Random Matrix Theory and its Applications in Finance
Although Random Matrix Theory has been developed for almost a century, its application in finance is underutilized. A random matrix is a Hermitian matrix with its entries drawn from a normal distribution with mean zero and variance one. Most of its interesting properties lie in the distribution of its eigenvalues. Not until recently has RMT been employed to estimate the profits and risks of financial portfolios. My project focuses on exploring new ways to manipulate current methods frequently adopted to maximize the profit of a financial portfolio given a certain level of risk. My preliminary research has shown that several distributions regarding the eigenvalues of a random matrix and some techniques developed in time series forecasting are likely to contribute in producing a better estimate. Thus, the goal of my project is to develop a method that can refine current estimates by integrating techniques derived from time series forecasting into Random Matrix Theory.
Message to Sponsor
- Major: Applied Mathematics, Statistics
- Sponsor: Thye Fund
- Mentor: Steve Evans, Mathematics