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研究生:劉和松
研究生(外文):Ho-Sung Liu
論文名稱:IPO異常現象與分析師自我預測之研究
論文名稱(外文):IPO Anomalies and Analyst’s Selective Forecast
指導教授:張永和張永和引用關係
指導教授(外文):Yung-Ho Chang
學位類別:碩士
校院名稱:東海大學
系所名稱:財務金融學系
學門:商業及管理學門
學類:財務金融學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:70
中文關鍵詞:首次公開上市自我預測個數自我預測誤差
外文關鍵詞:selective coverageearnings forecast bias
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本文採用1990至2004年美國證券市場數據,探討證券分析師對Initial Public Offerings (IPO) 股票未來報酬的預測能力。根據Lim (2001)的研究顯示,在最適的盈餘預測情況下,正預測誤差之存在是分析師的理性行為。本研究因此假設,在評量分析師之真實預測時,使用盈餘預測誤差(earnings forecast bias)比分析師個數(the number of analysts)更能反應分析師的預期心理。本文採用Somnath et al.(2006)所提出的殘餘分析師個數(Residual Analyst Coverage)模型,衡量分析師自我選擇之預測值,不同的是本研究採用預測誤差做為替代變數。在實證的部分,我們分別探討在公司特徵變數及承銷關係利益衝突變數的影響下,分析師預測行為對市場造成的衝擊與分析師的長期預測能力。實證結果指出分析師預測行為在短期下對股價市場有正向影響力,長期的模型中則呈現顯著負相關,此結果隱含分析師並無優異的預測能力,與Somnath et al.(2006)得到的實證結果相反,因此在本研究使用盈餘預測誤差進行分析所得到的結論為: 財務分析師並無較優越的預測能力。
This paper investigates security analysts' prediction ability on the IPO stocks’ future performance by using the US data sets from 1990 to 2004. According to Lim (2001), positive forecast bias exists in an analyst's rational behavior, given the condition of forecast error minimization. We thus assume that earnings forecast bias provides better assessment on analysts’ true forecast volition than do analysts’ forecast coverage. We adopted “Residual Analyst Coverage” model by Somnath et al.(2006) to measure the selective bias. Controlling for firm characteristics and the conflict of interests, we also examine analysts’ ability in forecasting firm performance and the impacts of their opinions on the market.
第1章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 觀念架構 4
1.4 研究目的 5
1.5 研究流程 5
第2章 文獻探討 6
2.1 財務分析師對IPO股票後市預測準確度的相關研究 6
2.1.1 分析師的預測準確之相關研究 6
2.1.2 分析師的預測不準確之相關研究 8
2.2 影響財務分析師預測行為的因素之相關研究 15
2.2.1 公開上市公司特徵影響分析師的預測之相關研究 15
2.2.2 發行公司與投資銀行之間的利益衝突關係影響分析師的預測 18
第3章 研究資料與研究方法 25
3.1 研究樣本 25
3.2 研究設計 25
3.2.1 市場對分析師預測的反應程度 26
3.2.2 分析師的自我真實預測與準確度 28
3.3 變數的選取和定義 35
3.3.1 預測誤差 35
3.3.2 公司特性變數衡量方式 35
3.3.3 利益衝突相關變數衡量方式 36
3.3.4 股票報酬變數衡量方式 37
第4章 實證結果與分析 39
4.1 預測誤差與公司特性變數之基本統計量 39
4.2 影響分析師預測誤差之因素的單變數分析 41
4.3 短期市場的反應分析 44
4.4 分析師預測能力之迴歸分析 45
4.4.1 殘餘自我預測迴歸模型分析 45
4.4.2 Fama & French的因子迴歸模型分析 48
4.4.3 Fama & MacBeth的橫剖面迴歸模型分析 49
第5章 結論 51
5.1 結論 51
5.2 研究建議 52
參考文獻 54
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