請用此 Handle URI 來引用此文件：
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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 石百達(Pai-Tai Shih) | |
| dc.contributor.author | Po-Jui Yu | en |
| dc.contributor.author | 余柏叡 | zh_TW |
| dc.date.accessioned | 2022-11-25T06:33:39Z | - |
| dc.date.copyright | 2021-08-18 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-06-30 | |
| dc.identifier.citation | Baker, M., and J. Wurgler. “Investor sentiment and the cross-section of stock returns.” The Journal of Finance 61, No.4(2006): 1645–1680. Brockman, P., Xu Li, and S. McKay Price. “Differences in conference call tones: Managers vs. Analysts.” Financial Analysts Journal 71, No.4(2015): 24-42. Doran, J. S., D. R. Peterson, and S. M. Price. “Earnings conference call content and stock price: The case of REITs.” Journal of Real Estate Finance and Economics 45, No.2(2010): 402–434. Garcia, D. “Sentiment during recessions.” Journal of Finance 68, No.3(2013): 1267–1300. Huang, Y. L., and C. M. Kuan. “Text mining of the FOMC minutes and forecasts of Taiwan economic variables.” Taiwan Economic Review 47, No.3(2019): 363-391. Kearney, C., and S. Liu. “Textual sentiment in finance: A survey of methods and models.” International Review of Financial Analysis 33(2014): 174–185. Kothari, S. P., X. Li, and J. E. Short. “The effect of disclosures by management, analysts, and business press on cost of capital, return volatility, and analyst forecasts: A study using content analysis.” Accounting Review 84, No.5(2009): 1639–1670. Li, F.”The information content of forward-looking statements in corporate filings – A naïve bayesian machine learning approach.” Journal of Accounting Research 48, No.5(2010): 1049-1102. Loughran, T., and B. McDonald. “When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks” The Journal of Finance 66, No.1(2011):35-65. Luangaram, P., and W. Wongwachara. “More than words: A textual analysis of monetary policy communication.” Puey Ungphakorn Institute for Economic Research, PIER Discussion Papers 54(2017). Picault, M., and T. Renault. “Words are not all created equal: A new measure of ECB communication.” Journal of International Money and Finance 79(2017): 136-156. Price, S. McKay, James S. Doran, David R. Peterson, and Barbara A. Bliss. “ Earnings conference calls and stock returns: The incremental informativeness of textual tone” Journal of Banking and Finance 36, No.4(2012): 992-1011. Pyo, D. J. and J. Kim. “News media sentiment and asset prices in Korea: Text-mining approach.” Asia-Pacific Journal of Accounting Economics 28, No.2(2021): 183-205. Shapiro, A. H., and D. Wilson. “Taking the fed at its word: A new approach to estimating central bank objectives using text analysis.” Federal Reserve Bank of San Francisco Working Paper 2(2019). Tetlock, P. C., M. Saar-Tsechansky, and S. Macskassy. “More than words: Quantifying language to measure firm fundamentals.” Journal of Finance 63, No.3(2008): 1437–1467. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/82205 | - |
| dc.description.abstract | 本論文研究2005年第三季至2020年第三季費城半導體指數歷史成份股公司法說會之情緒並建立情緒指標，透過情緒指標分別對公司未來短期及長期股價報酬進行狀態判別，並檢驗在不同狀態下報酬率差異性是否顯著。與Loughran and McDonald (2011) 所使用之詞庫進行比較，檢視新編之詞庫是否改善該詞庫在半導體法說會之情緒判斷能力。 實際驗證發現新編之詞庫在各檢驗皆有改善，且辨別負向文本在不同周期後仍有顯著報酬差異，顯示新編之詞庫在負向情緒判別上有卓越表現。而再進一步仔細探究後得出法說會的主要資訊來源為後段分析師問答部分，而前段公司前言則較無資訊含量，惝若公司前言表現為負向情緒卻依然對未來股價報酬有顯著負影響，推論為當最樂觀的公司內部也主動透露負面情緒，表示公司前景確實產生不確定性，造成投資人拋售股票而負面影響股價。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-25T06:33:39Z (GMT). No. of bitstreams: 1 U0001-2906202118010100.pdf: 1862254 bytes, checksum: 7be2bbb084211bd9346b93ff4fee3ff3 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 致謝 …………………………………………………………………ii 中文摘要 ……………………………………………………………iii 英文摘要 …………………………………………………………… iv 一、 緒論 …………………………………………………………… 1 1.1 研究背景與動機 …………………………………………… 1 1.2 研究目的與論文架構 ……………………………………… 2 二、 文獻探討 ……………………………………………………… 3 三、 研究方法 ……………………………………………………… 5 3.1 研究方法說明 ……………………………………………… 5 3.2 資料來源與特性 …………………………………………… 6 3.3 模型採用與架構說明 ……………………………………… 7 四、 實驗結果 ………………………………………………………11 4.1 實驗結果與彙整 ………………………………………… 11 五、 結論與建議 ……………………………………………………16 5.1 結論 ……………………………………………………… 16 5.2 研究貢獻、限制與建議 ………………………………… 17 參考文獻 …………………………………………………………… 18 附錄 ………………………………………………………………… 20 | |
| dc.language.iso | zh-TW | |
| dc.subject | 文字探勘 | zh_TW |
| dc.subject | Text Mining | en |
| dc.title | 以文字探勘美國半導體法說會判斷未來股價報酬 | zh_TW |
| dc.title | Text Mining: Predicting Semiconductor Stock Price Changes with Earnings Call Sentiment | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.coadvisor | 莊文議(Wen-I Chuang) | |
| dc.contributor.oralexamcommittee | 盧佳琪(Hsin-Tsai Liu),(Chih-Yang Tseng) | |
| dc.subject.keyword | 文字探勘, | zh_TW |
| dc.subject.keyword | Text Mining, | en |
| dc.relation.page | 26 | |
| dc.identifier.doi | 10.6342/NTU202101203 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2021-07-01 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| dc.date.embargo-lift | 2026-06-29 | - |
| 顯示於系所單位： | 財務金融學系 | |
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| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-2906202118010100.pdf 未授權公開取用 | 1.82 MB | Adobe PDF | 檢視/開啟 |
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