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Home  >  Volume 35

On Modelling Daily Share Price Data in Nigeria using ARIMA Modelling Approach by Osemwenkhae J. E. and Eguasa E. B.(pages 185-192)
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Abstract

The aim of this work is to develop a time series model for the Nigerian Stock Exchange using the daily stock closing price of Okomu Oil Palm Company Plc from Jan. 2010 to Dec. 2014.

We applied the Box-Jenkins autoregressive integrated moving average (ARIMA) modelling methodology. The time plot and the Augmented Dickey-Fuller (ADF) test showed that the time series data was non-stationary but was made stationary by log transformation and differencing once.

Our results revealed that the ARIMA (0,1,1) was best in modelling the data as indicted by the Akaike Information Criterion (AIC). Hence, the ARIMA (0,1,1) is found as the best model for forecasting the Okomu Oil Palm Company share price data.

Keywords:Autoregressive integrated moving average, Augmented Dickey-Fuller, Akaike Information Criterion, Okomu oil palm

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