分析師現金流量預測為企業過度投資之衡量指標

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姓名

程薇安(Wei-An Cheng) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

分析師現金流量預測為企業過度投資之衡量指標

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摘要(中)

本研究探討分析師現金流量預測次數與無形資產及研發支出之關係，並進一步以三天短窗期的累積異常報酬和以一年長窗期的累積異常報酬分析藉由分析師現金流量預測衡量企業的過度投資。McNichols & Stephen（2008）從企業財報資訊來判定該公司是否有過度投資之情形，會有其侷限性，一來歷史現金流量無法反應企業的未來，二來Tobin′s Q雖具未來性，但僅是市場一般投資人所形成的看法，因此，本研究由分析師的專業角度出發，試圖以其現金流量預測來建構過度投資之指標，並用盈餘預測準確度區分分析師能力高低，探討分析師能力對本研究之影響，同時與過去研究進行比較，並檢測模型所計算出最適投資差距是否能夠判斷企業為過度投資。研究期長為2010至2018年的美國企業資料，實證結果顯示能力較佳的分析師對無形資產較多的公司提供較佳長天期現金流量預測，另一方面分析師現金流量預測在長窗期時對公司之過度投資具有邊際解釋力。

摘要(英)

This study examines the relationship between analysts’ cash flow forecasts and intangible assets and R&D expenditures. Furthermore, we will measure companies’ overinvestment from the analyst’s perspective. McNichols, Maureen & Stephen (2008) determine whether the company has over-invested from financial or market information which has its limitations. For example, expenditure will be restricted by accounting rules and.it can’t truly reflect the value of the companies. On the other hand, if company as leader is measured by the average investment in the same industry, the results may be biased. Therefore, in this study, we will try to construct another indicators of overinvestment from the perspective of analysts’ cash flow and distinguish analysts’ ability from high to low by accuracy of earnings forecasts. The study period is from 2010 to 2018. The results provide better analysts with long-term cash flow forecasts for companies with more intangible assets. Another shows that analysts’ cash flow forecasts can find out overinvestment company during the long window period.

關鍵字(中)

★ 分析師
★ 現金流量預測
★ 過度投資

關鍵字(英)

論文目次

目錄
摘要 i
Abstract ii
目錄 iii
表目錄 v
一、緒論 1
1-1研究背景及動機 1
1-2研究目的 3
1-3論文架構 4
二、文獻回顧與假說發展 5
2-1分析師 5
2-1-1分析師角色 5
2-1-2 分析師報告資訊意涵 6
2-2長期資產 7
2-2-1無形資產與研發費用 7
2-2-2資本支出 8
2-3過度投資 8
2-4研究假說發展 9
三、研究方法 11
3-1資料來源 11
3-2實證模型與研究方法 11
3-2-1分析師現金流量預測與公司具未來性資產之關係 11
3-2-2分析師現金流量預測與過度投資之關係 13
四、實證結果 18
4-1探討假說一之實證結果 18
4-1-1敘述統計 18
4-1-2迴歸結果 19
4-2假說二之實證結果 21
4-2-1敘述統計 25
4-2-2迴歸結果 21
4-3假說三之實證結果 25
4-3-1迴歸結果 26
五、研究結論 28
參考文獻 30

表目錄
表 1假說一變數之敘述統計 30
表2 假說一PEARSON相關係數矩陣 34
表3 假說一PEARSON相關係數矩陣 34
表4 分析師各期預測數量與無形資產關係 35
表5分析師發佈各期報告比例與無形資產之關係 37
表6能力較佳分析師發佈報告數量與無形資產之關係 38
表7能力較佳分析師發佈各期報告比例與無形資產之關係 40
表8 分析師各期預測數量與研發支出關係 41
表9分析師發佈各期報告比例與研發支出之關係 43
表10能力較佳分析師發佈報告數量與研發支出之關係 44
表11能力較佳分析師發佈各期報告比例與研發支出之關係 46
表12 假說二變數之敘述統計 47
表13假說二 PEARSON相關係數矩陣 48
表14短窗期分析師角度投最適投資模型之結果 49
表15短窗期異常報酬迴歸結果 50
表16短窗期分析師角度投最適投資模型之結果 52
表17長窗期異常報酬迴歸結果 53
表18短窗期異常報酬迴歸結果 55
表19長窗期異常報酬迴歸結果 57

參考文獻

參考文獻
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指導教授

黃承祖

審核日期

2021-5-5

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