Term of Award
Fall 2012
Degree Name
Master of Science in Mathematics (M.S.)
Document Type and Release Option
Thesis (open access)
Department
Department of Mathematical Sciences
Committee Chair
Patricia Humphrey
Committee Member 1
Martha Abell
Committee Member 2
Jonathan Duggins
Committee Member 3
Jonathan Duggins
Abstract
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.
Recommended Citation
Diamond, L. Kaili, "A Non-Parametric Approach to Change-Point Detection in Cross-Asset Correlations" (2012). Electronic Theses & Dissertations. 16.
https://digitalcommons.georgiasouthern.edu/etd/16