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研究生:李泰逸
研究生(外文):Tai-Yi Lee
論文名稱:基因科技產業之產業風險評估與衡量
論文名稱(外文):Industrial Risk Assessment: Genetic Technology Industry
指導教授:黃金發黃金發引用關係
指導教授(外文):Jin-Fa Hwang
學位類別:碩士
校院名稱:中國文化大學
系所名稱:會計研究所
學門:商業及管理學門
學類:會計學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:71
中文關鍵詞:基因科技產業風險會計貝他
外文關鍵詞:genetic technologyindustrial riskaccounting beta
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本研究主要之目的在定義基因科技產業之產業風險,由於產業風險所涵蓋範圍太廣,故本研究嘗試以三個風險內涵:系統風險、信用風險及成長風險來嘗試解釋產業風險,並測試其對產業風險是否具顯著之解釋能力;而本研究另一個重點則在於探討會計BETA是否可用以替代傳統之系統風險代理變數-即CAPM下之BETA,希望能以會計基本面之變數來建構一評估產業風險的模式。
實證結果顯示,系統風險、信用風險及成長風險確對產業風險有顯著的解釋能力;而以個別會計BETA替代CAPM下之BETA時,模式仍具顯著的解釋能力,然或許因自變數均為會計資訊之本質,雖無複共線性的影響卻仍對迴歸之結果造成干擾,故本研究在最後考慮以線性組合的方式,將所有會計BETA組成變量以代表系統風險,放入模式中測試其對產業風險的解釋能力。結果發現以此會計BETA變量在解釋產業風險的能力上,似乎還更優於CAPM下之BETA,且變數間之干擾不復存在,而能得出一較佳之會計基礎產業風險評量模式。
The main idea of this research is to define the industrial risk of the genetic tech-nology industry. Because the component of the industrial risk is too complicated, this research would like to use three risk profiles: the systematic risk, the credit risk and the growth risk to capture the industrial risk, that isn’t only to realize whether the relation-ship between the industrial risk and its three risk profiles is significant but also to see how the industrial risk can be explained by the three risk profiles. Another issue this re-search would like to know is, if using accounting beta substitutes CAPM’s beta, which is used to be thought a traditional proxy for the systematic risk. This research hope there could be using the accounting–based variables to construct a model to access the indus-trial risk.
The findings indicate that the systematic risk, the credit risk and the growth risk would be significant to the industrial risk, and also have strong ability to explain it. While CAPM’s beta is replaced by individual accounting beta, the regression model is still significant. However, the regression coefficients are changed; there could be a simi-lar nature of our independent variables. So this research makes all accounting beta com-pose a linear function, and puts this new variate into the model and retest. Finally, this research finds that this variate, or can be called”quasi-accounting beta ”, is still signifi-cant to the industrial risk, and the regression coefficients become normal and stable. Furthermore, the ability to explain is much stronger than CAPM’s beta.
中文摘要 ...................... iii
英文摘要 ...................... iv
誌謝辭  ...................... v
內容目錄 ...................... vi
表目錄  ...................... viii
圖目錄  ...................... ix
公式目錄 ...................... x
第一章  緒論.................... 1
  第一節  研究背景................ 1
  第二節  研究動機與目的............. 3
  第三節  論文架構與研究流程........... 4
第二章  文獻探討.................. 6
  第一節  生物技術................ 6
  第二節  基因科技................ 16
  第三節  產業風險................ 19
第三章  研究設計.................. 29
  第一節  研究方法................ 29
  第二節  研究樣本與研究期間........... 29
第三節  相關變數之衡量............. 30
  第四節  實證模型與統計方法........... 39
第四章  實證結果.................. 45
  第一節  敘述統計................ 45
  第二節  Pearson相關分析............. 49
  第三節  實證結果分析.............. 51
第五章  結論與建議................. 60
  第一節  研究結論................ 60
  第二節  研究限制................ 63
  第三節  研究建議................ 64
參考文獻   .................... 65
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