負面新聞事件在財務危機預測：以台灣上市上櫃公司為例

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研究生：	劉雅文 Ya-Wen Liu
論文名稱：	負面新聞事件在財務危機預測：以台灣上市上櫃公司為例 Negative News events in financial distress problem: Taiwan-listed company
指導教授：	梁德容
口試委員:
學位類別：	碩士 Master
系所名稱：	資訊電機學院 - 資訊工程學系 Department of Computer Science & Information Engineering
論文出版年：	2019
畢業學年度：	107
語文別：	中文
論文頁數：	62
中文關鍵詞：	負面財務新聞事件、財務危機預測
相關次數：	點閱：7 下載：0
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財務危機預測問題(Financial distressed prediction problem)一直以來是個重要且已被廣泛討論的問題，其中又以特徵挑選及學習演算法為兩大重心。本研究著重於找尋新的特徵以幫助預測，過往的研究大多使用財務比率(Financial Ratio)，部分使用公司治理指標(Corporate Government Indicator)進行財無危機預測，卻少有研究使用公司的負面新聞對台灣地區的公司進行未來的財務危機預測，在本研究中我使用TEJ的看門狗資料庫中所蒐集並定義的負面新聞事件分類，接著使用統計方法分析後挑選出了其中八個負面新聞事件，提取欲預測年份的前一年的發生次數作為特徵值去建模在透過DET Curve及cost ratios分析，並證實了在大部分的cost ratio 下使用ensemble Bagged Tree建模這些負面事件對預測表現是有幫助的。

The financial distressed prediction problem has always been an important and widely discussed issue, with feature selection and learning algorithms as the two main focuses. This study focuses on finding new features that can help improve the prediction. Most of the previous studies used the Financial Ratio, and some used the Corporate Government Indicator for financial crisis prediction. However, few studies used the company's negative news to predict the financial crisis. In this study, we proposed eight negative news events to build the prediction model. For each event, calculate the number of occurrences of the year before predict year as the event feature value. After we analysis the result by DET Curve and different cost ratio analysis , we learned that these negative events are helpful for predicting performance over most of the cost ratios.

中文摘要    i
Abstract    ii
誌謝    iii
目錄    iv
圖目錄    vii
表目錄    ix
一、    緒論    1
1-1 研究背景    1
1-2 研究動機    2
1-3 研究目的    2
1-4 論文架構    3
二、    文獻探討    4
2-1 FDP相關文獻    4
2-1-1 Altman Z-Score    4
2-2 探討新聞事件相關文獻    6
2-3 探討分類器    6
2-3-1 支持向量機(SVM)    6
2-3-2 判別分析(DA)    12
2-3-3 邏輯斯回歸Logistic Regression    13
2-3-4 最近鄰居分類 (KNN)    14
2-3-5 Ensemble Bagged Tree    16
三、資料集    18
3-1資料集來源及簡介    18
3-2 樣本配對演算法    20
3-3 負面新聞特徵的分析    23
四、實驗設計    25
4-1資料前處理    25
4-1-1 負面新聞特徵正規化    25
4-2 實驗評估方法    25
4-2-1 DET curve(Detection error tradeoff curve)    26
4-2-2 Cost Ratio analysis    27
4-3實驗流程    28
4-3-1 N fold cross validation model    28
4-3-2 Hypothesis 實驗流程    29
4-4實驗各項參數設定    30
五、實驗結果    31
5-1 Hypothesis 實驗結果分析    31
5-2 Variable Importance and Variable Interaction    38
六、結論及未來展望    41
6-1 結論    41
6-2 未來展望    41
參考文獻    42
附錄一    44
附錄二    47
附錄三    48


                                

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