Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/22644
標題: 網路公司評價-應用資料包絡分析法之乘數評價方法
Valuing Internet Companies: A DEA-Based Multiple Valuation Approach
作者: 廖春貴
Liao, Chun-Kuei
關鍵字: DEA;資料包絡分析法;Multiple Valuation Approach;Internet Company;乘數評價方法;網路公司
出版社: 電子商務研究所
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摘要: 
過去十幾年來,許多學者紛紛投入網路公司評價的研究領域,希望能夠發展出一套強而有力的工具以幫助投資者估計網路公司的股價,在這之中,有些學者嘗試以傳統的評價方法來達成這個研究目的,有些則試圖去修正傳統評價方法來符合網路公司的特性,但大多數的研究都未得到令人滿意的結果。本研究之研究目的即在於發展一個為網路公司量身訂作的評價方法,進而幫助投資者制定正確的投資決策。
本研究主要是參考學者Anadol其碩士論文“Valuing private companies—A DEA approach” (2000)之研究概念,先以資料包絡分析法(Data Envelopment Analysis, DEA)進行比較公司(comparable firm)之篩選,再以股價毛利比率(Price-to-Gross Margin ratio)作為評價階段之乘數,估算目標公司之股價。
在比較公司篩選階段,本研究以四種不同的方法(Model 1~Model 4)進行測試,研究發現,在此四種方法中,綜合考量比較公司的篩選能力及股價的預測能力,Model 1為表現最佳的方法。若僅考量股價預測的方向(高估/低估)正確與否,本研究的預測準確率可達近百分之七十,此數據顯示,本研究成果對於提供相關資訊供投資者制定投資決策方面,確實具有相當程度的幫助。

During the last decade, many researchers have devoted themselves to developing such a tool that can help investors to estimate an Internet company's value. Some of them attempted to use those traditional valuation approaches to accomplish this mission; some tried to modify the traditional valuation approaches to fit Internet industry's unique characteristics, but most of them did not get satisfactory results. This research, hence, is designed to develop a tailored valuation method for Internet companies and then help the investors to make right investment decisions.
The whole research structure is inspired by Anadol's thesis “Valuing private companies—A DEA approach” (2000). This research extracts the idea of using DEA to find comparable firms for each target company, and then applies the Price-to-Gross Margin (P/GM) ratio (the multiple) in the second stage to estimate the price for it.
With different ways in forming comparable-firms-list, four models (Model 1~Model 4) are tested and an estimation based on the P/GM ratio is implemented under each model. Among these four models, Model 1 performs better than the other 3 models in terms of the ability of finding comparable firms for each sample company and the ability to get more accurate estimation of the subject company's current and future stock prices. And with the focus on the estimation direction (overvalued/undervalued), an accuracy rate of approaching 70% on average has been obtained from these four models. This implies that the research results are of some help for investors when they want to short or long an Internet stock.
URI: http://hdl.handle.net/11455/22644
其他識別: U0005-2506200721461300
Appears in Collections:科技管理研究所

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