吉尼係數（Gini Coefficient）是一種用來衡量集中度的方法，在經濟學裏通常用來專指「所得分配的集中度」，本論文利用計算吉尼係數方法來統計台灣所有證券商的分點進出明細，得出樣本個股每日的吉尼係數差值，再與樣本個股的價格與股價報酬率進行基本迴歸模型分析與進階向量自我迴歸（VAR）模型分析，另外將吉尼係數差值作累積得出吉尼係數線，與股價作共整合（co-integration）的檢定，研究探討個股吉尼係數的變化是否與個股的股價報酬率和與變異有明顯的連動關係。基於上述結果，進一步利用這些連動關係與特徵現象來設計個股的交易模型，實證結果證實在加入交易成本後，投資績效仍顯著優於大盤指數績效。

Gini coefficient is a way to measure the degree of stock concentration. In economics, it is usually used to measure the dispersion of income distribution. This thesis uses Gini coefficient to calculate stock concentration from all the transactions in Taiwan stock market. Analyses of basic regression model and more advanced vector auto-regression (VAR) model were carried out to capture the relation between stock concentration and stock price for the sample stocks. Through the co-integration analysis, we explore whether there is a connection between the stock price movement and its cumulative Gini coefficient. Based on the relations observed from preceding analysis, we develop our trading models for the individual constituent stocks from popular ETFs in Taiwan stock market. The back testing results show that the trading strategies based on our models perform better than the Taiwan stock market index as well as the related ETFs.

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