臺灣博碩士論文加值系統

本文研究台灣市場中季盈餘宣告前後期間是否存在媒體管理的現象。本研究使用支援向量機(SVM)作為訓練新聞詞彙之辦法，建立模型將新聞分類為正面與負面新聞，進而捕捉公司發布季盈餘時間前後一個月未預期新聞變化情形。本研究使用台灣TEJ資料庫進行資料蒐集，期間為2002年1月至2022年12月。其中盈餘宣告的獲利能力指標，以季營收變動為越好、SUE越好、ROE季變動越高會在盈餘宣告前後不同時間點，分別對於正負面新聞有顯著的正面影響能力，即正面新聞增加、負面新聞減少，符合市場預期與忠實表達財報的內容。償債能力指標亦顯示同樣的結果。解讀成與市場的方向是一致性的，實證結果無論是否有盈餘宣告消息提前洩漏的現象，沒有明顯發現媒體管理的現象。

This study investigates the phenomenon of media management around the quarterly earnings announcements in the Taiwanese market. To precisely analyze whether media management occurs, this research employs Support Vector Machines (SVM) to train on news vocabulary and subsequently develops a model to classify news as positive or negative, capturing the trend of news one month before and after the corporate earnings releases. The data was collected from the Taiwan Economic Journal (TEJ) database, spanning from January 2002 to December 2022. The study indicates that at various points around earnings announcements, improvements in quarterly revenue changes, better Standardized Unexpected Earnings (SUE), and an increase in quarterly Return on Equity (ROE) significantly enhance the likelihood of positive news and reduce negative news coverage. The solvency indicators also demonstrate similar outcomes. The regression results examining the data one month before and after the earnings announcements suggest that the findings align with market expectations and faithfully reflect the content of financial reports, with no apparent evidence of media management, regardless of potential premature leakage of earnings announcements.

摘要 ii
Abstract iii
目錄 iv
表目錄 v
壹、前言 1
貳、文獻探討 3
一、媒體管理 3
二、盈餘宣告 4
參、假說 6
肆、研究方法設計 7
一、研究方法 7
二、新聞報導的迴歸模型 9
三、訓練樣本分類 11
四、變數 11
伍、實證結果 15
陸、結論 17

中文部分
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4.陳和良（2008）。盈餘宣告事件下的動能交易策略。﹝碩士論文。銘傳大學﹞臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/39au75。
5.張岳和（2009）。台灣地區產業間盈餘宣告的異常報酬跟交易量效果。﹝碩士論文。國立東華大學﹞臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/5u8y9b。
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英文部分:
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