Forecasting Exchange Rates: An Empirical Application to Pakistani Rupee

• 발행기관: 한국유통과학회
• 저자명: Muhammad ASADULLAH Adnan BASHIR Abdur Rahman ALEEMI
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 8 No.4, 339~347쪽, 전체 9쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2021.04.30

영문 초록

This study aims to forecast the exchange rate by a combination of different models as proposed by Poon and Granger (2003). For this purpose, we include three univariate time series models, i.e., ARIMA, Naïve, Exponential smoothing, and one multivariate model, i.e., NARDL. This is the first of its kind endeavor to combine univariate models along with NARDL to the best of our knowledge. Utilizing monthly data from January 2011 to December 2020, we predict the Pakistani Rupee against the US dollar by a combination of different forecasting techniques. The observations from M1 2020 to M12 2020 are held back for in-sample forecasting. The models are then assessed through equal weightage and var-cor methods. Our results suggest that NARDL outperforms all individual time series models in terms of forecasting the exchange rate. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models with the lowest MAPE value of 0.612 suggesting that the Pakistani Rupee exchange rate against the US Dollar is dependent upon the macro-economic fundamentals and recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting, as stated by Poon and Granger (2003).

목차

1. Introduction

2. Literature Review

3. Data and Methodology

4. Results and Discussion

5. Conclusion

키워드

Forecasting Exchange Rate Auto-Regressive Naï ve Exponential Smoothing