The price of stocks, futures, commodities and currency are for ever changing. Anyone interested in financial prices soon discovers that changes in prices are frequently substantial and are always difficult to forecast. This paper describes the behavior of prices from a statistical perspective. Specifically, employ several technical trading rules to uncover the trend of futures price movement and attempt to make profit out of the trend. In this paper, trading of seven technical trading systems is simulated for three futures contracts from September 1998 to March 2005 to test for market disequilibrium. The results differ by trading systems. Four systems produced positive mean net returns and five systems produced positive gross return when optimal parameters were used. These results indicate that, there exist opportunities to design profitable trading systems for futures markets.

資料串流探勘是一個重要的研究領域，因為在現實中有許多重要的資料以串流的形式產生或被收集，金融市場的資料常常是一種資料串流，而通常這類型資料的本質是變動性大的。在這篇論文中我們運應了資料串流探勘的技術去預測台灣加權指數期貨的漲跌。對機器而言，預測期貨這種資料串流並不容易，而困難度跟概念飄移的種類與程度或頻率有關。概念飄移表示資料的潛在分布改變，這造成預測的準確率會急遽下降，因此我們專注在如何處理概念飄移。首先我們根據實驗的結果推測台灣加權指數期貨可能存在高頻率的概念飄移。另外實驗結果指出，使用偵測概念飄移的演算法可以大幅改善預測的準確率，甚至對於原本表現不好的演算法都能有顯著的改善。在這篇論文中我們亦整理出專門處理各類概念飄移的演算法。此外，我們提出了一個多分類器演算法，有助於偵測「重複發生」類別的概念飄移。該演算法相比改進之前，其最大的特色在於不需要使用者設定每個子分類器的樣本數，而該樣本數是影響演算法的關鍵之一。 / Data stream mining is an important research field, because data is usually generated and collected in a form of a stream in many cases in the real world. Financial market data is such an example. It is intrinsically dynamic and usually generated in a sequential manner. In this thesis, we apply data stream mining techniques to the prediction of Taiwan Stock Exchange Capitalization Weighted Stock Index Futures or TAIEX Futures. Our goal is to predict the rising or falling of the futures. The prediction is difficult and the difficulty is associated with concept drift, which indicates changes in the underlying data distribution. Therefore, we focus on concept drift handling. We first show that concept drift occurs frequently in the TAIEX Futures data by referring to the results from an empirical study. In addition, the results indicate that a concept drift detection method can improve the accuracy of the prediction even when it is used with a data stream mining algorithm that does not perform well. Next, we explore methods that can help us identify the types of concept drift. The experimental results indicate that sudden and reoccurring concept drift exist in the TAIEX Futures data. Moreover, we propose an ensemble based algorithm for reoccurring concept drift. The most characteristic feature of the proposed algorithm is that it can adaptively determine the chunk size, which is an important parameter for other concept drift handling algorithms.

Straddles and strangles are common trading strategies introduced in a lot of textbooks and are widely used for option market participants. However, to our knowledge, we might not know how these trades should be designed, which trades are preferable, and how they are constructed in practice. Thus, we want to apply and discuss straddles and strangles as our trading strategies to the practical market. In our research paper, focusing on the time value and finding some profitable strategies are the two important concepts of our straddles and strangles. Being a sell side to earn the time value is our main goal. Although we may take higher risk, time value decay is helpful for us. The research focuses on straddles and strangles by using historical data of TAIEX futures and options. We use the closing price and settlement price as our trading price from data period January 2005 to December 2010. We also compare two different situations, holding positions to maturity and early offset condition, to our straddles and strangles. The findings show that the straddle strategies have positive earnings by holding positions to maturity, and 3 out of 4 strangle strategies have the same results. We can indeed earn the time value as a seller because time value decays quickly for the last seven days of the options contracts. After considering the early offset condition, the profitability of the ATM straddle and strangles become worse. We might easily fall into a trap in which the index futures price fluctuates greatly for a few days and comes back to the normal level on the settlement date. Therefore, we encounter loss due to selling low and buying high so that the trading performance is poor compared with the positions held to the end. Key words: Straddle Strategy, Strangle Strategy, Time Value, Settlement, Early Offset, TAIEX Options, TAIEX Futures