favor of positive or negative writing, that is, sentiment analysis, will become the basis for investors to make decisions. In addition to the investors who directly trade stocks in the capital market, there are also many investors who choose to invest in mutual funds which are handled by professional managers. The managers may choose to invest the public funds to the stock. Therefore, the rise and fall in the stock price will also affect the net value of the specific fund. The purpose of this study is to investigate whether news media sentiment which report a particular fund or a particular invested company would influence the volatility of the fund`s net value.This study uses 133 domestic equity funds and 74 major invested companies as the research object. The research period is 2007~2017. The empirical results show that the fluctuation of the fund`s net value is significantly related to the news variables, and the volatility will be affected by the news of the day, yesterday, and the day before yesterday. The empirical results also show that volatility is negatively correlated with the number of positive words; positively correlated with the number of negative words; negatively correlated with news sentiment scores; and the number of news stories is positively correlated. en_US dc.description.tableofcontents 第一章 緒論 1第一節 研究動機與目的 1第二節 研究問題 2第三節 論文架構 3第二章 文獻探討 4第一節 境內共同基金現況 4第二節 情緒分析文獻 6第三節 財務預警文獻 8第四節 基金相關文獻 11第三章 研究方法 14第一節 研究假說 14第二節 資料來源與收集 16第三節 研究設計 17第四節 研究模型 18第五節 變數解釋 22第四章 研究結果及分析 25第一節 敘述性統計 25第二節 相關係數分析 29第三節 迴歸分析 33第五章 結論 40第一節 研究結論與貢獻 40第二節 研究限制 40附錄 42參考文獻 56 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105353041 en_US dc.subject (關鍵詞) 基金淨值波動 zh_TW dc.subject (關鍵詞) 情緒分析 zh_TW dc.subject (關鍵詞) 財務預警 zh_TW dc.subject (關鍵詞) 文字探勘 zh_TW dc.subject (關鍵詞) Mutual fund`s net asset volatility en_US dc.subject (關鍵詞) Sentiment analysis en_US dc.subject (關鍵詞) Financial warning en_US dc.subject (關鍵詞) Textual mining en_US dc.title (題名) 基金淨值波動與財務預警-數據分析觀點 zh_TW dc.title (題名) Mutual fund`s net asset volatility and financial warning - a data analytics perspective en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中文文獻1.王凱仁，2003，建設公司財務危機動態預警模型之研究，國立交通大學土木工程系研究所碩士論文。2.李明峰，2001，銀行業對企業授信「信用評等表」財務比率預警有效性之實驗分析，國立中山大學財務管理學系研究所碩士論文。3.池祥萱、林煜恩、周賓凰，2007，基金績效持續與聰明錢效果：台灣實證，管理學報，第二十四卷第三期，頁307-330。4.邱顯比、林清珮，1999，共同基金分類與基金績效持續性之研究，中國財務學刊，第七卷第二期，頁63-88。5.林宜萱，2013，財經領域情緒辭典之建置與其有效性之驗證-以財經新聞為元件，國立臺灣大學會計學研究所學位論文。6.林思瑢，2001，以財務及非財務性指標評估建築投資業經營績效之研究，國立中央大學土木工程研究所碩士論文。7.范宏書，2001，建立公營事業之財務預警制度，行政院主計處委託之研究報告。8.洪湘綺，2016，首次公開發行公司股票之初始報酬率與新聞情緒分析之關聯性研究，國立政治大學會計學研究所碩士論文。9.徐清俊、姜志堅，2003，基金績效持續性與基金類型之相關性研究，遠東學報，第二十卷第四期，頁45-58。10.陳安琳、洪嘉苓、李文智，2001，共同基金經理團隊屬性與基金績效之研究，證券市場發展季刊，第十三卷第三期，頁1-27。11.陳肇榮，1983，運用財務比率預測企業財務危機之實證研究，國立政治大學財政研究所博士論文。12.張淵智，1998，金融產業股價泡沫檢定之研究，東吳大學企業管理研究所，未出版碩士論文。13.許馨予，2016，股票價格波動性與新聞情緒分析之關聯性研究，國立政治大學會計學研究所碩士論文。14.鄧志豪、沈中華，2000，銀行及投資人如何由財務報表偵測地雷公司，存款保險資訊季刊，56-79。15.黃耀銜等，2013，企業經營危機預警模型－強調現金流量分析，當代財政，025 期，頁86-95。16.鄭碧月，1997，上市公司營運危機預測模式之研究，朝陽技術學院財務金融研究所碩士論文。17.諶家蘭，2017，科技部之創新行動金融商務科技之跨領域整合研究，結案報告。18.薛麗蘭，2008，國內中小企業財務危機預警模式之探討，國立高雄應用科技大學金融資訊研究所碩士論文。英文文獻19.Akhtar, S., Faff, R., Oliver, B., and Subrahmanyam, A. 2011. The power of bad: the negativity bias in Australian consumer sentiment announcements on stock returns. Journal of Banking & Finance, 35, 1239-1249.20.Altman, I. E. 1968. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.21.Beaver, W. H. 1966. Financial Ratios as predictiors of failure. Journal of Accounting Research, 4, 71-111.22.Blum, M. 1974. Failing company discriminate analysis. Journal of Accounting Research, 12, 72-102.23.Brad, M. B., T. Odean and L. Zheng. 2005. Out of sight, out of mind: the effects of expense on mutual fund flows. Journal of Business, 78, 2095-2119.24.Chen, H., De, P., Hu, Y., and Hwang, B. H. 2014. Wisdom of crowds: the value of stock opinions transmitted through social media. The Review of Financial Studies, 27(5), 1367-1403.25.Chen, Y. J., Wu, C. H., Chen, Y. M., Li, H. Y., and Chen, H. K. 2016. Enhancement of fraud detection for narratives in annual reports. International Journal of Accounting Information Systems, 26, 32-45.26.Deakin, E. B. 1972. A discriminiant analysis of predictors of business failure. Journal of Accounting Research, 167-179.27.Dellavigna, S., Pollet, J. M. 2009. Investor inattention and Friday earnings announcements. The Journal of Finance.28.Fang, L., Peress, J. 2009. Media coverage and the cross-section of stock returns. The Journal of Finance, 5.29.Ferguson, N. J., Philip, D., Lam, H. Y. T., and Guo, J. M. 2015. Media content and stock returns: the predictive power of press. Multinational Finance Journal, 19(1), 1-31.30.Gruber, M. J., 1996, Another puzzle: The growth in actively managed mutual funds, Journal of Finance, 51(2), 783– 810.31.Gurun, U. G., Butler, A. W. 2011. Don’t believe the hype: local media slant, local advertising, and firm value. Journal of Finance, 1-48.32.Henry, E. 2008. Are investors influenced by how earnings press releases are written? Journal of Business Communication, 45(4), 363-407.33.Laitinen, E. K. 1998. Financial ratios and different failure processes. Journal of Business Finance and Accounting, 18(5), 649-673.34.Liu, B. 2012. Sentiment analysis and opinion mining. Morgan & Claypool Publishers.35.Loughran, T., McDonald, B. 2011. When is a liability not a liability? Textual Analysis, dictionaries, and 10-Ks. The Journal of Finance, 1.36.Malkiel, B., 1995, Returms from investing in equity mutual funds 1971 to 1991, Journal of Finance, 50(2), 549-572.37.Mark, M. Carhart., 1997, On persistence in mutual fund performance, Journal of Finance, 52(1), 57-82.38.Meschke, F., Kim, Y. H. 2011. CEO interniews on CNBC. Fifth Singapore International Conference on Finance 2011. 1-64.39.Stephen, J. Brown., Goetzmann, William N., 1995, Performance persistence, Journal of Finance, 50(2), 679-698.40.Sharpe, William F., 1966, Mutual fund performance, Journal of Business, 39(1), 119-138.41.Tetlock, P. C. 2007. Giving content to investor sentiment: the role of media in the stock market. Journal of Finance, 62(3), 1139-1168.42.Tetlock, P. C., Saar-Tsechansky, M., and Macskassy, S. 2008. More than words: quantifying language to measure firms’ fundamentals. The Journal of Finance, 63(3), 1437-1467.43.Wei, S. X., C. Zhang. 2004. Why did individual stocks become more volatile? Journal of Business, 79(1), 259-292.44.Yu, Y., Duan, W., and Cao, Q. 2013. The impact of social and conventional media on firm equity value: a sentiment analysis approach. Decision Support Systems, 55(4), 919-926. zh_TW dc.identifier.doi (DOI) 10.6814/THE.NCCU.ACCT.030.2018.F07 -
