Statement of Purpose for Finance Program

Statement of Purpose

I never forget the days that Mathematics attracted me during my primary school. Every number and equation is amazing to discover. In my fifth grade, in 2008, Financial Crisis shocked me with its dramatic influences on the world. I was so curious why data-numbers that connected with Finance area can shake the world. After reading the book on my high school, Flash boys, written by Micheal Lewis, I was appealed to the knowledge of quantitative traders. Their talent of applying Mathematics to Finance inspiring me to demystify the way of applying Mathematics theory on data and finance.

To resolve my curiosity, I decided to begin studying Mathematics after high school. However, I faced studying barriers during my sophomore. I had a hard time on the upper-level math course not only because I underestimated its complexity but also I was lost about what can I do in the future by studying Group Theory and Elementary Analysis. How could I achieve my goal of discovering the relationship between Math and real-life with knowledge of continuity? The skills I had were just solving theoretical math-problems on paper. I need to find my way out.

It was my internship that impelled me to study Applied Mathematics. In 2018, I participate in an internship program at Sichuan Tsinghua University Energy Internet Research Institute (EIRI) during the summer break. I applied as a member of the Data Analysis group which might connect a lot with Math. The group was responsible for a project about providing Big Data services for industrial enterprises. During the project, interns include me are required to build a random forecast for the future distribution of certain goods. Working with a group of interns who majored in Computer Science, nevertheless, I am the only one who can generate the forecast based on my knowledge of random probability, stochastic process, and MATLAB. I realized the theoretical math concept will provide me great advantages in solving problems. The internship revealed to me the world of data science and the practicability of Mathematics.

After back to school, I changed my specialization to Applied Mathematics immediately. I made excellent progress on theory and application by studying the coursework in Applied Math. I learned Orthogonal Matrices and Single Value Decomposition in Math 121 Linear Algebra course. I was able to apply the Orthogonal Matrices on Matlab to do numerical analysis on Math 105 course and I could use SVD to understand Principal Components Analysis to preprocess data through Python on Math 10 course. My good performance in ODE and PDE courses supports me to learn financial, economic, and physical models in the Math Modeling course. During the COVID-19 pandemic, I joined a research group that focused on Epidemic Modeling at UC Irvine under Prof. Long Cheng’s guidance. At first, I used my ODE knowledge to study the basic SIR model. After analyzing historical data through Matlab, considered the infected tests are delayed by many uncontrollable factors includes the incubation period, we researched a Delay-Differential equation (DDE) to build a new model. Meanwhile, recalling dynamic hedging and Markov chain Monte Carlo from my Statistical Finance Course, I optimized the epidemic model with dynamic changing parameters to solve the problem of variation in infection speed. By studying applied Mathematics, I am not only capable of mining and analyzing data, but also equipped to build a model based on my strong Math theoretical background.

During the days studying Applied Math and learning how to deal with numbers, I read the autobiography of Edward O.Thorp, A Man For All Markets. As a former professor of the UCI math department, he showed me how powerful Mathematics is in the finance market. His words also remind me of the quantitative traders in Flash Boys, who apply Mathematics to Finance. To solve my inquisitiveness on the connection between Finance and Mathematics, I learned a lot of Finance courses. To begin with, on my Math 176 course, I realized how close the relationship between option prices and Black Scholes equations. The stochastic process I learned in Math 130 is the foundation of learning Brownian motion, while I used the Taylor Series to comprehend Ito’s Lemma. Besides learning and writing a proof of these theories, I also have experience in practical application. Based on the methodology of binomial option pricing and its connection with Black Scholes, I wrote a coding on Matlab to calculate the option pricing to increase the iteration of the binomial process. I also construct a matrix method on Matlab to achieve portfolio hedging. By analyzing the data in the option financial market and used my dynamic hedging model, I was able to make 8% profit on Stocktrak platform on trading options this year. My interests in finance and my preparation on data science guarantees my ability to learn and make connection between them.

Besides academic experience at the University of California, Irvine, my data analyst internship, model construction, and investment experience provides me strong knowledge and skills foundation on learning Finance. However, to succeed in the financial industry, advanced skills in statistics, optimization method, and further learning in the stochastic process is necessary. The Financial Engineering Concentration of the Master of Engineering in Operation Research and Information Engineering program at Cornell University provided exactly what I needed and the industry desired. I believe my educational background in Applied Mathematics, my integrated ability in programming, and my internship has prepared me well in pursuing a master’s degree in Financial Engineering. And my master’s experience will provide me profession to become a quantitative trader with the ability to process data, utilize data, discover insights, and present insights.

Statement of Purpose

I never forget the days that Mathematics attracted me during my primary school. Every number and equation is amazing to discover. In my fifth grade, in 2008, Financial Crisis shocked me with its dramatic influences on the world. I was so curious why data-numbers that connected with Finance area can shake the world. After reading the book on my high school, Flash boys, written by Micheal Lewis, I was appealed to the knowledge of quantitative traders. Their talent of applying Mathematics to Finance inspiring me to demystify the way of applying Mathematics theory on data and finance.

To resolve my curiosity, I decided to begin studying Mathematics after high school. However, I faced studying barriers during my sophomore. I had a hard time on the upper-level math course not only because I underestimated its complexity but also I was lost about what can I do in the future by studying Group Theory and Elementary Analysis. How could I achieve my goal of discovering the relationship between Math and real-life with knowledge of continuity? The skills I had were just solving theoretical math-problems on paper. I need to find my way out.

It was my internship that impelled me to study Applied Mathematics. In 2018, I participate in an internship program at Sichuan Tsinghua University Energy Internet Research Institute (EIRI) during the summer break. I applied as a member of the Data Analysis group which might connect a lot with Math. The group was responsible for a project about providing Big Data services for industrial enterprises. During the project, interns include me are required to build a random forecast for the future distribution of certain goods. Working with a group of interns who majored in Computer Science, nevertheless, I am the only one who can generate the forecast based on my knowledge of random probability, stochastic process, and MATLAB. I realized the theoretical math concept will provide me great advantages in solving problems. The internship revealed to me the world of data science and the practicability of Mathematics.

After back to school, I changed my specialization to Applied Mathematics immediately. I made excellent progress on theory and application by studying the coursework in Applied Math. I learned Orthogonal Matrices and Single Value Decomposition in Math 121 Linear Algebra course. I was able to apply the Orthogonal Matrices on Matlab to do numerical analysis on Math 105 course and I could use SVD to understand Principal Components Analysis to preprocess data through Python on Math 10 course. My good performance in ODE and PDE courses supports me to learn financial, economic, and physical models in the Math Modeling course. During the COVID-19 pandemic, I joined a research group that focused on Epidemic Modeling at UC Irvine under Prof. Long Cheng’s guidance. At first, I used my ODE knowledge to study the basic SIR model. After analyzing historical data through Matlab, considered the infected tests are delayed by many uncontrollable factors includes the incubation period, we researched a Delay-Differential equation (DDE) to build a new model. Meanwhile, recalling dynamic hedging and Markov chain Monte Carlo from my Statistical Finance Course, I optimized the epidemic model with dynamic changing parameters to solve the problem of variation in infection speed. By studying applied Mathematics, I am not only capable of mining and analyzing data, but also equipped to build a model based on my strong Math theoretical background.

During the days studying Applied Math and learning how to deal with numbers, I read the autobiography of Edward O.Thorp, A Man For All Markets. As a former professor of the UCI math department, he showed me how powerful Mathematics is in the finance market. His words also remind me of the quantitative traders in Flash Boys, who apply Mathematics to Finance. To solve my inquisitiveness on the connection between Finance and Mathematics, I learned a lot of Finance courses. To begin with, on my Math 176 course, I realized how close the relationship between option prices and Black Scholes equations. The stochastic process I learned in Math 130 is the foundation of learning Brownian motion, while I used the Taylor Series to comprehend Ito’s Lemma. Besides learning and writing a proof of these theories, I also have experience in practical application. Based on the methodology of binomial option pricing and its connection with Black Scholes, I wrote a coding on Matlab to calculate the option pricing to increase the iteration of the binomial process. I also construct a matrix method on Matlab to achieve portfolio hedging. By analyzing the data in the option financial market and used my dynamic hedging model, I was able to make 8% profit on Stocktrak platform on trading options this year. My interests in finance and my preparation on data science guarantees my ability to learn and make connection between them.

Besides academic experience at the University of California, Irvine, my data analyst internship, model construction, and investment experience provides me strong knowledge and skills foundation on learning Finance. However, to succeed in the financial industry, advanced skills in statistics, optimization method, and further learning in the stochastic process is necessary. The Financial Engineering Concentration of the Master of Engineering in Operation Research and Information Engineering program at Cornell University provided exactly what I needed and the industry desired. I believe my educational background in Applied Mathematics, my integrated ability in programming, and my internship has prepared me well in pursuing a master’s degree in Financial Engineering. And my master’s experience will provide me profession to become a quantitative trader with the ability to process data, utilize data, discover insights, and present insights.