My interests in mathematics stems heavily from the intersection of Probabilistic Analysis and Financial mathematics, along with a broad subset of interests in both mathematical and statistical approaches to financial time-series analysis.
As an undergraduate student, I had felt lost in a world of college academics for quite some time. Unlike many other mathematicians who began their love for math at an earlier age, I was very unsure of myself, and for a long time I struggled with finding the right major for me. It wasn’t until the second half of my junior year that I decided to jump into economics, and shortly thereafter I came to the realization I wanted to work on the stock market. During my last year as an undergraduate student in economics, I couldn’t help but wonder “if this OLS regression equation is so great, why isn’t everyone using these to predict the stock market? It just can’t be that easy”. Turns out, my naïve assumption that it can’t be that easy was (depending on who you talk to) correct. For my capstone project, I decided to go head-on towards these weaknesses, and found myself reading about time-series statistics for hours on end.
Jump ahead 4 years, and I am where I stand today: having a fulfilling financial markets internship under my belt, as well as completing a masters in statistics. I am now bent on researching new ideas that can be applied to the financial markets. The only major difference between now and the past few years, however, is the way I am going about doing it: instead of pursuing statistical applications even further, mathematical analysis and its intersection with probability theory has caught my full attention. Going ahead into the next few years, I hope to begin working on probabilistic analysis based ideas that can be applied to the stock market. The possible applications of analysis to finance in my eyes seem to only be limited by one’s imagination.