Browsing by Author "Gil-Alana, L. A."

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Fractional integration and structural breaks in bank share prices in Nigeria
(Elsevier, 2015) Gil-Alana, L. A.; Yaya, O.S.; Adepoju, A. A.
The paper employs both fractional integration and structural break techniques in studying the daily share prices structure of the banking sector in Nigeria. Our data span between 2001 and 2012, covers periods before and after the global financial crisis. The results obtained using both parametric and semi parametric methods indicate little evidence of mean reversion since most of the orders of integration are equal to or higher than1. Long memory is found in the absolute and squared return series. The possibility of structural breaks is also taken into account and the results show a different number of breaks depending on the bank examined. In general, an increase in the degree of dependence across time is noticed, and the most common break took place in December 2008, probably being related with the world financial crisis affecting also the banking system in Nigeria
Time series analysis of quarterly rainfall and temperature (1900–2012) in sub-Saharan African countries
(Springer Nature, 2018) Gil-Alana, L. A.; Yaya, O. S.; Fagbamigbe, A. F.
In this paper, we examine the statistical properties of rainfall data and temperature in six sub-Saharan African countries in the western, eastern, and southern regions (Botswana, Ethiopia, Ghana, Nigeria, Uganda, and South Africa) using time series data spanning between 1900 and 2012. By using linear trends, seasonality, and long-range dependence models, in fractional or I(d) frameworks, the results first indicate that time trends are required in most cases to explain the time series properties of the climatic series. Evidence of anti-persistence (d < 0) or I(0) behavior is found for the rainfall data, while long memory (d > 0) is found for the temperature data. Evidence of structural breaks are only found in the cases of Ethiopia, Ghana, and Uganda for the temper[1]ature data. With both series displaying significant evidence of seasonality and by working with the seasonally differenced data, the results show evidence of I(0) behavior or anti-persistence (d < 0) for the rainfall data but long memory (d > 0) for the temperature data. Testing the causality between the two variables, the results indicate evidence of causality in the two directions in all cases except for the case of the temperature on the rainfall in South Africa. The implication of the results obtained here is that erratic or constant rainfall is expected in Africa in the future while temperature is likely to continue to increase, and these subsequently lead to future warming experiences.