Forecasting exchange rates with linear and nonlinear models

Bissoondeeal, Rakesh; Binner, Jane; Bhuruth, Muddun; Gazely, Alicia M. and Mootanah, Veemadevi P. Forecasting exchange rates with linear and nonlinear models. Working Paper. Aston University, Birmingham (UK).

Abstract

In this paper the exchange rate forecasting performance of neural network models are evaluated against random walk and a range of time series models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore the parameters are chosen according to what the researcher considers to be the best. Such an approach, however, implies that the risk of making bad decisions is extremely high which could explain why in many studies neural network models do not consistently perform better than their time series counterparts. In this paper through extensive experimentation the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of performing well. Our results show that in general neural network models perform better than traditionally used time series models in forecasting exchange rates.

Divisions: Aston Business School > Economics finance & entrepreneurship
Aston Business School > Economics finance & entrepreneurship research group
Uncontrolled Keywords: exchange rates,forecasting,time series models,neural networks

Download

Full text not available from this repository.

Export / Share Citation


Statistics

Additional statistics for this record