Forecasting Chinese Yuan/USD Via Combination Techniques During COVID-19

• 발행기관: 한국유통과학회
• 저자명: Muhammad ASADULLAH Imam UDDIN Arsalan QAYYUM Sharique AYUBI Rabia SABRI
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 8 No.5, 221~229쪽, 전체 9쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2021.05.30

영문 초록

This study aims to forecast the exchange rate of the Chinese Yuan against the US Dollar by a combination of different models as proposed by Poon and Granger (2003) during the Covid-19 pandemic. For this purpose, we include three uni-variate 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 Chinese Yuan against the US dollar by two combination criteria i.e. var-cor and equal weightage. After finding out the individual accuracy, the models are then assessed through equal weightage and var-cor methods. Our results suggest that Naïve outperforms all individual & combination of time series models. Similarly, the combination of NARDL and Naïve model again outperformed all of the individual as well as combined models except the Naïve model, with the lowest MAPE value of 0764. The results suggesting that the Chinese Yuan exchange rate against the US Dollar is dependent upon the recent observations of the time series. Further evidence shows that the combination of models plays a vital role in forecasting which commensurate with the literature.

목차

1. Introduction

2. Literature Review

3. Methodology

4. Results and Discussion

5. Conclusion and Limitations

키워드

Forecasting Exchange Rate Auto-Regressive Naï ve Exponential Smoothing