On the use of ARIMA and GARCH in Modelling Nigeria’s Naira: Us Dollar Monthly Exchange Rates
Ahmad, Nafisatu Tanko, G. K. Musa, Musa, Salisu Auta, Muhammed Haruna
Asian Journal of Probability and Statistics · pp. 8–18 · Published 8 Apr 2023
10.9734/ajpas/2023/v22i2479Abstract
This paper aimed at modelling the volatility of monthly average official exchange rate (Naira/USD) using the Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) for the period January, 1981 to December, 2021. The data for the study was obtained from Central Bank of Nigeria 2021 Statistical Bulletin. The time plot, Augmented Dickey Fuller (ADF) and Phillip’s Perron (PP) were used to check for the Stationarity of the Series. It was discovered that the series is not stationary, thus the need for differencing to make it stationary. Based on the findings of the study, it was concluded that the ARIMA (0, 2,2) and GARCH (1,1) with Student’s t-distribution are the optimal models for modeling monthly average official exchange rates return (Naira/USD) in Nigeria.
Cited by 0
No indexed citations yet.
Related research
- Time Series and Empirical Orthogonal Transformation Using Meteorological Parameters across the Climatic Zones in Nigeria — shares topic coverage
- India’s Basmati Rice Export Forecasting and Performance: ARIMA Model — shares topic coverage
- Comparison between Different Mustard Yield Prediction Models Developed using Various Techniques for Udaipur Region of Rajasthan — shares topic coverage
- Trajectory of COVID-19 Data in India: Investigation and Project Using Artificial Neural Network, Fuzzy Time Series and ARIMA Models — shares topic coverage
- Modeling Temporal Variation of Particulate Matter Concentration at Three Different Locations of Delhi — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
0
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.