本研究主要是分析投資人情緒對於指數股票型基金（ETFs）流動性的影響，並捕捉投資人情緒的改變對於ETF流動性影響的效果，本研究使用美國恐慌指數（VIX）作為投資人情緒的代理變數。我們的樣本數據主要集中在亞洲市場的ETF，實證結果顯示，投資人情緒對於這些亞洲國家ETF的流動性有顯著的影響。
為了準確地捕捉到流動性的特點，本研究採用GARCH模型來檢測ETF的流動性是否具有波動叢聚效應的現象，並且採用Polite(2008) 之GARCH厚尾修正模型，它是修正GARCH模型在資料分配型態補捉的缺失，厚尾係數表示厚尾承受風險承度，此部份亦為本論文創新之處。實證結果顯示亞洲市場ETF具有流動性波動叢聚的效應。此外，我們的研究還發現投資人情緒和不同國家的ETF流動性會有顯著不同程度的影響關係。從風險管理和證券投資的觀點，本文建議考慮採用投資人情緒這個因子來納入其投資的決策。

This study aims to analyze the effect of investor’s sentiment on the Exchange Traded Funds (ETFs) liquidity to capture the various investment sentiment for the ETFs liquidity changes, using the Volatility Index (VIX) as a proxy variable to observe the market characteristics. Our sample data mainly focus on the Asia ETF market, and the empirical results show that the degree of market investor sentiment plays an important role in the ETF liquidity within these Asia countries. In order to accurately capture the liquidity characteristics, this study adopt the GARCH model to check whether ETF liquidity has a volatility-clustering effect or not, by adding Polite (2008) financial data with heavy tail characteristic, to correct the distribution pattern of missing data on GARCH model, which is an new idea in this paper. The empirical result shows that ETF has liquidity and volatility-clustering effect, which means there is a better or poor liquidity phenomenon in a specific period, which depends on monetary environment conditions and market investors’ expectation. In addition, our research also found that VIX and ETF liquidity would have a significantly different relationship with the development of different countries. From the viewpoints of hedging market risk and portfolio investment, this paper suggests investor to take consideration of the sentiment factors into their investment decision, and timely readjust the investment weight of ETF product.

CONTENTS
ACKNOWLEDGEMENT	I
ABSTRACT IN CHINESE	II
ABSTRACT IN ENGLISH	III
CONTENTS 	IV
LIST OF TABLES	VI
LIST OF FIGURES	VII

CONTENTS
CHAPTER 1 INTRODUCTION	1
1.1 Background	1
1.2 Research Objectives	7
1.3 Description of the Chapters and Research Papers Flowchart	9
CHAPTER 2 LITERATURE REVIEW	11
2.1 Relationship between Investor Sentiment and Trading Behavior	11
2.2 Relationship between Trading Behavior and Volatility	15
2.3 Discussion on Relationship between Liquidity and Trading Behavior,
Quantitative Easing	16
CHAPTER 3 METHODOLOGY	19
3.1 Variables	19
3.2 Model Specification	25
CHAPTER 4 EMPIRICAL RESULTS AND ANALYSIS	35
4.1 Basic Statistics	37
4.2 Empirical Results Analysis	54
CHAPTER 5 CONCLUSIONS	59
REFERENCES	61

LIST OF TABLES
Table 1 Data source and description	35
Table 2 Contractionary and expansionary monetary periods	37
Table 3 Descriptive statistics from	42
Table 4 Unit root test	43
Table 5 KLV Liquidity indicator – Japan	44
Table 6 KLV Liquidity indicator – Malaysia	45
Table 7 KLV Liquidity indicator – Singapore	46
Table 8 KLV Liquidity indicator – Korea	47
Table 9 KLV Liquidity indicator – Taiwan	48
Table 10 ETF Turnover rate – Japan	49
Table 11 ETF Turnover rate – Malaysia	50
Table 12 ETF Turnover rate – Singapore	51
Table 13 ETF Turnover rate – Korea	52
Table 14 ETF Turnover rate – Taiwan	53

LIST OF FIGURES
Figure 1 The research flow chart in this dissertation	10

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