Date of Award

2011

Degree Type

Thesis

Degree Name

Master of Science (MSc)

Department

Mathematics

First Advisor

Marcos Escobar

Second Advisor

Sebastian Ferrando

Abstract

The aim of the thesis is to emphasize the different dependence measures beyond the well known Pearson correlation. The study is developed in the setting of a fund that deals with multiple strategies hedge funds under risk constraints. The relevance of our analysis is made clears by noticing that the Pearson correlation is sensitive only to linear relationships and it does not capture tail co-movements. Specifically, the dependence measures we focus are Kendall's tau, Spearman's rho and tail dependence. This thesis attempts to suggest some other solutions to an effective optimization that combines various fund strategies by using the aforementioned dependence measures.



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