School of Business and Management Department of Finance 205 Products, Supply Chains, and Finance Supervisor: ZALDOKAS Alminas / FINA Student: LI Mengyi / QFIN Course: UROP4100, Spring The goal of the research is to quantify the relationship between the first-time released New Product Announcement (NPA) and the abnormal return of the underlying stock within a two-day event window. We focused on the implementation issues based on the ideas generated in the previous semester, and we mainly accomplished the following tasks: automatically converted the raw data in .rtf form into .xlsx form, automatically converted the word document in .docx form into .txt form, and retrieved information needed for further processing, and conducted Term Frequency – Inverted Document Frequency (TF-IDF) test to find out similar articles. Products, Supply Chains, and Finance Supervisor: ZALDOKAS Alminas / FINA Student: HUI Siu Lun / ECOF LING Xiuqi / ECOF XIAO Yunyi / QFIN YUAN Xuzhi / FINA WONG Chun Ho / QFIN Course: UROP1100, Spring UROP1100, Spring UROP1100, Spring UROP1100, Spring UROP2100, Spring The ultimate goal of this research is to find out relationships between New Product Announcement (NPA) and the abnormal return for given stocks listed on NYSE and NASDAQ. In addition to this, we will continue discussing the relationships of the NPA and their effects on the economy. One important stage of this research is to build up the database and utilize big data technologies to clean it and identify keywords related to the company and their new products. We exchanged different ideas to overcome the difficulties in this stage, and have been able to set up a framework for further experiments. Next, we have designed codes for keyword identification and extraction is implemented, and we will try refining the code. Products, Supply Chains, and Finance Supervisor: ZALDOKAS Alminas / FINA Student: LUI Hiu Lum / ACCT SHI Qingqing / ECOF ZHUANG Nanpeng / QFIN YUAN Xuzhi / FINA Course: UROP1100, Summer UROP1100, Summer UROP1100, Summer UROP2100, Summer This research will continue the process from last semester to find out the relationships between New Product Announcement (NPA) and the stock return. We will exam whether the second or third news describing the same product can also affect the stock price. We will further analyze if the stock return is correlated with the similarity of 2 news articles or the number of days between 2 articles. In this program, we start from code refinement and data cleaning to abstract all data we need from Bloomberg Terminal. And end up with regression model analysis to make our conclusion.
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