UROP Proceedings 2010-11

Financial Risk ManagementAdvisor : SO Mike K P / ISOMStudent : JIANG Yue / RMBI(UROP1100, Fall 2010)This research project focuses on finding a suitable model to forecast the quantile basedrealized volatility of financial asset’s return. We first learn about the necessary backgroundknowledge and review literature about modeling technology. We then collect high-frequencydata, write programs for sorting stock prices, calculate quantile based realized volatility andstudy its properties.A Text Mining Approach on News Analytics: Overview and EmpiricalStudyAdvisor : SO Mike K P / ISOMStudent : LI Wai Ming / RMBI(UROP1100, Fall 2010)This project studies the use of text mining approach in trading volume prediction in highfrequency context. Several state-of-the-art algorithms are introduced and an empirical study isconducted. Results show that the classification attains 75% accuracy at cross validation inpredicting whether trading period subsequent to the news arrival has an abnormally high/lowtrading volume.Use of Statistical Technique in Financial News Analytics: ExperimentalStudy and DiscussionAdvisor : SO Mike K P / ISOMStudent : LI Wai Ming / RMBI(UROP1200, Spring 2011)This project is a study on various techniques in classification problem of financial newsanalytics. The Principal Component Analysis (PCA), Linear Discriminant Analysis and LatentSemantic Indexing techniques are examined for level of accuracy and ability in reducing thenoise level of the extracted data. Results show that the use of PCA attains a similar level ofaccuracy but a much smaller bias in classification.66