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A hybrid slantlet denoising least squares support vector regression model for exchange rate prediction
Procedia Computer Science
Despite the active exploration of linear and nonlinear modeling of exchange rates, there is no consensus on the optimal forecasting model other than the traditional random walk and ARMA benchmark models in the literature. Given the increasing recognition of heterogeneous market structure, this paper proposes an alternative Slantlet denoising based hybrid methodology that attempts to incorporate the linear and nonlinear data features. The recently emerging Slantlet analysis is introduced todoi:10.1016/j.procs.2010.04.270 fatcat:b22riqfdjzcq7kcxxqeearla64