Document Type masters report Author Name Chen, Huanting Email Address hchen at wpi.edu URN etd-080614-144242 Title Portfolio Construction Using Principle Component Analysis Degree MS Department Mathematical Sciences Advisors Marcel Y. Blais, Advisor Keywords Principle Component Analysis Date of Presentation/Defense 2014-08-06 Availability restricted
Principal Components Analysis (PCA) is an important mathematical technique widely used in the world of quantitative finance. The ultimate goal of this paper is to construct a portfolio with hedging positions, which is able to outperform the SPY benchmark in terms of the Sharpe ratio. Mathematical techniques implemented in this paper besides principle component analysis are the Sharpe ratio, ARMA, ARCH, GARCH, ACF, and Markowitz methodology. Information about these mathematical techniques is listed in the introduction section.
Through conducting in sample analysis, out sample analysis, and back testing, it is demonstrated that the quantitative approach adopted in this paper, such as principle component analysis, can be used to find the major driving factor causing movements of a portfolio, and we can perform a more effective portfolio analysis by using principle component analysis to reduce the dimensions of a financial model.
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