ANALYSIS OF CRUDE OIL PRICE VOLATILITY IN NIGERIA: A GARCH MODEL APPROACH

Volatility and the risk-return trade off of crude oil or crude oil market participation is essential to National Investment, decision making, marketing, and the determination of the financial strength of Nations among other things. Therefore, this research study was targeted at modeling price volatility and the risk-return related to crude oil export in Nigerian crude oil market using the first order asymmetric and symmetric univariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family model in three distributional assumptions namely, Normal, student’s-t and generalized error distribution. To achieve this target, three objectives with three research questions and two hypotheses were raised for the study. The data for the study was extracted from the Central Bank of Nigeria online statistical database starting from January, 1987 to June, and 2017. The results from the statistical analysis reveal that the markets were optimistic of their investment and other trade related activities. Sequel to that, there were high probabilities of gains than losses. Although, the variables use in these markets were extremely volatiles and shows evidence there exists positive risk first-rated meaning that investments or investors deserved rewards for holding risky assets. In estimation, first order symmetric GARCH model (GARCH, (1,1) in student’s-t error assumption gave a better fit than the first order Asymmetric GARCH model (EGARCH (1,1)) in Normal error distributional assumptions. However, the selected models were subjected to several diagnostic test such as ARCH effect test, test for serial correlation and QQ-plot in order to validate their fitness which was confirmed to be appropriate. And recommendations were made to the Government to look for new ways to diversify the economy from total dependence on oil to non-crude oil such as agriculture, manufacturing and mining sector. For investors or marketers in this markets, they were advice to be mindful in trading in a highly volatile period especially when there is evidence of high standard deviation in the descriptive statistic of the return series and in modeling volatility of price return of certain micro/ macro-economic variable the leverage effect of such variable should be properly estimated using asymmetric GARCH model