配對交易—以台灣股票期貨之標的股為例

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Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/19943

Title:	配對交易—以台灣股票期貨之標的股為例
Authors:	林明猷
Contributors:	國際企業管理學系
Keywords:	配對交易統計套利避險基金
Date:	2010
Issue Date:	2011-10-27 13:36:47 (UTC+8)
Abstract:	配對交易為一種交易策略，將兩者標的依照一定原則，形成配對，待兩者價格發生偏離時，預期將會收斂，而買入相對價值低之標的及賣出相對價值高之標的，藉此規避掉系統風險，從中進行套利獲取報酬。而本研究是以股票期貨之標的股為研究對象，並且分成兩大類，分別為金融與非金融，在配對條件上，金融部分以產品性質60%以上、股權結構及相關係數大於0.6三步驟來建立配對；而非金融部分則是以同一產業及產品性質60%以上兩步驟來建立配對。而在進出場訊號方面，則是利用技術分析中之RSI指標，來建立起交易訊號，而本研究之目的為:一、運用配對交易方法，來探討是否配對交易能獲取超額報酬。二、以本研究之配對，探討是否具有共整合關係，且具有共整合關係之配對，可獲得較佳報酬。三、另一方面再以本研究之配對，來探討是否兩者股票具有較高程度相關係數，且具有較佳之報酬。最後結果發現，各檔年化報酬不一，最高可達5.71%，最低可達-0.79%，因此在某些配對上可優於市場指數年化報酬3.69%，再進一步來探討，具有共整合關係之配對則績效較優於無共整合關係之配對，而具有較高程度相關係數亦有顯著差異。 The issue of pairs trading is regarded as a sort of trading strategy, which groups two targets with certain limitations and compares these targets. When the prices of these two targets are deviate, they are anticipated to be convergent. Therefore, investors are able to buy targets with relatively low price and sell them with higher price in order to minimize system risks and get benefits from the arbitrage behavior. This paper chose the sample from Taiwan Futures Exchange on Jan. 25, 2010. The categories are financial group and non-financial group. The data of pairs trading divides financial group into three sub-groups by the conditions of the 60% similarity of products, ownership structure and correlation coefficients above 0.6. Alternatively, the non-financial group is divided by the conditions of the same industry and the 60% similarity of products. With the aspects of buy-and-sell signals, the RSI is employed for the technical analysis. Hence, the technique of pairs trading is used to examine if investors can have abnormal returns by using this method. Secondly, with pairs trading, the data can be investigated whether or not they have the relationship of cointergration. Therefore, the investors can have higher returns by using pairs trading. Finally, if there are higher correlation coefficients between any two target stocks and to see if target stocks with higher correlation coefficients contribute higher returns. It indicates that the ranges of annual returns are somewhere fluctuated, with the highest 5.71% and the lowest -0.79%. Comparing with the annual returns of benchmark, some pairs trading are actually resulted in higher returns. Regarding with the cointergration, those pairs with the relationship of cointergration have higher returns compared with others which are without the cointergration. Another finding concerning the correlation coefficients between any two target stocks is found that the returns with lower and higher correlation coefficients are significantly different.
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