| 研究生: |
賴威宇 Stanley Lai |
|---|---|
| 論文名稱: |
論基本面因子與評價乘數相互關係: 採用SARD篩選最適PB比較公司 Comparison sample of securities valuation: Comparison of fundamental factors and industry peers |
| 指導教授: |
葉錦徽
Jin‑Huei Yeh |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 財務金融學系 Department of Finance |
| 論文出版年: | 2018 |
| 畢業學年度: | 106 |
| 語文別: | 中文 |
| 論文頁數: | 49 |
| 中文關鍵詞: | 加總絕對排序差異 、本淨比 、基本面因子 、評價乘數 |
| 外文關鍵詞: | SARD, Price-Book Ratio, Fundamental factor, Valuation multiplier |
| 相關次數: | 點閱:22 下載:0 |
| 分享至: |
| 查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
許多文獻顯示,現在主流的證劵評價方式為未來預估的每股盈餘、每股淨值乘以評價乘數,如本益比(PE ratio)、本淨比(PB ratio)等。過往的文獻與研究皆採用同產業性質之公司作為比較基準,但是選擇同產業的公司作為比較公司的隱含假設為這些公司擁有相同的基本面,即便在相同產業中各公司表現也不盡相同,每家公司因各自的基本面表現的不同應該享有不同的評價乘數。本文欲研究基本面因子對於評價的重要性,相較於傳統產業平均比較,個別公司評價更受到基本面因子影響。
本文採用 Knudsen, Kold, Plenborg ( 2017)之研究方法SARD ( Sum of Absolute Rank Differences)針對2001~2016台灣上市上櫃股票選擇ROE、負債比率、每股盈餘成長率、市值、毛利率相似公司作為PB估計參考。實證發現原使用產業同業估計PB誤差平均數/中位數為0.592/0.401,使用SARD方式估計可以有效減少誤差至0.338/0.305,若先篩選產業別在使用SARD方式估計可以進一步減少誤差至0.267/0.234,證明選取基本面因子作為篩選標準,可以有效減少估計誤差。
At present, the mainstream evaluation method of securities is to use the estimated evaluation multiplier to evaluate ( EG PB ratio, PE ratio). Past studies using industry criterion averages as corporate assessment multiplier estimates. However, such companies may not have similar characteristics in terms of these drivers and thus should not be traded at the same multiple. This article wants to study the importance of fundamental factors for evaluation. Compared with the traditional industries criterion averages, individual company evaluations are more impacted by fundamental factors.
This article uses Knudsen, Kold, Plenborg (2017)'s research method SARD (Sum of Absolute Rank Differences) to select ROE, debt ratio, earnings per share growth rate, Capitalization, and gross profit margin for Taiwanese listed stock from 2001 to 2016. Benchmark multiplier using PB. The empirical results show that the original industry peers estimated the PB error mean/median of 0.592/0.401. Using the SARD estimation can effectively reduce the error to 0.338/0.305. If the industry is first selected, the SARD estimation can further reduce the error to 0.267/ 0.234, it is proved that selecting the fundamental factor as the screening criterion can effectively reduce the estimation error.
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