Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-042605-092010

Document Typethesis
Author NameRen, Zhiwei
URNetd-042605-092010
TitlePortfolio Construction using Clustering Methods
DegreeMS
DepartmentMathematical Sciences
Advisors
  • Arthur Heinricher, Advisor
    • Keywords
  • risk
  • clustering
  • covariance matrix
  • expected return
    • Date of Presentation/Defense2005-04-26
    Availability unrestricted

    Abstract

    One major criticism about the traditional mean-variance

    portfolio optimization is that it tends to magnify the estimation

    error. A little estimation error can cause the distortion of the

    whole portfolio.

    Two popular ways to solve this problem are to use a

    resampling method or the Black-Litterman method (Bayesian

    method).

    The clustering method is a newer way to solve the problem.

    Clustering means we group the highly correlated stocks first

    and treat the group as a single stock. After we group the

    stocks, we will have some clusters of stocks, then we run the

    traditional mean-variance portfolio optimization for these

    clusters. The clustering method can improve the stability

    of the portfolio and reduce the impact of estimation error. In

    this project, we will explain why it works and we will perform

    tests to determine if clustering methods do improve the

    stabilities and performance of the portfolio.

    Files
  • ZhiweiRen.pdf

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