A Time Series Analysis of Nigeria All Share Index (1985-2018) Buys-Ballot Methodology

D. Enegesele¹ , O.A.P ² , Otaru ³

Section:Research Paper, Product Type: Journal-Paper
Vol.6 , Issue.5 , pp.91-98, Oct-2019

Online published on Oct 31, 2019

Copyright © D. Enegesele, O.A.P, Otaru . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Classical time-series analysis is the decomposition of time-series into components due to seasonal variation, trend, cyclic variation and irregular fluctuations. A good knowledge of this method is necessary because most real life data are not normally distributed hence most analyst are faced with the problem of choice of appropriate transformation, choice of model for decomposition and difficulty to determine the presence of seasonal effect in a series to achieve unbiased decision. Thus, the study aims to identify the best transformation for modeling of Nigeria All Share Index (ASI), an appropriate choice of model for decomposition, the seasonal effect as well as trend pattern of Nigeria All Share Index (ASI). The study applied Buys-Ballot methodology to assess the characteristics of ASI. Evidence of the result showed that logarithm transformation is best suitable for ASI series and multiplication model is the appropriate model for decomposition. Also, result revealed that ASI contains seasonal effect and quadratic trend curve best fit ASI with p<0.05 and coefficient of determination of 0.974. We therefore recommend that appropriate transformation approach should be used to obtain stability of the variance of time series data and care should be taken in the choice of appropriate model for decomposition

Key-Words / Index Term :
Normality, Buys-Ballot, Transformation, Model, Trend, Seasonal, Decomposition

References :
[1] M.S. Bartlett, “The Uses of Transformation”, Biometrika, Vol3, pp. 39-52, 1947.
[2] G.E.P Box, G.M,Jenkins, “Time Series Analysis: Forecasting and Control”, Holden-Day, San Francisco, 1976.
[3] G.E.P Box, G. M Jenkins, G. C, Reinsel, “Time Series Analysis, Forecasting and Control”, 3rd Edition, Prentice-Hall, 1994.
[4] C. Chatfield, “The Analysis of Time Series: An Introduction”, Chapman and Hall/CRC Press, Boca Raton, 2004.
[5] I.S.Iwueze, A.C. Akpanta, “On Applying the Bartlett Transformation Method to Time Series Data”, Journal of Applied Mathematics, Vol 2, pp. 633-645, 2009.
[6] I. S. Iwueze, E. C. Nwogu, “Buys-Ballot Estimates for Time Series Decomposition”, Global Journal of Mathematics, Vol. 3 No. 2, pp 83-98, 2004.
[7] I.S., Iwueze, E.C. Nwogu, J. Ohakwe, J.C. Ajaraogu, “Uses of the Buys-Ballot Table in Time Series Analysis”, Applied Mathematics, pp 633-645, 2011.
[8] E.F. Fama, “Efficient Capital Markets: A Review of Theory and Empirical Work”,Journal of Finance,Vol. 25,pp.383-417. 1970.
[9] T. F. Gosnell,A. J. Keown, J. M. Pinkerton, “The Intraday Speed of Stock Price Adjustment to MajorDividend Changes: Bid-Ask Bounce and Order Flow Imbalances”,Journal of Banking and Finance, Vol.20, pp.247-266. 1996.
[10] J. Patell, M. Wolfson, “The Intraday Speed of Adjustment of Stock Prices to Earnings and Dividend Announcements”, Journal of Financial Economics, Vol. 13,pp 223-252. 1984.
[11] N. Seyhun,“Insiders’ Profits, Cost of Trading and market Efficient”, Journal of Financial Economics,Vol.16, pp.189-212. 1986
[12] M. A. Adebiyi, “Capital Market Performance and the Nigerian Economic Growth Management in Nigeria Lagos”: University Press. 2005
[13] O. Ajakaiye, T. Fakiyesi, “Global Financial Crisis Discussion Series Paper 8: Nigeria”, Overseas Development Institute London. 2009
[14] N. G. Mankiw,“Macro Economics”, 4th Edition, , UK: Macmillan Press Ltd.pp.472 1999.
[15] A.O. Ologunde, D.O. Elumilade, T. O. Asaolu, “Stock Market Capitalization and Interest Rate in Nigeria: A Time Series Analysis”, International Research Journal of Finance and Economics, Issue 4, pp.154-166. 2006
[16] H. Alile, “Government must Divest”,The Business Concord of Nigeria 2nd December, pp.8.1997
[17] C.O.Mgbame,O.J.Ikhatua, “Accounting Information and Stock Volatility in the Nigerian Capital Market: A Garch Analysis Approach”, International Review of Management and Business Research, Vol 2, No 1, pp. 265 – 281. 2013
[18] D. Aurangzeb, “Factors Affecting Performance of Stock Market: Evidence from South Asian Countries”,International Journal of Academic Research in Business and Social Sciences, Vol 2, No. 9, pp.1-15.2012.
[19] N. Okereke-Onyuike, “Strategies for Stock Market Recovery”, A Paper presented to the Ad-hoc Committee of the House of Representatives during the Capital Market Probe. Business World, pp.14-21. 2012.
[20] CBN, Central Bank of Nigeria Statistical Bulletin, Various Issues. Abuja: Central bank of Nigeria Publication (CBN). 2017.
[21] W.W.W Wei, “Time Series Analysis, Univariate and Multivariate Methods”, Addison- Wesley, Redwood City, 1989.
[22] H.Wold, “A study in the Analysis of Stationary Time Series”. 2nd Edition, Stockholm: Almqrist and witsett, 1938.