Timeseries Analysis of All Shares Index of Nigerian Stock Exchange: A Box-Jenkins Approach

Author(s): C. A. Uzuke, H. O. 0biora-Ilouno, Eze F. C, J. Daniel

This study was aimed at analyzing the Nigerian Stock Exchange All Share Index. The data was extracted from the Central Bank of Nigeria’s Statistical Bulletin and it covered the period of January 1985 to September 2014. The Box and Jenkins approach of model identification, parameter estimation and diagnostic checking was adopted in the analysis with the aid of S-plus Package. From the analysis, the result revealed that Autoregressive model of order two AR (2) after differencing once gives Akaike Information Criteria (AIC) of 6682.4416 which is an optimal order for Nigeria Stock Exchange All Share Index, the model is ... . Therefore, the model generated shows that ARIMA (2, 1, 0) is adequate to define the optimal order of Nigerian Stock Exchange All Share index.

Autocorrelation, Partial Autocorrelation, Autoregresive Integrated Moving Average (ARIMA), Autoregresive Moving Average (ARMA), Autoregresive (AR), Moving Average (MA), Differencing, All Share Index, Stationary Series

1. Abdul A. (2008). Implications of the random walk hypothesis for portfolio management. Fin. Anal. Journal, 27: 16-22.
2. Agwuegbo, S.O.N, Adewole, A.P and Maduegbuna, A. N (2010). A Random Walk for Stock Market Prices. Journal of Mathematics and Statistics, Science Publications, 6(3): 342-346.
3. Bluestone N. A. (2006). A Simple Neural Network for ARMA (p, q) Time series, OMEGA: Internal Journal of Management Science, Vol. 29, pp 319-333.
4. Box, G.E.P., Jenkins, G.M., and Reinsel, G.C (1994). Time series analysis, forecasting and control, 3rd edn. Englewood Cliffs, N.J, Prentice Hall.
5. Central Bank of Nigeria (2014). Central Bank of Nigeria Statistical Bulletin Vol. 305.
6. Chatfield, C. (2004). The analysis of time series, An introduction, 6th ed., Chapman and Hall/CRC, Boca Raton.
7. Durbin J. (2012) Time Series Analysis by State Space Methods. Oxford Statistical Science Series Oxford University Press
8. Leuthold et.al (2000). A Random Walk Down Wall Street. W.W. Norton and Company, 6th Edition.
9. Lirby A. D. (2004). Predicting the Stock Market. Technical Report Series IMa-TOM-1997-2007. Malardalen University, Vasteras, Sweden.
10. Malkiel F. O. (2013). Stock Return Predictability and Model Uncertainty. Journal of Financial Economics, Vol. 64.
11. Naylor et al (2012). Time Series Analysis: Univariate and Multivariate Methods, Addison-Wesley Redwood City, CA
12. Senol, A. (2012). The stock market and economic efficiency, New York; Fordham University Press.