Term of Award

Fall 2012

Degree Name

Master of Science in Mathematics (M.S.)

Document Type and Release Option

Thesis (open access)


Department of Mathematical Sciences

Committee Chair

Patricia Humphrey

Committee Member 1

Martha Abell

Committee Member 2

Jonathan Duggins

Committee Member 3

Jonathan Duggins


In this thesis we explore the problem of detecting change-points in cross-asset correlations using a non-parametric approach. We began by comparing and contrasting several common methods for change-point detection as well as methods for measuring correlation. We finally settle on a statistic introduced in early 2012 by Herold Dehling et.al. and test this statistic against real world financial data. We provide the estimated change-point for this data as well as the asymptotic p-value associated with this statistic. Once this process was complete we went on to use simulated data to measure the accuracy, power, and type 1 error associated with this new statistic. Finally, we were able to draw conclusions on the functionality and usefulness of this statistic.

Included in

Mathematics Commons