Exchange rates forecasting using nonparametric methods

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@PhdThesis{Marcos_Alvarez-Diaz:thesis,

• author = "Marcos Alvarez-Diaz",
• title = "Exchange rates forecasting using nonparametric methods",
• school = "Columbia University",
• year = "2006",
• address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-0-542-91527-7",
• URL = "http://search.proquest.com/docview/305345652",
• size = "105 pages",
• abstract = "The existence of non-linear deterministic structures in the dynamics of exchange rates has already been amply demonstrated in the literature. With my research, I try to explain if we can exploit these non-linear structures in order to improve our predictive ability and, secondly, if we can use these predictions to generate profitable strategies in the Foreign Exchange Market. To this purpose, I employ different nonparametric forecasting methods such as Nearest Neighbours, Genetic Programming, Artificial Neural Networks, Data-Fusion or an Evolutionary Neural Network. My analysis will be centre on the specific case of the Yen/US$ and Pound Sterling/US$ exchange rates and it considers both point predictions and the anticipating of either depreciations or appreciations. My results reveal a slight forecasting ability for one-period-ahead which is lost when more periods ahead are considered, and my trading strategy obtains above-normal profits. However, when transaction costs are incorporated, the profits practically disappear or become negative",
• notes = "UMI Microform 3237194 ProQuest Dissertations Publishing, 2006. 3237194",

}

Genetic Programming entries for Marcos Alvarez-Diaz

Citations