本文利用平滑轉換向量差修正模型(Smooth transition vector error-correction model, STVECM)與一般化自我迴歸異質條件變異數模型(Generalized Autoregressive Conditional Heteroskedastic model, GARCH），探討滬深300股價指數與滬深300股價指數期貨價格發現功能及二者間偏離共移均衡時非線性動態調整之交易行為。研究結果概述如下：首先，在滬深300指數現貨和期貨市場間具有價格發現功能。其次，在滬深300指數現貨和期貨存在正反饋效應。最後，滬深300指數現貨和期貨價格的變化係私人信息產生的交易動機所致。本文實證研究凸顯出投資者行為不能僅由單一特定的的交易動機分析。

This study utilizes non-linear smooth transition vector error correction model (STVECM) together with generalized autoregressive conditional heteroskedasticity model (GARCH) and combine investigation of feedback trading with motives of liquidity and private information-driven trading in the same one empirical. The findings are outlined below. First, the price discovery process to take place in both CSI 300 spot and futures markets. Second, we find evidence of positive feedback effects emerge in CSI 300 spot and futures. Finally, we find evidence of the price changes are driven by private information. The empirical evidence reported in this thesis highlights the investors’ motives cannot be identified a single for predominance of a particular motive.

CONTENTS
ACKNOWLEDGEMENT	I
ABSTRACT IN CHINESE	II
ABSTRACT IN ENGLISH	III
CONTENTS		IV
LIST OF TABLES	VI
LIST OF FIGURES	VII
CHAPTER 1  INTRODUCTION	1
CHAPTER 2  LITERATURE REVIEW	7
2.1 Literature Review on CSI 300	7	
2.2 Literature Review on Price discovery	10
2.3 Literature Review on motives of investment behavior	13
2.4 Literature Review on motives on Econometric Model	16
CHAPTER 3  METHODOLOGY	19
3.1 Variables Definitions	19
3.2 Theoretical Model of Different motives to trade	19
3.2.1 The models of Feedback trading	19
3.2.2 The models of Feedback trading	20
3.2.3 STVECM-GARCH models	21
3.3 Empirical Model	24
  3.3.1 The LSTVECM-GARCH model of price discovery process	26
  3.3.2 The LSTVECM-GARCH model of feedback trading	28
  3.3.3 Introducing liquidity- and private information-motivated trades into the LSTVECM-GARCH model	29
CHAPTER 4  DATA SOURCE 	31
4.1 The CSI 300 spot and futures	31
4.2 Data Collection	33
4.3 Summary Statistics	34
CHAPTER 5  EMPIRICAL RESULTS	39
5.1 Co-integration test, linearity and non-linearity test	39
5.2 Empirical evidence on investors’ trading behaviors	40
  5.2.1 Price discovery process on CSI 300 spot and futures	45
  5.2.2 Empirical evidence on feedback trading	46
  5.2.3 Empirical evidence on liquidity or private information	47
CHAPTER 6  CONCLUSIONS	50
REFERENCES	52	

LIST OF TABLES
Table 1 China Securities Index 300 (CSI 300) Futures	32
Table 2 Descriptive statistics for Daily return on CSI 300 spot and futures and volume           detail	35	
Table 3 The Johansen Test	39	
Table 4 Non-linear and STVEM Test	40	
Table 5 Estimation Results for CSI 300spot and futures	43

LIST OF FIGURES
Figure 1  Flowchart research framework	6
Figure 2  plot of the CSI 300 spot and futures price movements	36
Figure 3  plot of the CSI 300 spot and futures return movements	37
Figure 4  plot of the CSI 300 spot and futures log trade volumes movements	38
Figure 5  Smooth Transition Functions for the CSI 300 spot and futures	44

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