探討分析師推薦是否能區別高階經理人為過度自信之研究

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黃建銘(Chien-Ming Huang) 查詢紙本館藏

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企業管理學系

論文名稱

探討分析師推薦是否能區別高階經理人為過度自信之研究

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摘要(中)

本研究主要探討分析師的推薦對於過度自信CEO是否具有價值攸關，檢視Malmendier and Tate (2005) 區分CEO為過度自信與否的方法，是否能清楚地將CEO分類為是因為過度樂觀而表現出過度自信，又或是因為其持有一些非公開的資訊，以至於讓他表現出過度自信。故由先前研究中區分CEO的方法為出發點，檢視此方法是否能將CEO分類為過度自信與非過度自信，驗證此分類方法是否是正確的。接著探討分析師的推薦是否是可信的，先釐清分析師推薦以及各公司間累積異常報酬的關係，才能進一步地檢視分析師的推薦是否能成為分類過度自信CEO的指標。實證結果顯示，Malmendier and Tate (2005) 的CEO分類方法未能全然地將CEO分為過度自信與非過度自信，也就是說利用此方法而被歸類為過度自信的CEO中，可能存在著一定比例遭誤判的非過度自信CEO。而在檢視分析師的推薦下，結果顯示分析師的推薦對長窗期累積異常報酬具價值攸關，但分析師推薦對過度自信CEO的長窗期累積異常報酬，未具統計顯著性。

摘要(英)

The purpose of this research is to examine whether the recommendation of the analysts can classify that CEO showed overconfident because of their over-optimism or because they hold some non-public information and made them be overconfident. This research started from previous research which classified CEO as overconfident and non-overconfident. First, I examined this classification is correct or not. Second, I use the cumulated abnormal return of the companies to examine the recommendation of these analysts is credible or not. With the previous test, and I can prove whether the recommendation of the analysts can classify overconfident CEO or not. The results showed that the previous CEO classification couldn’t completely divide CEO into overconfidence and non-overconfidence. It meant that there would be a certain percentage of non-overconfident CEOs who were be classified as overconfident. And the results showed that recommendation of analysts is reliable, so I would want to use the analysts’ recommendation to examine they could be used to classify overconfident CEO or non-overconfident CEO.

關鍵字(中)

★ 分析師
★ 分析師推薦
★ 過度自信

關鍵字(英)

論文目次

摘要 i
Abstract ii
表目錄 vi
一、緒論 1
1-1研究動機與背景 1
二、文獻探討與研究假說 4
2-1 財務分析師的預測特徵與行為 4
2-2 財務分析師的推薦價值 5
2-3 過度自信 6
2-4 研究假說建立 8
三、研究方法與模型建立 13
3-1 樣本與資料來源 13
3-2 研究方法與模型建立 13
3-2-1 過度自信CEO以及非過度自信CEO之分類與累積異常報酬的關係 13
3-2-1-1 假說一之模型建立 14
3-2-2 分析師的推薦與累積異常報酬的關係 15
3-2-2-1 假說二之模型建立 15
3-2-3 分析師的推薦與累積異常報酬之間的關係 16
3-2-3-1 假說三之模型建立 17
3-2-4 預測準確度高的分析師推薦與累積異常報酬之間的關係 18
3-2-4-1 假說四之模型建立 18
3-3 變數的衡量與說明 20
3-3-1 長窗期累積異常報酬 (CAR_Long) 與短窗期累積異常報酬 (CAR_Short) 20
3-3-2 CEO虛擬變數 (Holder_67) 之建立與運用 22
3-3-3 分析師虛擬變數 (Dummy_Analyst) 的建立與運用 23
3-3-4 預測準確度高分析師虛擬變數 (Dummy_Analyst50) 的建立與運用 24
四、實證結果 27
4-1 假說一實證結果 27
4-1-1 敘述性統計量 27
4-1-2 迴歸結果 28
4-2 假說二實證結果 29
4-2-1 敘述性統計量 29
4-2-2 迴歸結果 31
4-3 假說三實證結果 32
4-3-1 敘述性統計量 32
4-3-2 迴歸結果 33
4-4 假說四實證結果 34
4-4-1 敘述性統計量 34
4-4-2 迴歸結果 35
五、研究結論 37
參考文獻 39

參考文獻

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指導教授

黃承祖

審核日期

2020-7-28

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