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Forecasting Turkish lira against the US Dollars via forecasting approaches

Author

Listed:
  • Rabia Sabri
  • Abdul Aziz Abdul Rahman
  • Abdelrhman Meero
  • Liaqat Ali Abro
  • Muhammad AsadUllah

Abstract

The aim of this study is to predict the Turkish Lira’s exchange rate against the US Dollar by combining models . As a result, the authors include three univariate forecasting models: ARIMA, Naive, and Exponential smoothing, and one multivariate model: NARDL for the first time with Artificial Neural Network model. To the best of our knowledge, it is a unique study to integrate univariate models, ANN with NARDL. The researchers utilize two combination criteria to forecast the Turkish Lira, namely, equal weightage and var-cor. The findings conclude that the combination of NARDL and Naive outperforms all standalone and combined time series techniques. The results indicate that the Turkish Lira’s currency rate against the USD is strongly reliant on recent time-series observations with symmetric and asymmetric behavior of macro-economic fundamentals.

Suggested Citation

  • Rabia Sabri & Abdul Aziz Abdul Rahman & Abdelrhman Meero & Liaqat Ali Abro & Muhammad AsadUllah, 2022. "Forecasting Turkish lira against the US Dollars via forecasting approaches," Cogent Economics & Finance, Taylor & Francis Journals, vol. 10(1), pages 2049478-204, December.
    • Handle: RePEc:taf:oaefxx:v:10:y:2022:i:1:p:2049478
    DOI: 10.1080/23322039.2022.2049478
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    Cited by:

    1. Joscha Beckmann & Robert L. Czudaj, 2023. "The role of expectations for currency crisis dynamics—The case of the Turkish lira," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 625-642, April.

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