FORECASTING VOLATILITY OF OIL PRICES & THEIR EFFECT ON THE ECONOMY

With the importance of crude oil and its effect on the macro and micro economy alike and with the fluctuations of oil prices mainly due to geopolitical reasons -speculators taking this advantage in raising the prices in 2008; forecasting crude oil volatility becomes vital. This project addresses three main areas: modelling volatility, forecasting and calculating options premiums and finally examining the effect of oil prices on the economy. Five year daily prices of OPEC, being the reference to oil prices, Brent being one of the main oil markets, BP.plc as one of the giant oil companies, and S&P500 being the important market index are obtained from different approved resources. Auto Regressive Conditional Heteroskedasticity series proved, as examined by vast number of studies in the literature reviewed; to be better in forecasting volatility in time series. GARCH and EGARCH are estimated under normality using random walk with drift for a better fit. Upon choosing the optimal models according to the Akaike and Schwartz Information Criteria; EGARCH(1,2) is of better fit to volatility for OPEC containing recent shocks to the prices, yet GARCH(1,2) and GARCH(5,4) provided almost similar results. EGARCH(1,1) proves to be yet another good model for both modelling and forecasting volatility of Brent crude returns by covering the asymmetry and the leverage effects. Options premiums calculated of 31-day forecast period using Black-Scholes model show different outcome to that obtained from Bloomberg implying the attraction of more investors to buy more profitable options since higher risk leads to higher profits. By performing the Johansen cointegration method, it is evident that oil price fluctuations have longer term relationship between OPEC and BP than between OPEC and S&P500 yet all three are in equilibrium portraying for more downturn in the economy.