臺灣博碩士論文加值系統

在評估股票價格時，一般是使用公司的財務報表資訊來進行分析與判斷，而Ohlson(1995)股權評價模型則將公司財務報表中的會計數據與其他可能影響股價的重要非會計資訊，譬如分析師對盈餘的共識預測(consensus forecast)，整合在一起來評估股票價格。

然而在影響股價的非會計資訊中，除了分析師的共識預測之外，分析師在盈餘預測上的歧異程度與分析師對盈餘預測的修正幅度也隱含著許多重要的訊息，因此也有可能對股票價格產生影響。本文依循與延伸Ohlson(1995) 模型，研究分析師盈餘預測的歧異度與分析師盈餘預測的修正量在公司股權評價中的作用。依據財務理論，分析師在盈餘預測上的歧異程度對股價應呈負向影響，因為當分析師預測歧異度增加時，表示公司與分析師之間的資訊不對稱現象比較嚴重，不同分析師彼此間對公司未來盈餘的看法呈現比較大的分歧，代表這家公司營運上的風險增加，對股價應會產生負面的影響。此外，若分析師盈餘預測是向上修正，表示公司未來的盈餘會增加，所以股價應該上漲，但若分析師對盈餘預測是向下修正，則表示公司未來的盈餘不如原先的預期，所以公司股價應會下跌。因此分析師盈餘預測的修正量向上修正時，股價也會跟著向上修正，而分析師盈餘預測的修正量向下修正時，股價也會跟著向下修正，所以這之間的關係應為正向的，代表分析師預測修正量與股價之間為同方向變動。

本文依循Ohlson(1995)模型，從股利折現模型( discounted dividend model)出發，並假定乾淨盈餘會計關係(clean surplus relation)，而本文將Ohlson(1995)模型中的線性動態資訊系統(linear dynamic information system)擴展為包括了分析師預測歧異度、分析師預測修正量以及其他相關會計或非會計變數的一階向量自迴歸模型(VAR(1) model)，並由此推導出包括分析師預測歧異度與分析師預測修正量的股權評價模型。本文使用2000年至2011年間，台灣141家上市公司的時間序列與橫斷面資料來對本文的股權評價模型進行實證研究。實證結果發現分析師預測歧異度與分析師預測修正量的估計係數之正負符號與預期的一致，但估計係數並不顯著，而敏感度分析也顯示了實證結果的穩健性。此外包括了分析師預測歧異度、分析師預測修正量的股權評價模型也具有較佳的樣本外預測能力。

While we evaluate the stock prices of corporations, we often take the financial statements as a basis and engage in investigating the information contained in the financial statements in order to determine the proper stock price. However Ohlson(1995) equity valuation model combine accounting numbers in the financial statements and other important non-accounting information which may affect share price, like analysts’ consensus forecast, to jointly determine the stock price of corporations.

Among the non-accounting factors which may affect stock price, analysts’ consensus forecast is not an unique factor. Analysts’ forecast dispersions and revisions contain much significant information, so they are also other possible factors which may have impacts on the stock price. Hence we follow and extend Ohlson(1995) model to study the effects of analysts’ forecast dispersions and revisions on the equity price. According to the finance theory, analysts’ forecast dispersions represent asymmetric information between corporations and analysts. More serious analysts’ forecast dispersions are, more unstable the future performance of corporations is. When the analysts’ opinions about corporation diverse severely than before, then the risk of operation of corporations increase. Therefore analysts’ forecast dispersions have negative effect on the share price. Moreover analysts adjust his forecast upward, this means the future earnings of corporation will increase. So share price should rise. If Analysts adjust his forecast downward, then this means the future earnings of corporation will decrease. So share price should fall. Therefore analysts’ forecast revisions and share price will move in the same direction.

We follow Ohlson(1995) model to start with discounted dividend model and to postulate clean surplus accounting relation. Besides we also extend linear dynamic information system of Ohlson(1995) model to incorporate analysts’ forecast dispersions and revisions. Hence the linear dynamic information system in our model is designed as first-order vector autoregressive model (VAR(1) model) which include analysts’ forecast dispersions, analysts’ forecast revisions and other relevant accounting variables and non-accounting variable. Based on these setting, we can derive our equity valuation model with analysts’ forecast dispersion and revisions. We use time series and cross sectional data sampled from 2000 to 2011 and 141 listed corporations in Taiwan centralized market to conduct empirical studies. Empirical results reveal that the signs of estimated coefficients about analysts’ forecast dispersions and revisions coincide with the predictions, but the estimates are not significant. However sensitivity analysis also reveals that the empirical results are robust. Besides, our equity valuation model with analysts’ forecast dispersions and revisions also has better out-of sample forecast abilities.

摘要 I
Abstract II
謝辭 IV
目錄 V
第一章 緒論 1
第二章 文獻回顧 5
第三章 具有分析師預測歧異度與修正量的股權評價模型
第一節 剩餘所得股權評價模型 18
第二節 線性動態資訊系統 20
第三節 分析師對盈餘預測的歧異度與修正量 22
第四節 具有分析師盈餘預測歧異度與修正量的Ohlson股權評價模型 24
第四章 實證結果
第一節 資料來源與樣本敘述統計量 27
第二節 線性動態資訊系統VAR(1)模型的估計 29
第三節 股權評價模型的估計與檢定 31
第四節 模型的樣本外預測能力 33
第五節 敏感性分析 34
第五章 結論 36
參考文獻 37

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