Department of Accounting
Web Crawling and Business Information Analysis
Supervisor: CHEN Szu Fan / ACCT Co-supervisor: CHEN Zhihong / ACCT
Student: WENG Zijie / QFIN Course: UROP1100, Fall
UROP2100, Spring
With the development of computer science techniques, more and more people choose to use computer programming to help them to analyze business data. This can help researchers and business people gain more insights into the latest issues in corporate governance and business decisions. In this report, the author establishes a web crawling program based on Python, and a VBA program to analyze the data in the press release of all companies on U.S. Securities and Exchange Commission. The author researches into companies’ Non-GAAP reconciliation tables and Non-GAAP earnings like bookings, billings, and backlogs. After comparing the data of the same companies in a period, the author believes that the difference in companies’ behavior will provide some reference for investors.
Financial Analyst Conflict of Interest Supervisor: HUANG Allen Hao / ACCT
Student: HE Mengxi / IS Course: UROP1000, Summer
In this project, I intended to examine how underwriting relationships can affect analysts’ earnings forecast and recommendations. The first question I want to find out is weather affiliated analysts, which refer to lead underwriters and co-underwriters, issue more favorable forecast and recommendation than unaffiliated writers before a company has chosen its underwriter to do the business. The second question I would like to study is the long-term earnings between investors following affiliated underwriter’s suggestions and those following unaffiliated underwriter’s suggestions. Whether the recommendations given by affiliated underwriters will generate weaker performance.
These findings will suggest how banks with different identities (underwriter or non-underwriter) react to the same company’s equity offerings and how the investors react to. By analyzing these results, we will be able to understand how the underwriting relationships might affect the forecasts and recommendations they stated in their reports.
Financial Analyst Conflict of Interest Supervisor: HUANG Allen Hao / ACCT
Student: HU Yunruo / LMGBM Course: UROP1000, Summer
This research project aims to analyze the effect of underwriting relationships on analysts’ earnings forecasts and investment recommendations from two perspectives: analysts’ recommendations and investors’ responses; and for different time periods as well as time points, namely, one-year growth forecast & 5-year growth forecast and before-announcement recommendation & post-announcement recommendation. According to definition, analysts can be divided into two groups, affiliated analysts and unaffiliated analysts. To make this analysis more accurate,
Department of Accounting
affiliated analysts will also be grouped into lead underwriter and co-underwriter analysts. Research on different groups’ comparisons will be carried out. Reasons behind, if there is any difference, or not, between groups’ forecasts in different time periods, will also be analyzed.
Financial Analyst Conflict of Interest Supervisor: HUANG Allen Hao / ACCT
Student: LIU Weiyang / QFIN Course: UROP1000, Summer
This paper explores the influence of underwriting relationship on the earnings forecasts and recommendations of analysts. Following the methodology of the previous research conducted by Lin and McNichols (1998) on companies listed in the US, this article examines the effect on their European counterparts. The long-term growth forecasts issued by lead and co-underwriter analysts are considerably more optimistic than those issued by unaffiliated analysts. The recommendations and subsequent year earnings forecasts issued by affiliated analysts are slightly overoptimistic while affiliated forecasts of current year earnings are less optimistic. The findings suggest affiliated analysts are more likely to issue favorable growth forecasts and recommendations and may have conservative estimations of current year earnings to match their higher forecasted growth.
Financial Analyst Conflict of Interest Supervisor: HUANG Allen Hao / ACCT
Student: WANG Xinyue / QFIN Course: UROP1000, Summer
Financial analysts are necessary intermediaries in capital market for communicating information between listed companies and external investors. Hence the accuracy of earnings forecasts and the quality of recommendations issued by financial analysts are of great significance for investors in terms of investment decisions and valuation of listed companies. This report examines the conflict of interest in underwriting relationship on affiliated analysts’
earnings forecasts and stock recommendations. Major emphasis would be laid on initial public offerings (IPOs) and mergers and acquisitions (M&A) in Europe, considering vast majority of prior researches focused on US markets.
Findings suggest that earnings forecasts of affiliated analysts are on average less accurate and more biased compared to unaffiliated analysts. Moreover, affiliated analysts tend to issue optimistic stock recommendations which
underperform.
Department of Accounting
YANG Chu / FINA UROP1000, Summer
The UROP title “Global Macro and Stock Analysis” is a research lead by professor LI Xi (李系), aiming to gather global macroeconomic data as well as stocks, equities and futures data to perceive macroeconomic trends and therefore predict country/sector growth and decline. We used the data service terminals Bloomberg and Thomson Reuters to gather historical macroeconomic, securities and derivatives data, and by the means of html and Javascript (online) and MySQL and Apache (local database), we visualized the data, employing Python as a means to search for and refine data, coming up with potential investments. Moreover, we have improved the functionality of the online visualization, as well as updating the database and also researching various futures contracts in the world.
Global Macro and Stock Analysis Supervisor: LI Xi / ACCT Student: LI Xinran / ECOF
WU Shuning / QFIN YANG Xiao / QFIN
Course: UROP1100, Fall UROP1100, Fall UROP1100, Fall
In the 3-month time of this UROP Global Macro and stock analysis, our team updates the quarterly report containing over 20000 stocks in 46 MSCI listed countries, analyzes the US Macroeconomics data such as wage rates as well as dynamically computes the interval returns. During the whole process, other than the financial knowledge, we have also trained various programming skills, for example, Visual Basic of Application, MYSQL and Python. As a result, it is an extremely rewarding project we did in the University.
Global Macro and Stock Analysis Supervisor: LI Xi / ACCT
Student: WU Shuning / QFIN Course: UROP2100, Spring
In the 3-month time of this continuing UROP series Global Macro and stock analysis, our team mainly updated the S&P 500 Sector data and the interval returns for individual stocks as well as sectors in the US, HK, Europe and Japan.
We observed the Macroeconomics data such as the US CPI and PPI, and their relationship with the level of S&P 500, USD index, Hang Seng Index, H Share, Shanghai Composite and copper price. We also kept updating the transaction volume of a basket of futures in order to keep track of the popularity of them. Moreover, we learned the technical skills of generating Google graph to display those graphs plotted in excel in a more precise and professional way.