Stochastics: Finance and Risk
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.
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,
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© A. G. Malliaris and Mary Malliaris 2011