政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/118603
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113303/144284 (79%)
Visitors : 50799841      Online Users : 816
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/118603


    Title: VIX與財務預警 – 數據分析觀點
    VIX and Financial Warning – A Data Analytics Perspective
    Authors: 呂樂憫
    Leu, Lok-Man
    Contributors: 諶家蘭
    Seng, Jia-Lang
    呂樂憫
    Leu, Lok-Man
    Keywords: 恐慌指數
    新聞
    文字探勘
    情緒分析
    財務預警
    Volatility index
    Financial news
    Text mining
    Sentiment analysis
    Financial warning
    Date: 2018
    Issue Date: 2018-07-12 13:31:58 (UTC+8)
    Abstract: 新聞資訊能幫助投資人快速瞭解金融市場及總體經濟環境所發生之事情。從新聞內容中,投資人可以判斷整體市場的走勢。因此,新聞內容將影響投資人的投資決策,台灣投資人之情緒主要受本地新聞媒體所撰寫之報導所影響。本研究之樣本期間為2007年至2017年,新聞來源為全曜財經資訊股份有限公司(CMoney)資料庫。本研究使用文字探勘技術,研究財務預警新聞與台灣投資人情緒之關聯性。本研究使用台灣恐慌指數(VIXTWN)作為衡量整體台灣投資人情緒之變數,觀察本地產業新聞及國際主要股市新聞與市場恐慌指數之關聯性。

    本研究之結果顯示,台灣投資人之整體情緒受本地產業新聞及全球股市新聞內容所影響。投資人情緒波動將反映在當日及明後兩日之恐慌指數上。新聞中所使用的字詞及語調,將影響投資人之情緒及對市場未來走勢之看法,並進一步影響投資人之投資決策。
    Mass media communicates with readers, investors can understand issues of the financial market through reading news articles. Information provided in the news articles plays an important role in affecting investors’ perspective on the future trend and opportunities of the financial market. Financial news are extracted from CMoney and the research period is 2007 to 2017. In this study, we the text mining technique to analyze the association between financial warning news and investors’ sentiment. The market volatility index (VIXTWN) will be used to quantify Taiwanese investors’ sentiment, models are established to observe how local industrial news and global stock market news affect market volatility.

    The empirical result of this study proves the relationship between local industrial and global stock market news and market volatility. Wordings and tone of news affect investors’ sentiment and their perspective on future market return. Therefore, changes in investors’ sentiment affect their investment decision and further affect market volatility. Moreover, the study proves that market volatility reaction consist of two parts, immediate reaction and delayed reaction.
    Reference: 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. 臺灣大學會計學研究所學位論文。

    張溢晃,2009,財經新聞語料中所隱含之樂悲觀情緒在企業財務危機預警模型構建上的應用,銘傳大學財務金融學系碩士論文。

    經濟日報,2017.9.12,陸股漲勢俏 消費股可望成為領頭羊。

    諶家蘭,2017,創新行動金融商務科技之跨領域整合研究結案報告,科技部研究結案報告。

    Agarwal, V., Arisoy, Y. E., & Naik, N. Y. (2017). Volatility of aggregate volatility and hedge fund returns. Journal of Financial Economics, 125(3), 491-510.

    Akhtar, S., Faff, R., Oliver, B., & Subrahmanyam, A. (2011). The power of bad: The negativity bias in Australian consumer sentiment announcements on stock returns. Journal of Banking & Finance, 35(5), 1239-1249.

    Baba, N., & Sakurai, Y. (2011). Predicting regime switches in the VIX index with macroeconomic variables. Applied Economics Letters, 18(15), 1415-1419.

    Bansal, R., Kiku, D., Shaliastovich, I., & Yaron, A. (2014). Volatility, the Macroeconomy, and asset prices. The Journal of Finance, 69(6), 2471-2511.

    Baker, M., Wurgler, J., & Yuan, Y. (2012). Global, local, and contagious investor sentiment. Journal of Financial Economics, 104(2), 272-287.

    Becker, R., Clements, A. E., & McClelland, A. (2009). The jump component of S&P 500 volatility and the VIX index. Journal of Banking & Finance, 33(6), 1033-1038.

    Benhabib, J., Liu, X., & Wang, P. (2016). Sentiments, financial markets, and macroeconomic fluctuations. Journal of Financial Economics, 120(2), 420-443.

    Brière, M., & Drut, B. (2009). The revenge of purchasing power parity on carry trades during crises (No. 09-013. RS). Universite Libre de Bruxelles.

    Carretta, A., Farina, V., Martelli, D., Fiordelisi, F., & Schwizer, P. (2011). The impact of corporate governance press news on stock market returns. European financial management, 17(1), 100-119.

    Chen, Y. J., Wu, C. H., Chen, Y. M., Li, H. Y., & Chen, H. K. (2017). Enhancement of fraud detection for narratives in annual reports. International Journal of Accounting Information Systems, 26, 32-45.

    Chung, K. H., & Chuwonganant, C. (2014). Uncertainty, market structure, and liquidity. Journal of Financial Economics, 113(3), 476-499.

    Corrado, C. J., & Miller Jr, T. W. (2005). The forecast quality of CBOE implied volatility indexes. Journal of Futures Markets, 25(4), 339-373.

    DellaVigna, S., & Pollet, J. M. (2009). Investor inattention and Friday earnings announcements. The Journal of Finance, 64(2), 709-749.

    Ferguson, N., Philip, D., Lam, H., & Guo, J. M. (2013). Media content and stock returns: The predictive power of press”, Midwest Finance Association 2013 Annual Meeting Papers.

    Fernandes, M., Medeiros, M. C., & Scharth, M. (2014). Modeling and predicting the CBOE market volatility index. Journal of Banking & Finance, 40, 1-10.

    Fleming, J., Ostdiek, B., & Whaley, R. E. (1995). Predicting stock market volatility: A new measure. Journal of Futures Markets, 15(3), 265-302.

    Gray, G. L., & Debreceny, R. S. (2014). A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits. International Journal of Accounting Information Systems, 15(4), 357-380.

    Gilbert, T. (2011). Information aggregation around macroeconomic announcements: Revisions matter. Journal of Financial Economics, 101(1), 114-131.

    Goodell, J. W., & Vähämaa, S. (2013). US presidential elections and implied volatility: The role of political uncertainty. Journal of Banking & Finance, 37(3), 1108-1117.

    Hammer, S., & Russo, C. J. (2012). Tax-Advantaged Investing for an Uncertain Economy: These Seven Strategies May Mitigate Risk and Enhance After-Tax Returns. Journal of Accountancy, 213(5), 28-33.

    Kaplanski, G., & Levy, H. (2010). Sentiment and stock prices: The case of aviation disasters. Journal of Financial Economics, 95(2), 174-201.

    Kelly, B., Pástor, Ľ., & Veronesi, P. (2016). The price of political uncertainty: Theory and evidence from the option market. The Journal of Finance, 71(5), 2417-2480.

    Kim, K., Pandit, S., & Wasley, C. E. (2016). Macroeconomic uncertainty and management earnings forecasts. Accounting Horizons, 30(1), 157-172.

    Kurihara, Y. (2006). The relationship between exchange rate and stock prices during the quantitative easing policy in Japan. International Journal of Business, 11(4), 375.

    Li, Q., Wang, T., Gong, Q., Chen, Y., Lin, Z., & Song, S. K. (2014). Media-aware quantitative trading based on public Web information. Decision support systems, 61, 93-105.

    Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.

    Liu, L. X., Shu, H., & Wei, K. J. (2017). The impacts of political uncertainty on asset prices: Evidence from the Bo scandal in China. Journal of Financial Economics, 286-310.

    Mitchell, M. L., & Mulherin, J. H. (1994). The impact of public information on the stock market. The Journal of Finance, 49(3), 923-950.

    Pastor, L., & Veronesi, P. (2012). Uncertainty about government policy and stock prices. The Journal of Finance, 67(4), 1219-1264.

    Savor, P., & Wilson, M. (2013). How much do investors care about macroeconomic risk? Evidence from scheduled economic announcements. Journal of Financial and Quantitative Analysis, 48(2), 343-375.

    Simon, D. P., & Wiggins, R. A. (2001). S&P futures returns and contrary sentiment indicators. Journal of futures markets, 21(5), 447-462.

    Solomon, D. H. (2012). Selective publicity and stock prices. The Journal of Finance, 67(2), 599-638.

    Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. The Journal of Finance, 62(3), 1139-1168.

    Yang, R., Yu, Y., Liu, M., & Wu, K. (2017). Corporate Risk Disclosure and Audit Fee: A Text Mining Approach. European Accounting Review, 1-12.

    Yin, S., Mazouz, K., Benamraoui, A., & Saadouni, B. (2018). Stock price reaction to profit warnings: the role of time-varying betas. Review of Quantitative Finance and Accounting, 50(1), 67-93.

    Zhang, W., & Skiena, S. (2010). Trading Strategies to Exploit Blog and News Sentiment. In ICWSM.
    Description: 碩士
    國立政治大學
    會計學系
    105353043
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105353043
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.ACCT.025.2018.F07
    Appears in Collections:[Department of Accounting] Theses

    Files in This Item:

    File SizeFormat
    304301.pdf1745KbAdobe PDF2422View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback