DocumentCode
3756740
Title
A Proposal of a Methodological Framework with Experimental Guidelines to Investigate Clustering Stability on Financial Time Series
Author
Gautier Marti;Philippe Very;Philippe Donnat;Frank Nielsen
Author_Institution
Hellebore Capital Manage., France
fYear
2015
Firstpage
32
Lastpage
37
Abstract
We present in this paper an empirical framework motivated by the practitioner point of view on stability. The goal is to both assess clustering validity and yield market insights by providing through the data perturbations we propose a multi-view of the assets´ clustering behaviour. The perturbation framework is illustrated on an extensive credit default swap time series database available online at www.datagrapple.com.
Keywords
"Time series analysis","Clustering algorithms","Correlation","Stability criteria","Databases","Portfolios"
Publisher
ieee
Conference_Titel
Machine Learning and Applications (ICMLA), 2015 IEEE 14th International Conference on
Type
conf
DOI
10.1109/ICMLA.2015.11
Filename
7424282
Link To Document