衍生性金融商品日益蓬勃發展，隨著法令的逐步開放以及國外避險基金的相關商品不斷引進國內金融市場，國內法人不僅運用期貨與選擇權進行避險操作，更期待透過現貨與期貨商品的組合，達到風險極小化獲利極大化的目標；另一方面，國內法人在不得放空的限制下，在股票市場盤整期間或是空頭市場期間便無法發揮所長，藉由股票的單一方向性交易賺取利潤，因此，如何透過現貨與期貨的組合以及期貨部位的動態調整解決上述問題進而開發新的金融商品便成為國內法人努力思考的方向。
　　為了提供一可用、穩定的模型，本研究應用馬可夫鏈進行台股現貨與期貨交易策略，在現貨組合的建構上採用Mean-Varian Theory，以Matlab程式建構放空限制下的最適投資組合，成分股的選取為台灣五十成份股權重前三十名之個股，期貨部位之決定則先以最小風險避險比例法（Minimum Variance Hedge Ratio）求得最適避險比例，再應用馬可夫鏈轉換矩陣達到動態調整期貨部位的目的，組成台股現貨與期貨間交易策略，其中馬可夫鏈轉換矩陣乃以現貨組合日漲跌幅與期貨指數日漲跌幅的差作為狀態變數。相關文獻以及研究方法詳見第二章及第三章，第四章以Matlab程式進行實證研究，第五章是結論與建議。

As the derivatives bloom in global financial market, the government gradually loosens regulations and relevant foreign hedge fund products are introduced to Taiwan financial market, domestic institutional investors not only use futures and options to hedge, but also minimize the risks and maximize the profits through the combination of stock trading and futures trading. On the other hand, domestic institutional investors are not allowed to do short trading so they are hard to make profits through stock trading in non-bull market. Thus, how to trade through combining stocks and futures, and dynamically adjusting hedge ratio, and then developing new financial products is the first topic for domestic institutional investors.
To provide an useful and stable model, this study applies Markov chain approach to develop a strategy of trading Taiwan stocks and futures. This strategy is to use Mean-Varian Theory in stock trading and to use Matlab program to find the optimal portfolio under the restriction of short trading. The stocks of this portfolio are from the most thirtieth weight components of Taiwan 50. The volume of futures of this portfolio is first decided by the Minimum Variance Hedge Ratio to find the optimal hedge ratio and then applies Markov chain transition matrix to adjust the future position dynamically. Markov chain transition matrix is the variables of the differences between the combined return of these stocks and the return of the future on the day that this portfolio is set up. Relevant studies and methodologies are referred to the second section and the third section; the fourth section is the test of using Matlab program; the fifth section is the conclusion and suggestion.

一、中文部分
1.張傳章，期貨與選擇權，台北：雙葉書廊，2005。
2.鍾惠民、吳壽山、周賓凰、范懷文，財金計量，台北：雙葉書廊，2004。
3.周賓凰，賣空限制下的最適投資組合建構，中央大學財金研究所研究方法論課程教材，　2004。
4.銘傳大學財務金融研究中心，投資分析＋Matlab應用，台北：全華科技，2003。
5.謝劍平，現代投資學－分析與管理，台北：智勝文化，2003。
6.陳信富，台北股市最適組合投資與避險操作有效性分析，銘傳大學經濟學研究所碩士論　文，2003。
7.楊士賢，應用馬可夫決策過程進行台股期貨日內交易策略之研究，東海大學工業工程與　經營資訊研究所碩士論文，2003。
8.江錦宗，應用馬可夫決策過程進行台灣股票投資分析之研究，東海大學工業工程與經營　資訊研究所碩士論文，2002。
9.楊靜榆，兩狀態下的國際資產配置－馬可夫轉換模型之應用，中央大學財務管理研究所　碩士論文，2001。
10.黎明淵，馬可夫轉換模型應用性與合用性探討，政治大學國際貿易研究所博士論文，　　2000。
11.張保隆，現代管理數學，台北：華泰文化，2000。
二、英文部分
1.Jin-Chuan Duan, Jean-Guy Simonato, “American option pricing under GARCH by a Markov chain approximation”, Journal of Economic Dynamics & Control, Vol. 25, 2001, pp. 1689~1718.
2.Craig Steven Edwards, Option Pricing With Continuous-time Markov Chain Regime Switching, A Dissertation presented to the Graduate Faculty of the University of Virginia in Candidacy for the Degree of Doctor of Philosophy, 2004.
3.Edwin J. Elton, Martin J. Gruber, Stephen J. Brown, and William N. Goetzmann, Modern Portfolio Theory and Investment Analysis, New York: John Wiley & Sons, 2003.
4.John C. Hull, Fundamentals of FUTURES AND OPTIONS MARKETS, London: Prentice-Hall, 2002.
5.Bodie Kane Marcus, INVESTMENTS, New York:McGraw-Hill/Irwin, 2002.