Are Foreign Currency Markets Interdependent? Evidence from Data Mining Technologies

Authors

Anastasios G. Malliaris, Loyola University ChicagoFollow
Mary Malliaris, Loyola University Chicago

Document Type

Article

Publication Date

2012

Publication Title

Stochastics: Finance and Risk

Volume

2

Pages

31-47

Abstract

This study uses two data mining methodologies: Classification and Regression Trees (C&RT) and Generalized Rule Induction (GRI) to uncover patterns among daily cash closing prices of eight currency markets. Data from 2000 through 2009 is used, with the last year held out to test the robustness of the rules found in the previous nine years. Results from the two methodologies are contrasted. A number of rules which perform well in both the training and testing years are discussed as empirical evidence of interdependence among foreign currency markets. The mechanical rules identified in this paper can usefully supplement other types of financial modeling of foreign currencies.

Comments

Author Posting. © A. G. Malliaris and Mary Malliaris 2011. This is the author's version of the work. It is posted here by permission of the Munich Personal RePEc Archive for personal use, not for redistribution. The definitive version was published in Stochastics: Finance and Risk, vol. 2, 2012, https://mpra.ub.uni-muenchen.de/35261/

Recommended Citation

Malliaris, Anastasios G. and Malliaris, Mary. Are Foreign Currency Markets Interdependent? Evidence from Data Mining Technologies. Stochastics: Finance and Risk, 2, : 31-47, 2012. Retrieved from Loyola eCommons, School of Business: Faculty Publications and Other Works,

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

Copyright Statement

© A. G. Malliaris and Mary Malliaris 2011