Sustainable Development Goals (SDGs)
一、團隊目標 Team Goals
金融市場充斥著大量的數據,使得金融投資分析一向是資訊工程應用最多的領域之一。但相較於以往許多研究著重在程式交易,隨著資料科學的廣泛發展,大數據使用於投資分析成為重要的研究議題。目前大數據分析雖然提供許多解決方案,但金融市場的數據類型繁雜,如何應用於投資分析?應用的有效性為何?這些問題仍有待研究。為了回答上述問題,需要不同領域的研究者合作,尤其是程式設計、資料科學與金融投資分析。藉由本計畫,我們希望以金融大數據分析建立的模型來檢驗不同投資策略的績效。研究的重點將著重在資料科學技術能夠存取的公開數據,分析出具有代表性的資訊來源,進行樣本內與樣本外檢驗,並與傳統的基本面或技術分析進行比較。
Financial markets are filled with a large amount of data that changes rapidly over time, making financial analysis one of the most successful applications for information technology. With the extensive development of data science, the use of “big data” in the financial investment analysis has become an important research topic. Big data analysis currently offers many solutions; however, the types of data in financial markets are complex; how can they be applied to investment analysis? What is the effectiveness of the application? These questions still need to be studied. Answering these questions will require collaboration between researchers in different fields, especially programming, data science, and financial investment analysis. By this project, we seek to examine the performance of different investment strategies with the model established by financial big data analysis. Our research will focus on the information or statistics that are publicly accessible via the skills of data science. We will identify representative data sources, conduct in-sample and out-of-sample tests, and perform the comparison with traditional fundamental or technical analysis.
二、招募學生條件 Desired Disciplines & Prior Knowledge of Student Participants
資工系與財金系中對投資理財、程式設計、資料科學以及大數據分析有興趣的學生為主。
Students who are interested in investments and financial management, programming, data science and big data analysis in the Department of Information Technology and the Department of Finance.
三、團隊學生需選修其他延伸課程 Other support courses or knowledge
初等程式設計 - Python、投資分析與程式設計(跨域共授課程)
四、團隊指導教師群 Team Leaders & Members
五、團隊相關連結(網頁、粉絲頁、等) Other Information
六、聯絡窗口 :