研究使用2000~2016年台灣證券交易所1887家公司，包含所有上下市櫃分析師預測公司，分析師預測資料除研究常用之盈餘預測外，亦將營收、毛利與毛利率等預測項目納入研究，此外加入額外因子，如:規模因子、淨值市價比因子、系統性風險因子、非流動性因子等進行多因子研究，使用Fama and French(1992)之Fama Macbeth迴歸模型，進行時間序列與橫斷面迴歸測驗，檢驗各因子之有效性，最終依據各績效評估因子決定出最適之投資組合，並附上各因子組合之權益曲線與績效。 實證結果發現，在台灣分析師樣本公司中，分析師歧異度、短期動能與長期動能三因子的影響較為顯著，分析師預期歧異度較高的公司未來預期報酬相對低於分析師預期歧異度較低的公司，而短期動能與長期動能較強的公司相較於短期動能與長期動能較弱的公司，擁有較高之未來預期報酬，以此三因子構建之投資組合，在2000~2016年間夏普值達0.78；而Fama and French使用的三因子在此樣本空間解釋力並不顯著，非流動性因子亦不顯著。 / This paper used the 1887 companies in Taiwan from 2000 to 2016, including all the analysts forecasting listed and delisted companies in either exchange market or over-the-counter market. The data of analyst’s prediction not only used the earnings forecast, but also revenue, gross profit and gross profit forecast in this research. In addition, other factors such as size factor, B/M factor, systemic risk factor, non-liquidity factor were used in this study. This paper used the Fama Macbeth regression model, which contains both time series and cross section Regression test, test the effectiveness of each factor, and ultimately based on the performance factor to determine the optimal portfolio, and finally obtain the equity curve and performance of the combination with various factors. The empirical results show that the analyst's earning dispersion, short-term momentum and long-term momentum three factors are more significant in the analyst forecasting companies in Taiwan. Companies with higher degree of earning prediction dispersion have relatively lower return in the future, and companies with higher short-term momentum and long-term momentum have a higher expected return. Build a portfolio with the three factor in 2000~2016 could obtain 0.88 Sharpe ratio! Neither Fama and French three factors nor non-liquidity factor in this sample space is significant.

本研究之宗旨在於探究中國大陸對亞洲區域內國家的金融市場影響程度之變化。由過去的各國股市日報酬率資料間相關程度與政策改變間的影響結果，來觀察是否未來在兩岸政策更開放下會使中國大陸對台灣的影響程度上升，進而使國際間投資組合的風險分散效果下降。本研究自DataStream選取台灣、香港、中國大陸、泰國、印尼、新加坡、馬來西亞、菲律賓、日本以及美國等十國的股價指數日資料，以對數轉換為日報酬率後年化加以分析。選取時間自1991年7月15日(中國大陸上海證券交易所股價指數公開後)至2008年12月31日。本研究選用的方法為使用風險值(VaR; Value at Risk)的概念來取代傳統的標準差，衡量以該十國所分別組成的各投資組合風險值變動情形；以及由風險值所衍生出的Diversification Benefit與Incremental VaR的結果。發現到僅由亞洲區域國家內組成的投資組合風險分散效果逐漸下降；且效果並不如有納入區域外國家(如美國)的投資組合。接著本研究將Gaussian Copula模型放入VaR中以增加對極端值的捕捉能力，結果發現本研究所選用的指數加權移動平均法所求得之相關係數已可有效反應出各國之間的相依程度，即加入Copula的效果有限。另外藉由Copula所求得之相關係數顯示，台灣、香港對中國大陸之間的相依程度已逐漸上升，並開始出現超越美國之現象，其中又以2005年為上升趨勢的起點。最後本研究以向量自我迴歸模型(VARs)來驗證2005年前後中國大陸股市對其他亞洲區域國家的影響力是否存在結構性的改變；並再佐以變異數拆解之方法來觀察2005年前後各國家之間自發性衝擊對彼此之間的影響程度變化。研究結果發現，透過VARs可證明中國大陸對亞洲區域各國的影響力在2005年後轉變為顯著；僅對美國不存在此一現象。另外變異數拆解的結果也顯示各國之間的相依程度在2005年後有明顯的上升，中國大陸對各國的影響程度亦然。透過本研究之結論，在未來兩岸將簽訂金融監理備忘錄使整合關係提升的環境下，需提醒投資人整合關係的上升將使得以之為標的之投資組合風險分散效果下降，需作為投資策略之考量。 / The object of this research is to find out the trend of dependence and correlation between China and other Asian countries. Based on past information about the relationship between equity markets’ correlation and changes in policies, this research can make suggestions to the foreseeable future of Taiwan and China whose relationship will be more solid due to new policy. The data of this research are gathered from DataStream, which includes Taiwan, Hong Kong, China, Thailand, Indonesia, Singapore, Malaysia, Philippines, Japan and United States. Selected from 1991/07/15 (when the Shanghai SE Composite went public) to 2008/12/31, this research calculates the annualized daily return using natural logarithms of two consecutive daily index prices. This research uses Value at Risk (VaR) to measure the risk exposure of portfolios formed by ten countries, and extends to the use of Diversification Benefit and Incremental VaR. The results found out that the diversification effects of portfolio which includes only Asian countries are decreasing and inferior to the effects when cross region countries are included. The second study of this research is to combine Gaussian Copula Model with VaR to capture the effects of extreme values. Empirical results found out that the VaR using Exponentially Weighted Moving Average method is good enough for analyzing Asian stock markets. The correlation in Copula model suggests that the dependence between Taiwan and China had increased since 2005 and has the increasing trend which might overwhelm the dependence between Taiwan and United States. Final research is about using Vector Autoregressions Model (VARs) to testify is there exist any structural change of dependence before and after 2005, and using Variance Decomposition to observe the relationships between these ten countries. The results found out that there exist structural change in 2005, the post-2005 periods shows that for Asian countries the effect from China are significant and greater than pre-2005 periods.