School of Business and Management Department of Information Systems, Business Statistics and Operations Management 210 Department of Information Systems, Business Statistics and Operations Management Algorithmic Trading Strategies Supervisor: CHEN Yanzhen / ISOM Student: PANGESTU Dani Surya / ECOF WONG Hon Yu / OM ZHOU Zhuorui / COGBM ZHU Xinyu / QFIN Course: UROP1100, Fall UROP1100, Fall UROP1100, Fall UROP3100, Fall Our group accessed and preprocessed the real-time market data during the meeting of the Federal Open Market Committee Press Conference from 2011 to 2017. Then these data are regressed between the market indexes and the speaker behavioural indicator. Behavioural indicators include factors such as blink rate while the market index includes e-mini futures rate, VIX and so on. This serves as an attempt to explore whether the behavioural indicator of the speaker can send market movement signals or not, and is there any chance to construct trading strategies if any pattern of market reaction according to the speaker behaviors is found based on the regression result. Financial Analyses of Tech Companies Supervisor: KOH Tat Koon / ISOM Student: TANG Zexi / MATH-SFM Course: UROP1100, Spring This project aims to examine tech companies' (e.g., FAANG BAT, Salesforce, Oracle, etc.) strategy and financial performance. By collecting weekly stock prices from Bloomberg and analysing stock return with special regression tactics, this project discovers the relationship between mainland tech companies and tries to predict their stock prices in near future. Now, this project is still in its exploratory stage and now only data relevant to mainland tech companies (Alibaba, Meituan, Pinduoduo, Vipshop and Maoyan) is collected and stored in a database.
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