TITLE:
A Multiplicative Seasonal ARIMA/GARCH Model in EVN Traffic Prediction
AUTHORS:
Quang Thanh Tran, Zhihua Ma, Hengchao Li, Li Hao, Quang Khai Trinh
KEYWORDS:
Traffic Prediction, ARIMA, GARCH, Multiplicative Seasonal ARIMA/GARCH, EViews
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.8 No.4,
April
2,
2015
ABSTRACT: This paper highlights the statistical
procedure used in developing models that have the ability of capturing and forecasting
the traffic of mobile communication network operating in Vietnam. To build such
models, we follow Box-Jenkins method to construct a multiplicative seasonal
ARIMA model to represent the mean component using the past values of traffic,
then incorporate a GARCH model to represent its volatility. The traffic is
collected from EVN Telecom mobile communication network. Diagnostic tests and
examination of forecast accuracy measures indicate that the multiplicative
seasonal ARIMA/GARCH model, i.e. ARIMA (1, 0, 1) × (0, 1, 1)24/GARCH (1, 1)
shows a good estimation when dealing with volatility clustering in the data
series. This model can be considered to be a flexible model to capture well the
characteristics of EVN traffic series and give reasonable forecasting results.
Moreover, in such situations that the volatility is not necessary to be taken
into account, i.e. short-term prediction, the multiplicative seasonal
ARIMA/GARCH model still acts well with the GARCH parameters adjusted to GARCH (0,
0).