由於近年來的金融動盪，風險控管成了重要課題，投資人期待在金融危機發生前就已做好萬全準備。本研究主要以Fama and French三因子，加入美匯指數(USDX)做為匯率變動指標來捕捉國際關係，構成了四因子模型以分析美國S&P100成分股之股價報酬變化，探討股票報酬受市場、公司特徵、匯率風險各因子之影響程度，且引進Skewed-t分配以模擬股價報酬之分配，以捕捉其偏態及峰態係數之特性。利用集群分析將樣本公司依據其風險特性分群，將各公司依其相似程度聚集，再觀察各風險因子對集群之解釋力。研究結果發現S&P100成份股之樣本公司皆會受到市場風險溢酬之影響，且受規模效應的影響較其他風險因子的影響小。
　　再依照GARCH-Skewed-t架構模擬出各集群分配之平均值、變異數、偏態係數及峰態係數四項參數估計值，並追蹤各參數長期之表現，用以觀察金融事件前之不尋常變動，並判斷極端事件發生與否之預警機制。本文實證結果顯示，偏態參數用以衡量金融動盪，具有極佳的警示作用。且受到淨值市價比效應及匯率變動率因子影響之集群，皆具有預警效果，其中以受匯率變動指標影響之集群具有較佳的預警效果。顯示用以評估美國股票報酬之多因子模型，若加入了匯率變動風險指標，將會得到更優良的分群結果，且受匯率變動風險指標影響的集群具有較佳的警示作用。亦即受匯率變動風險指標影響較劇之集群，其偏態參數可用以觀察金融動盪，可做為判斷極端事件發生之預警系統。

Due to the financial turmoil in recent years, risk management has become an important issue, investors would like to be fully-prepared to cope with financial crisis before it happen. This research uses the Fama and French three-factor and the U.S. Dollar Index (USDX) as an exchange rate variations indicator to capture the international relations. It constitutes a four-factor model to analyze the S&P100 stock returns changes, and we introduce the skewed-t distribution to simulate the distribution of stock returns and capture the characteristics of skewness and kurtosis. We use cluster analysis to cluster the sample companies by their risk characteristics. And then we observe the explanatory power of each risk factor. The study shows that the S&P100 stocks are subjected to the market premium, and the scale effect is smaller than others.
　　 At last, in accordance with the GARCH-Skewed-t model to simulate the average, variance, skewness and kurtosis of each cluster. We track the long-term performance of each parameter which are used to observe the unusual changes before financial crisis. The empirical results show that the skewness parameter has perfect warning for financial turmoil. The cluster with warning ability is affected by B/M ratio effect and exchange rate changes. Among the case, the cluster has the best early warning effect when it's influenced by the exchange rate indicator. It displays that by adding an exchange rate risk indicator into the multi-factor model, we will have a better clustering result. It means that the skewness parameter of cluster with influence of exchange rate indicator can be used to observe financial turmoil, which can in turns, be used as an early warning system to determine the occurrence of extreme events.

目 錄
中文摘要 …………………………………………………………….…..………… I
英文摘要 ……………………………………………………….…..…………… II
圖目錄 …………………………………………………………………………… VI
表目錄 …………………………………………………………………………… VII
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 研究流程 4
第二章 文獻探討 5
第一節 影響股票報酬因子之文獻 5
第二節 匯率影響股價報酬之文獻 7
第三節 匯率影響股價報酬之文獻 8
第三章 模型與研究方法 10
第一節 多因子模型 10
第二節 集群分析 11
第三節 GARCH-Skewed-t模型架構 13
第四章 實證研究分析結果 14
第一節 資料處理與說明 14
第二節 基本資料分析 17
第三節 模型估計 19
第四節 集群分析 20
第五節 參數估計與分析 22
第五章 結論 27
參考文獻 29

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