录取学校：University of California, Los Angeles Master of Financial Engineering
Financial engineering requires a combination of mathematical/quantitative abilities and creative thinking. Describe a project you worked on, either as a student or professional, than demonstrates your analytical and creative problem-solving skills. Tell us why this project was interesting to you. (Maximum 750 words)
Having a keen interest in Financial Engineering, I have seized every opportunity to hone my quantitative ability in every possible way. In March 2020, after I learned that Professor Eric See-To at The Hong Kong Polytechnic University was recruiting undergraduate students to conduct researches on consumer behaviors through the application of data science techniques, I immediately contacted Professor See-To. After two rounds of online interview, I became an intern on Professor See-To’s research projects.
From March to September in 2020, under the direction of Professor Eric See-To, I participated in two projects. First, I studied the relationship between social media comments and the price of stocks. I was in charge of analyzing the comments that Prof. See-To collected from thirty companies, and trying to build an emotion model through data processing and mining. In this financial sentiment analysis project, I first tried our several algorithms and recorded the accuracy rate of each algorithm, and at last, chose the Naive Bayes to grade the consumer comments. Later, I also learned to use Lexicon to grade the comments. Through this project, I have advanced my understanding and utilization of algorithms and also trained my skills of using Python to analyze data.
In the second project, I analyzed consumers’ comments on restaurants ’ services, in which, I further enhanced my ability to apply different methods of sentiment analysis like Continuous Bag of Words (CBOW) and Skip-gram. Prof. See-To has rich professional experience for international firms in the banking and finance industry. Thus, through our interactions, he gave me many constructive suggestions and guidance, which indeed strengthened my determination to launch a career as a financial analyst.
Why does a career in quantitative finance appeal to you? Based on your abilities and what you know about careers in financial engineering, why do you think this is the right career path for you? (Maximum 750 words)
My goal is to become a financial analyst in an investment bank, security company, fund, or investment firm. Conscious that quantitative analysis plays a vital role in financial analysis, at Sun Yat-sen University (SYSU) I have taken a series of mathematics courses and achieved high marks in them, including Calculus, Linear Algebra, Discrete Mathematics, Probability and Statistics, and Engineering Mathematics. In computer science, I have studied in-depth C, C++, JAVA, data structures, operating systems, database management, ERP, WEB development technologies, information security technology, computer network technology, workflow technology, etc. to enable me to quickly master software applications like Matlab, R, SAS, and S-PLUS. Besides, with my experience in cross-platform coding, programming debugging, and testing of Windows and Linux, I am confident that I can perform advanced cross-platform operations of analysis tools.
However, I am well aware that to fulfill my goals, I need to acquire more advanced quantitative analysis tools and methods. Also, considering that some of the knowledge I have attained at SYSU, such as computational methods, matrix analysis, stochastic process, statistics, and data analysis, did not apply to finance, during my graduate program I will combine them with the study of financial analysis to learn how they apply more directly to finance.
Data Analysis and Data Ming also lay a solid foundation for financial analysis, so apart from course study and class projects, I have sought opportunities to conduct research in the application of data mining to finance. In Fall 2020, while participating in our School’s Software Engineering Training, I teamed up with two schoolmates and signed up for the Micro-Loans User’s Credit Prediction Competition, using the given data of users to forecast their credits. As the team leader, I took charge of the data mining and the progress of our project. At first, we used single model to process and analyze the data. After we submitted our results, although the effect of the training set worked well, the scores of our work were not high. Serving as the head of our team, I could not just give it up halfway through and organized several group meetings to discuss and analyze the places of our work that could be improved. After some brainstorming, we found the limitations of using single model, so we tried out the integration of models. We applied several algorithms, such as the Logistic Regression, SVM (Support Vector Machine), RF (Random Forest) and XGBoost, and eventually adopted the results from RF and XGBoost algorithms to carry out the convergence training. At last, our work earned a quite good score in the competition. This experience is of great value to me since it has not only given me the opportunity to improve my mastery of algorithms applied to data mining, but also tempered my ability to communicate and work with others.
I strongly believe that I am well prepared to pursue UCLA Anderson’s MFE program. I am certain that I will make full use of the resources offered at UCLA to build the knowledge I need in order to prepare for my career goals.
Personal History Statement
Under my family’s constant influence, I started to plan my career path to become a financial analyst during high school. My mother worked at the People’s Bank of China and would often talk with me about taxation, financial risk management, and how the circulation of money influences the inflation rate. When she transferred to a commercial bank, I learned from her about savings, loans, commercial mortgages, financial asset management, and credit ratings. Later, when she served as the general manager of an investment company, I got the chance to dabble in risk investment and became familiar with products like stocks, securities, and funds. All that financial knowledge intrigued and encouraged me to grasp more of it.
My mother began to discuss my career path with me when I was in high school and offered me many great suggestions. The original plan was for me to study finance for both my undergraduate and graduate degrees to form a comprehensive view of the finance field and sharpen my financial analysis ability from every possible aspect. However, we adjusted this plan when I learned from my teachers that to better master Financial Engineering, it is essential to build a sound mathematics and computer science foundation. Additionally, many American universities, they said, preferred Financial Engineering graduate applicants to have a strong background in mathematics and computer science.
So I was thrilled be admitted to major in Software engineering at the Data and Computer Science School at the Sun Yat-sen University (SYSU). I have spared no effort to actively participate in class projects and undertake independent research to advance my understanding of mathematics and computer science applications.
In my spare time, I taught myself finance and economics courses such as Principles of Finance, Microeconomics, and Macroeconomics. Through these courses, my interest in Quantitative Financial Analysis, Financial Products, Derivatives Pricing and Trading, and Risk Management grew progressively stronger. To become an outstanding financial analyst, I can see clearly that I need to master Quantitative Analysis, Risk Analysis, Pricing Methods, AssetAllocation, Investment Strategies, and Numerical Valuation. This is why I want to pursue the Master of Financial Engineering program at UCLA, to become thoroughly equipped with the tools and concepts I will need as a financial analyst, and subsequently take the CFA test. I will also take advantage of my computer background and concentrate on the study of Financial Programming and Financial Software Development.