文章基本信息

标题：Forecasting Turkish lira against the US Dollars via forecasting approaches
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作者：Rabia Sabri ; Abdul Aziz Abdul Rahman ; Abdelrhman Meero 等
期刊名称：Cogent Economics & Finance
电子版ISSN：2332-2039
出版年度：2022
卷号：10
期号：1
页码：1-15
DOI：10.1080/23322039.2022.2049478
语种：English
出版社：Taylor and Francis Ltd
摘要：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.
关键词：Projection ;exchange rate changes ;auto-regressive ;naïve ;exponential smoothing ;ANN