| dc.contributor.advisor | 吳啟銘 | zh_TW |
| dc.contributor.advisor | Wu, Chi Ming | en_US |
| dc.contributor.author (Authors) | 傅奇珅 | zh_TW |
| dc.contributor.author (Authors) | Fu, Chi Shen | en_US |
| dc.creator (作者) | 傅奇珅 | zh_TW |
| dc.creator (作者) | Fu, Chi Shen | en_US |
| dc.date (日期) | 2009 | en_US |
| dc.date.accessioned | 8-Dec-2010 15:46:52 (UTC+8) | - |
| dc.date.available | 8-Dec-2010 15:46:52 (UTC+8) | - |
| dc.date.issued (上傳時間) | 8-Dec-2010 15:46:52 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0097357034 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/49648 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 財務管理研究所 | zh_TW |
| dc.description (描述) | 97357034 | zh_TW |
| dc.description (描述) | 98 | zh_TW |
| dc.description.abstract (摘要) | 本研究蒐集經濟日報、聯合報、與聯合晚報的新聞文章，以中研院的中文斷詞性統進行結構性的處理，參考並延伸Tetlock、Saar-Tsechansky和Macskassy(2008)的研究方法，檢驗使用一個簡單的語言量化方式是否能夠用來解釋與預測個別公司的會計營收與股票報酬。有以下發現：1. 正面詞彙(褒義詞)在新聞報導中的比例能夠預測高的公司營收。2. 公司的股價對負面詞彙(貶義詞)有過度反應的現象，對正面詞彙(褒義詞)則有效率地充分反應。綜合以上發現，本論文得到，新聞媒體的文字內容能夠捕捉到一些關於公司基本面難以量化的部份，而投資者迅速地將這些資訊併入股價。 | zh_TW |
| dc.description.abstract (摘要) | This research collects all of the news stories about China Steel Corporation fromEconomic Daily News, United Daily News, and United Evening News. These articles I collectare segmented by a Chinese Word Segmentation System of Academia Sinica and used by themethodology of Tetlock, Saar-Tsechansky, and Macskassy(2008). I examine whether a simplequantitative measure fo language can be used to predict individual firms’ accounting sales andstock returns. My two main findings are:1. the fraction of positive words (commendatory term) in firm-specific news stories forecastshigh firm sales;2. firm’s stock prices briefly overreaction to the information embedded in negative words(Derogatory term); on the other hand, firm’s stock prices efficiently incorporate theinformation embedded in positive words (commendatory term).All of the above, we conclude this linguistic media content captures otherwise hard-toquantifyaspects of firms’ fundamentals, which investors quickly incorporate into stock prices. | en_US |
| dc.description.tableofcontents | 第壹章 緒論 1第一節 研究動機與目的 1第二節 研究範圍與限制 3第三節 研究架構與流程 4第貳章 文獻探討 6第一節 國外相關文獻探討 6第二節 國內相關文獻探討 7第參章 研究方法 9第一節 研究假說 9第二節 詞彙與變數定義 11（一）詞彙定義 11（二）解釋變數(自變數)定義 11（三）被解釋變數(應變數)定義 12（四）控制變數定義 13第三節 資料處理 15（一）資料取樣期間 15（二）新聞資料取樣原則 16（三）新聞資料(解釋變數、自變數)的處理 16（四）Fama-French(1993)三因子模型的處理 18第肆章 實證分析與結果 19第一節 敘述統計 19第二節 營收分析 21第三節 公司未來股價報酬分析 24第四節 交易策略 29第伍章 結論與建議 32參考文獻 33中研院平衡語料庫詞類標記集 34 | zh_TW |
| dc.format.extent | 2691159 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0097357034 | en_US |
| dc.subject (關鍵詞) | 內容分析法 | zh_TW |
| dc.subject (關鍵詞) | 文字資訊 | zh_TW |
| dc.subject (關鍵詞) | 資訊內涵 | zh_TW |
| dc.subject (關鍵詞) | 文件資料探勘 | zh_TW |
| dc.subject (關鍵詞) | 關鍵資訊擷取 | zh_TW |
| dc.subject (關鍵詞) | 資訊效果 | zh_TW |
| dc.subject (關鍵詞) | 褒義詞 | zh_TW |
| dc.subject (關鍵詞) | 貶義詞 | zh_TW |
| dc.subject (關鍵詞) | 正面詞彙 | zh_TW |
| dc.subject (關鍵詞) | 負面詞彙 | zh_TW |
| dc.subject (關鍵詞) | 基本面分析 | zh_TW |
| dc.subject (關鍵詞) | 股票報酬分析 | zh_TW |
| dc.subject (關鍵詞) | Content Analysis | en_US |
| dc.subject (關鍵詞) | Textual Information | en_US |
| dc.subject (關鍵詞) | Informative Content | en_US |
| dc.subject (關鍵詞) | Text Mining | en_US |
| dc.subject (關鍵詞) | Information Effect | en_US |
| dc.subject (關鍵詞) | Critical Information Extraction | en_US |
| dc.subject (關鍵詞) | Commendatory Term | en_US |
| dc.subject (關鍵詞) | Derogatory Term | en_US |
| dc.subject (關鍵詞) | Positive words | en_US |
| dc.subject (關鍵詞) | Negative words | en_US |
| dc.subject (關鍵詞) | Fundamental Analysis | en_US |
| dc.subject (關鍵詞) | Stock Return Analysis | en_US |
| dc.title (題名) | 文字背後的意含-資訊的量化測量公司基本面與股價（以中鋼為例） | zh_TW |
| dc.title (題名) | Behind the words - quantifying information to measure firms` fundamentals and stock return (taking the China steel corporation as example) | en_US |
| dc.type (資料類型) | thesis | en |
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