Modelling the Behaviour of Currency Exchange Rates with Singular Spectrum Analysis and Artificial Neural Networks

Paulo Canas Rodrigues,Olushina Olawale Awe,Rahim Mahmoudvand,Jonatha Sousa Pimentel

doi:10.3390/stats3020012

Paulo Canas Rodrigues, Olushina Olawale Awe + Show 2 more

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https://doi.org/10.3390/stats3020012

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Journal: Stats	Publication Date: Jun 1, 2020
Citations: 9	License type: CC BY 4.0

Affiliation: Universidade Federal da Bahia, Bu-Ali Sina University

Abstract

A proper understanding and analysis of suitable models involved in forecasting currency exchange rates dynamics is essential to provide reliable information about the economy. This paper deals with model fit and model forecasting of eight time series of historical data about currency exchange rate considering the United States dollar as reference. The time series techniques: classical autoregressive integrated moving average model, the non-parametric univariate and multivariate singular spectrum analysis (SSA), artificial neural network (ANN) algorithms, and a recent prominent hybrid method that combines SSA and ANN, are considered and their performance compared in terms of model fit and model forecasting. Moreover, specific methodological and computational adaptations were conducted to allow for these analyses and comparisons.

Highlights

Apart from other important economic indicators such as interest rates, consumer price index, money supply and inflation, the currency exchange rate is one of the most important determinants of a country’s relative level of economic health [1]
The results presented in this paper are based on an alternative parametrization of the autoregressive integrated moving average (ARIMA) model that is implemented in the arima function of the software R [12]
As for artificial neural network (ANN), overfitting may ease the problem of having non-stationary time series significantly and might be a key to success for complex financial time-series analysis [46]

Summary

Introduction

Apart from other important economic indicators such as interest rates, consumer price index, money supply and inflation, the currency exchange rate is one of the most important determinants of a country’s relative level of economic health [1]. No economy can operate in autarky, exchange rates are among the most analysed and governmentally manipulated economic indicators in any nation. A fluctuating (volatile) exchange rate might lead to an unstable economy where it becomes difficult to predict the value of goods, services and other important economic components. Exchange rates have been shown, in the literature, to be among the major challenging and difficult economic measures to accurately forecast because changes in exchange rates are erratic and can have drastic effects on the economy [4,5,6]. Erratic behaviour of exchange rate was identified in the literature as part of the leading causes of economic recessions [7]. Various nations adopt different exchange rate systems based on their history and economic goals. Brazil, India and South Africa implement a free floating exchange rate system while China and Russia adopts a system of managing floating exchange rates

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