@article{MAKHILLJMMS202115128219,
    title = {Box-Jerkins Approach to Fuel Prices and Currency Strength in the International Market},
    journal = {Journal of Modern Mathematics and Statistics},
    volume = {15},
    number = {1},
    pages = {8-15},
    year = {2021},
    issn = {1994-5388},
    doi = {jmmstat.2021.8.15},
    url = {https://makhillpublications.co/view-article.php?issn=1994-5388&doi=jmmstat.2021.8.15},
    author = {Matthew and},
    keywords = {Box-Jerkins,fuel prices,exchange rate,stationarity test,AutoRegressive Integrated Moving Average,mathematical modeling,time series},
    abstract = {South African economy has been said to be
fuel price dependent and that the fuel price keeps
increasing on yearly basis. Thus, there is a need to
develop a scientific model to predict the behaviour and
future values of fuel prices and exchange rates. This study
employs an Autoregressive Integrated Moving Average
(ARIMA) in predicting the fuel prices and the strength of
the South African rand in the international market based
on the 35 years monthly data. The prices of fuel exhibit an
upward trend variation. Among the competing models
estimated per each variable, ARIMA (3, 1, 1), ARIMA (3,
1, 1), ARIMA (1, 1, 2) and ARIMA (1, 0, 1) are
respectively found to be the best for modeling and
predicting the behaviour and future values of diesel,
paraffin, petrol and exchange rate (ZAD-USD). Their
respective forecasting accuracy are 93.4, 91.7, 91.5 and
79.3%, respectively. Hence, predicting the future values
of fuel prices and the strength of South African currency
against the United States of America dollars using these
models will help the policymakers and all stakeholders
make well-informed decisions in planning. Further
research can be carried out on the short and long-run
relationship between the four variables. Also, the
direction of causality among the variables should be
looked into to determine which variable can be used to
determine the future values of the other.}
    }