台灣為淺碟型市場，許多文獻證實機構投資人有影響市場的行為，為了解決一般投資人資訊缺乏，本研究以台灣股價指數為主，透過向量自我迴歸模型(VAR)、Granger因果關係檢定、衝擊反應函數及變異數分解，來探討基差、期貨大額交易人未平倉部位與選擇權大額交易人未平倉部位與台股報酬率的領先落後關係，由於期貨與選擇權的大額交易人未平倉部位的統計量有八種不同方法，本研究透過定義與模型配適度來選取最適當之代理變數，研究期間自2007年1月至2012年12月，共1366筆資料，其研究結果如下：
一、 基差對台股報酬率有領先關係，基差領先兩期，t-2期基差對台股當期報酬率有正向影響。
二、 選擇權的賣權大額交易人未平倉部位對台股報酬率有領先關係，但買權的大額交易人未平倉部位對台股報酬率則無顯著領先關係，選擇權的賣權大額交易人未平倉部位領先兩期，t-2期選擇權的賣權大額交易人未平倉部位對台股當期報酬率有負向影響。
三、 期貨大額交易人未平倉部位對台股報酬率有互相領先關係，期貨大額交易人未平倉部位在VAR模型下落後兩期的係數為負且顯著，t-2期期貨大額交易人未平倉部位對台股當期報酬率有負向影響。
根據以上結論，本研究嘗試建立交易策略模型來進行跟隨交易，當檢定機構投資人的變數出現買進訊號時，跟隨進場做多和做空，可以得到顯著大於50%的勝率，證明跟隨策略是能有效觀察出機構投資人的買賣時點。但在是否可以獲得超額報酬部分則無法顯著拒絕等於0之假設，可能推測為變數判斷僅用簡單的二分法判斷會產生誤差，即使將交易條件改以中位數做判斷，也無法顯著拒絕虛無假設。

Due to the small size of market in Taiwan, literature confirmed that institutional investments affect the market. In this study, a VAR model and granger causality tests, impulse response function and variance decomposition are used to solve the problems that general investors are lack of information. The variables used are stock index return, spread, and open interest of futures and options. Eight different definitions are used to calculate the open interest. This study will find out which definition method is the best to fit the model. The data period covers from January 2007 to December 2012 with 1366 data in total. Results are listed below:
1. Spread has two periods earlier than index Return, and it has positive correlation with return.
2. Open interest of put options has two periods earlier than index return, but that of call options does not. Open interest of put options has negative correlation with index return.
3. Open interest of futures and index return has bilateral Granger causality. The coefficient of open interest of futures in the VAR model is negative. Open interest of futures has negative correlation with index return.
Based on the above findings, this study attempts to establish a trading strategy to follow the smart money from institutional investment. When the buying signal is shown, stock index is bought. The winning ratio of the strategy is found to be significantly greater than 50%. But the null hypothesis that there is excess return can't be rejected, even if many different trading strategies are used.

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