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Forecasting Euro against US dollar via combination of NARDL and Univariate techniques during COVID-19

Muhammad AsadUllah (Department of Commerce and Professional Studies at the Institute of Business Management, Karachi Pakistan)
Muhammad Adnan Bashir (Department of Marketing, Institute of Business Management, Karachi, Pakistan)
Abdur Rahman Aleemi (Department of Accounting and Finance at the Institute of Business Management, Karachi, Pakistan)

Foresight

ISSN: 1463-6689

Article publication date: 16 July 2021

Issue publication date: 29 April 2022

212

Abstract

Purpose

The purpose of this study is to examine the accuracy of combined models with the individual models in terms of forecasting Euro against US dollar during COVID-19 era. During COVID, the euro shows sharp fluctuation in upward and downward trend; therefore, this study is keen to find out the best-fitted model which forecasts more accurately during the pandemic.

Design/methodology/approach

The descriptive design has been adopted in this research. The three univariate models, i.e. autoregressive integrated moving averages (ARIMA), Naïve, exponential smoothing (ES) model, and one multivariate model, i.e. nonlinear autoregressive distributive lags (NARDL), are selected to forecast the exchange rate of Euro against the US dollar during the COVID. The above models are combined via equal weights and var-cor methods to find out the accuracy of forecasting as Poon and Granger (2003) showed that combined models can forecast better than individual models.

Findings

NARDL outperforms all remaining individual models, i.e. ARIMA, Naïve and ES. By applying a combination of different models via different techniques, the combination of NARDL and Naïve models outperforms all combination of models by scoring the least mean absolute percentage error value, i.e. 1.588. The combined forecasting of NARDL and Naïve techniques under var-cor method also outperforms the forecasting accuracy of individual models other than NARDL. It means the euro exchange rate against the US dollar which is dependent upon the macroeconomic fundamentals and recent observations of the time series.

Practical implications

The findings could help the FOREX market, hedgers, traders, businessmen, policymakers, economists, financial managers, etc., to minimize the risk indulged in global trade. It also helps to produce more accurate results in different financial models, i.e. capital asset pricing model and arbitrage pricing theory, because their findings may not be useful if exchange rate fluctuations do not trace effectively.

Originality/value

The NARDL models have been applied previously in different time series and only limited to the asymmetric or symmetric relationships. This study is using it for the forecasting exchange rate which is almost abandoned in earlier literature. Furthermore, this study combined the NARDL with univariate models to produce the accuracy which itself is a novelty. Moreover, the findings help to enhance the effectiveness of different financial theories as well.

Keywords

Acknowledgements

The authors are extremely thankful to the journal’s editors and the anonymous referees for their valued suggestions to improve this work.

Citation

AsadUllah, M., Bashir, M.A. and Aleemi, A.R. (2022), "Forecasting Euro against US dollar via combination of NARDL and Univariate techniques during COVID-19", Foresight, Vol. 24 No. 3/4, pp. 319-335. https://doi.org/10.1108/FS-04-2021-0082

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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