Faculty Advisor or Committee Member

Marcel Y. Blais, Advisor

Identifier

etd-080614-144242

Abstract

"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."

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Mathematical Sciences

Project Type

Thesis

Date Accepted

2014-08-06

Accessibility

Unrestricted

Subjects

Principle Component Analysis

Share

COinS