Identifier

etd-11172006-091911

Degree

Master of Science (MS)

Department

Mathematics

Document Type

Thesis

Abstract

Though Pearson's correlation coefficient provides a convenient approach to measuring the dependency between two variables, in the last few years, there has been a significant amount of literature cautioning against the use of Pearson's correlation coefficient, as it does not remain invariant under monotone transformations of the underlying distribution functions. Since we are interested in examining the dependency pattern observed by the return on the Sterling Pound with that of the Japanese Yen, we will use the notion of a copula to approximate the joint density function between the daily returns on the Sterling Pound and the Japanese Yen. In particular, we use a result that is fundamental to the development of copula theory, namely Sklar's Theorem, to examine the observed joint density function between the daily returns on the Sterling Pound and the Japanese Yen. We will attempt to capture the approximated joint density function using a theoretical Gaussian Copula Model. This comparison is performed in the case where the underlying marginal distributions are both uniform, as well as the case where the underlying marginal distributions are both gaussian.

Date

2006

Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Ambar N. Sengupta

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