本論文透過馬可夫轉換模型區分不同的財務市場景氣狀態，並將之作為解釋變數，同時加入其他外生解釋變數，以三大法人買賣超ETF股數作為被解釋變數並採用向量自我迴歸模型(VAR模型)，目的在於:(1)檢視三大法人於台灣ETF市場的投資行為，是否受到不同的財務市場景氣狀態及市場投資人情緒影響，而投資於不同類型的ETF?(2)三大法人是否有彼此影響之情況?
希望可以幫助投信公司了解三大法人於臺灣ETF市場的動向，並做出相對的措施因應。

The purpose of this study is to investigate the factors which drive institutional investors’ investment decisions in Taiwan ETFs market. The thesis first predicts phases of the financial cycle in a Markov switching framework. VIX index is used to identify the turning points for a transition to a volatile state. The state variable, other institutional investors’ investment behavior in ETFs, and investor's sentiment variables are then use to explain the behaviors of three major institutional investors’ ETF shares in a vector autoregressive (VAR) framework.
In particular, the study asks the following two research questions: (1) Whether institutional investors will invest in different types of ETFs in various financial market states, and (2) Whether there will be any interactions among the three types of major institutional investors in their ETF investment.
Understanding the institutional investor behavior can help investment trust companies to promote ETFs in various financial states.

一、中文文獻
李詩文(1996)。股市外資、自營商與基金之互動關係－狀態空間模型應用之實證研究。
翁英傑(1996)。自營商及外資之投資行為研究。
黃懷慶(2000)。台灣股市三大機構投資人(外資、投信與自營商)投資行為之實證研究。
許雅菁、陳光華及吳元功(2001)。投資者購買共同基金選擇因素之研究。
黎明淵(2002)。高、低股市波動狀態下之雙重貝它係數檢測-美國、日本與亞洲四小龍股市實證研究，台灣管理學刊，第2卷，第2期，頁99-118
鄭婉秀(2004)。股價報酬的可測性 : 三狀態馬可夫轉換模型應用。
張瑞真(2007)。歐肯法則與台灣之景氣循環-雙變量馬可夫轉換模型與 GibbsSampling 之應用。
陳盈君(2010)。台灣股市三大法人從眾行為。
薛羽玲(2012)。臺灣股市三大法人從眾行為之探究。
彭健豪(2012)。台灣股市從眾行為研究-三大法人與個人投資者的比較。

二、英文文獻
Clifford S. Asness, Jacques A. Friedman, Robert J. Krail, and John M. Liew (2000). Style timing: Value versus growth. The Journal of Portfolio Management, Vol. 26, No. 3, pp. 50-60.
Constantinos Antoniou, John A. Doukas, and Avanidhar Subrahmanyam (2016). Investor Sentiment, Beta, and the Cost of Equity Capital, Management Science Volume 62, Issue 2, February 2016, 347 - 367
Charles Engel and James D. Hamilton (1990). Long swings in the dollar: Are they in the data and do markets know it? American Economic Review 80, 689-713.
Yasushi Hamao and Jianping Mei (1995). Living With the “Enemy”: an Analysis of Foreign Investment in the Japanese Equity Market, Journal of International Money and Finance, 20, 715-735.
James D. Hamilton (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, Vol. 57, No. 2,357-2384.
Jonathan Lewellen (2002). Momentum and Autocorrelation in Stock Returns. The Review of Financial Studies, Vol. 15, No. 2. (2002), pp. 533-564.
J. Bollen, H. Mao, and X. Zeng, Twitter mood predicts the stock market, Journal of Computational Science 2(1) (2011) 1-8.
Josef Lakonishok, Andrei Shleifer, and Robert W. Vishny (1992). The impact of institutional trading on stock prices. Journal of Financial Economics, 32, 23-43.
M. Baker and J. Wurgler, Investor sentiment and the cross‐section of stock returns. The Journal of Finance 61(4) (2006) 1645-1680.M. Schmeling, Investor sentiment and stock returns: Some international evidence, Journal of empirical finance 16(3) (2009) 394-408.
Philip Hodges, Ked Hogan, Justin R. Peterson, and Andrew Ang (2017). Factor Timing with Cross-Sectional and Time-Series Predictors. The Journal of Portfolio Management Fall 2017, 44 (1) 30-43.
Richard W. Sias (2002). Institutional Herding. Review of Financial Studies, 165-206
Q. Zhang and S. Yang, Noise trading, investor sentiment volatility, and stock returns, Systems Engineering-Theory & Practice 29(3) (2009) 40-47.