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Home  >  Volume 36 (no2)

Hybrid of ARIMA-ARCH Modelling of Daily Share Price Data of Okomu Oil Plc in Nigeria by Osemwenkhae J. E, Eguasa E. B. and Iduseri A.(pages 163-168)
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The aim of this work is to study and develop an appropriate time series model for the residuals from the autoregressive integrated moving average (ARIMA) model derived from the daily stock data of Okomu Oil. 

The autocorrelation structure of the residuals and the squared residuals were examined. The Box-Ljung test, Box-Pierce, and McLeod-Li test were applied to the residuals and squared residuals from the ARIMA model. These tests revealed the presence of conditional variance (volatility) in the residuals from the ARIMA model. The autoregressive conditional heteroscedastic (ARCH) models were then applied in modeling this volatility.

Our results showed that the ARCH (5) model was best (having the smallest AIC) giving rise to a hybrid ARIMA-ARCH model. This model better explains and captures the dynamics of the daily stock price of the company being studied.

Keywords: ARCH, McLeod-Li test, Akaike Information Criterion, volatility, autocorrelation function, Okomu.