Please review this essay. Please also comment on the overall structure of the essay. I have used the word helped many times; not sure how to restructure the sentences to get rid of one or two of them.
Describe your background and preparation in the four concentration areas - finance, computer science, math and statistics. In particular, please detail your background in calculus-based probability. If your only exposure to probability was as part of a course that combined probability and statistics, please list the probability topics covered by this course.
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During my five-year coursework at XXX, I came across a multitude of mathematical science courses. The first three semesters at XXX focused on mathematical analysis, linear algebra, calculus-based probability and statistical methods. The courses set the foundation for the advanced courses taken at later semesters.
Courses on mathematical analysis and linear algebra taught me the way to reason mathematical theorems. While linear transformation approach to linear algebra helped me to easily visualize and grasp important mathematical results, the theorems and concepts of mathematical analysis eased my way to learn measure-theoretic probability. Statistical methods introduced me to the standard methods of statistical analysis.
The foundation courses while helped me to understand and establish advance statistical concepts, the courses also provided me with new perspectives to look at various statistical results. The idea that linear regression can be seen as a projection, gave me insights to approach statistical problems from multiple directions.
The advanced courses introduced me to the novel branches of statistics such as machine learning, decision theory, and time series analysis. Introduction to various topics such as clustering, classification, and statistical sampling, enhanced my statistical skills. I learned that one needs to be mindful of outliers and the curse of dimensionality while doing data analysis. I successfully applied my learning to various projects I undertook.
At XXX, I also took four computer programming courses. The courses taught me the fundamentals of programming, the principles of database management systems, and the advance concepts of numerical analysis and data structures. The courses, projects and assignments helped me to gain an expertise in few programming languages and statistical softwares. At XXX, on an average, I devoted about one hour everyday to programming, which led me to learn the secrets of good programming practices.
In finance course, I learned celebrated concepts such as Black-Scholes model, option pricing theory, and delta hedging. The concepts such as mean-variance portfolio theory came handy when I applied my findings of the dissertation project for predictive portfolio analysis.
At YYY, I have built various financial models for US mortgage products. I have also conceptualized and developed trading strategies for the etf trading desk.
While building mortgage models, I gained an expertise over the primary and secondary US residential mortgage market. I developed an in-depth understanding of various kinds of mortgage loans (prime, sub-prime, Jumbo, ARM, FRM etc.) and their borrower characteristics. It was a challenge to model the prepayment behavior of mortgage borrowers. Moreover, as the econometric problem was non-linear in nature, standard goodness of fit measures were not applicable to access the quality of produced model.
I produced an internal research paper to propose a new goodness of fit measure for our problem. Using the measure, I developed a prepayment model, which is currently used by CMO trading desk to price mortgage securities. I also generated analytics report on empirical duration, OAS duration etc. which helped us to analyze the performance of various models.
In algorithmic trading business, I learned the process of generating strategies, understood typical issues (for instance, latency) associated with trading processes, and get to know the need to reconcile our daily trade statistics with that of controllers. I dealt with millisecond level tick data, and learned the basic concepts of financial market such as net asset value, active and passive trading, and the rung of a fill.
The generation of trading strategies required extensive application of machine learning techniques. Apart from testing my technical skills, the exercise also tested my communication skills. I had to convince the desk using innovative ideas to use the strategies in production.
My job requires around five hours of programming everyday, which involves heavy use of KDB/Q and to a lesser extent C++. I learned the skills to produce and maintain large code base efficiently. My programming experience also helped me to gain an understanding of various paradigms of programming.
I attend a weekly meeting with Dr. PPP, global head of market modeling at AAA. In a couple of those meetings, PPP gave lectures on his research papers. The lectures also enhanced my understanding of stochastic calculus.
I have also passed Financial Risk Manager (FRM) examination of GARP. The coursework improved my understanding of risk management and helped me to learn about different businesses such as credit and interest rate.
Describe your background and preparation in the four concentration areas - finance, computer science, math and statistics. In particular, please detail your background in calculus-based probability. If your only exposure to probability was as part of a course that combined probability and statistics, please list the probability topics covered by this course.
---------------------------------------------------------------------- -----------------------------------------------------------------
During my five-year coursework at XXX, I came across a multitude of mathematical science courses. The first three semesters at XXX focused on mathematical analysis, linear algebra, calculus-based probability and statistical methods. The courses set the foundation for the advanced courses taken at later semesters.
Courses on mathematical analysis and linear algebra taught me the way to reason mathematical theorems. While linear transformation approach to linear algebra helped me to easily visualize and grasp important mathematical results, the theorems and concepts of mathematical analysis eased my way to learn measure-theoretic probability. Statistical methods introduced me to the standard methods of statistical analysis.
The foundation courses while helped me to understand and establish advance statistical concepts, the courses also provided me with new perspectives to look at various statistical results. The idea that linear regression can be seen as a projection, gave me insights to approach statistical problems from multiple directions.
The advanced courses introduced me to the novel branches of statistics such as machine learning, decision theory, and time series analysis. Introduction to various topics such as clustering, classification, and statistical sampling, enhanced my statistical skills. I learned that one needs to be mindful of outliers and the curse of dimensionality while doing data analysis. I successfully applied my learning to various projects I undertook.
At XXX, I also took four computer programming courses. The courses taught me the fundamentals of programming, the principles of database management systems, and the advance concepts of numerical analysis and data structures. The courses, projects and assignments helped me to gain an expertise in few programming languages and statistical softwares. At XXX, on an average, I devoted about one hour everyday to programming, which led me to learn the secrets of good programming practices.
In finance course, I learned celebrated concepts such as Black-Scholes model, option pricing theory, and delta hedging. The concepts such as mean-variance portfolio theory came handy when I applied my findings of the dissertation project for predictive portfolio analysis.
At YYY, I have built various financial models for US mortgage products. I have also conceptualized and developed trading strategies for the etf trading desk.
While building mortgage models, I gained an expertise over the primary and secondary US residential mortgage market. I developed an in-depth understanding of various kinds of mortgage loans (prime, sub-prime, Jumbo, ARM, FRM etc.) and their borrower characteristics. It was a challenge to model the prepayment behavior of mortgage borrowers. Moreover, as the econometric problem was non-linear in nature, standard goodness of fit measures were not applicable to access the quality of produced model.
I produced an internal research paper to propose a new goodness of fit measure for our problem. Using the measure, I developed a prepayment model, which is currently used by CMO trading desk to price mortgage securities. I also generated analytics report on empirical duration, OAS duration etc. which helped us to analyze the performance of various models.
In algorithmic trading business, I learned the process of generating strategies, understood typical issues (for instance, latency) associated with trading processes, and get to know the need to reconcile our daily trade statistics with that of controllers. I dealt with millisecond level tick data, and learned the basic concepts of financial market such as net asset value, active and passive trading, and the rung of a fill.
The generation of trading strategies required extensive application of machine learning techniques. Apart from testing my technical skills, the exercise also tested my communication skills. I had to convince the desk using innovative ideas to use the strategies in production.
My job requires around five hours of programming everyday, which involves heavy use of KDB/Q and to a lesser extent C++. I learned the skills to produce and maintain large code base efficiently. My programming experience also helped me to gain an understanding of various paradigms of programming.
I attend a weekly meeting with Dr. PPP, global head of market modeling at AAA. In a couple of those meetings, PPP gave lectures on his research papers. The lectures also enhanced my understanding of stochastic calculus.
I have also passed Financial Risk Manager (FRM) examination of GARP. The coursework improved my understanding of risk management and helped me to learn about different businesses such as credit and interest rate.