Browsing by Author "Yaya, O. S."

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Estimation of garch models for Nigerian exchange rates under non-gaussian innovations
(2013) Adepoju, A. A.; Yaya, O. S.; Ojo, O. O.
Financial series often displays evidence of leptokurticity and in that case, the empirical distribution often fails normality. GARCH models were initially based on normality assumption but estimated model based on this assumption cannot capture all the degree of leptokurticity in the return series. In this paper, we applied variants of GARCH models under non-normal innovations-t-distribution and Generalized Error Distribution (GED) on selected Nigeria exchange rates. The Berndt, Hall, Hall, Hausman (BHHH) numerical derivatives applied in the estimation of models converged faster and the time varied significantly across models. Asymmetric GARCH model with t-distribution (GARCH-t) was selected in most of the cases whereas for Nigeria-US Dollar exchange rate, GARCH-GED was specified. Both distributions showed evidence of leptokurticity in Naira exchange rate return series. The result is of practical importance to practitioners
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.
Volatility persistence and returns spillovers between oil and gold Prices: analysis before and after the global financial crisis
(Elsevier Ltd, 2016) Yaya, O. S.; Tumala, M. T.; Udomboso, C. G.
This paper investigated volatility persistence and returns spillovers between oil and gold markets using daily historical data from 1986 to 2015 partitioned into periods before the global crisis and after the crisis. The log-returns, absolute and squared log-returns series of these asset prices were used as proxy variables to investigate volatility persistence using the fractional persistence approach. The Constant Conditional Correlation (CCC) modelling framework was applied to investigate the spill over effects between the asset returns. The volatility in the gold market was found t be less than that at the oil market before and after the crisis periods. The returns spill over effect was bid irectional before the crisis period while it was unidirectional from gold to oil market after the crisis. The fact that there was no returns spill over running from oil to gold after the crisis suggested a measure of optimumal location weights and hedge ratio. The results obtained are of practical implications for port folio managers and decision managers in these two ways: gold market should be used as a hedge against oil price inflationary shocks; and the volatility at the oil market can be used to determine the behaviour of gold market.