Abstract
Risk analysis of the crude oil market has always been a core research problem important to both practitioners and academia. Risks arise primarily from changes in oil prices. During the 1970s and 1980s there were a number of steep increases in oil prices; these price fluctuations reached new peaks in 2007 when the price of crude oil doubled during the financial crisis, and double digit fluctuations continued between 2007 and 2008 for short periods. These fluctuations would not be worrisome if oil was not such an important commodity in the world’s economy. But when oil prices become too high and their volatility increases, they have a direct impact on the economy in general, and affect the government decisions regarding market regulation, thus impacting firm and individual consumer incomes.1
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J.C. Hung, M.C. Lee, H.C. Liu (2008) ‘Estimation of value-at-risk for energy commodities via fat-tailed GARCH models,’ Energy Economics, 30 (3): 1173–1191.
P.K. Narayan, S. Narayan, A. Prasad (2008) ‘Understanding the oil price-exchange rate nexus for the Fiji islands,’ Energy Economics, 30 (5): 2686–2696.
F. Malik, B.T. Ewing (2009) ‘Volatility transmission between oil prices and equity sector returns,’ International Review of Financial Analysis, 18 (3): 95–100.
A.H. Alizadeh, N.K. Nomikos, P.K. Pouliasis (2008) ‘A Markov regime switching approach for hedging energy commodities,’ Journal of Banking & Finance, 32 (9): 1970–1983.
C. Aloui, R. Jammazi (2009) ‘The effects of crude oil shocks on stock market shifts behaviour: a regime switching approach,’ Energy Economics, 31 (5): 789–799.
F. Klaassen (2002) ‘Improving GARCH volatility forecasts with regime-switching GARCH,’ Empirical Economics, 27: 363–394.
A. Cologni, M. Manera (2009) ‘The asymmetric effects of oil shocks on output growth: a Markov-Switching analysis for the G-7 countries,’ Economic Modelling, 26 (1): 1–29.
Y. Fan, Y.J. Zhang, H.T. Tsaic, Y.M. Wei (2008) ‘Estimating ‘Value at Risk’ of crude oil price and its spillover effect using the GED-GARCH approach,’ Technological Change and the Environment, 30 (6): 3156–3171.
C. Aloui, S. Mabrouk (2009) ‘Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models,’ Energy Policy, 38 (5): 2326–2339.
P. Agnolucci (2009) ‘Volatility in crude oil futures: a comparison of the predictive ability of GARCH and implied volatility models,’ Energy Economics, 31 (2): 316–321.
C. Engel (1994) ‘Can the Markov switching model forecast exchange rates?’ Journal of International Economics, 36(1): 151–165.
M.T. Vo (2009) ‘Regime-switching stochastic volatility: evidence from the crude oil market,’ Energy Economics, 31 (5): 779–788.
E. Fama (1970) ‘Efficient capital markets: a review of theory and empirical work,’ Journal of Finance, 25: 383–417.
R.F. Engle (1982) ‘Autoregressive conditional heteroscedasticity with estimates of variance of United Kingdom inflation,’ Econometrica, 50: 987–1008.
T. Bollerslev (1986) ‘Generalized autoregressive conditional heteroskedasticity,’ Journal of Econometrics, 31: 307–327.
D.B. Nelson (1991) ‘Conditional heteroskedasticity in asset returns: a new approach,’ Econometrica, 59: 347–370.
J.E. Raymond, R.W. Rich (1997) ‘Oil and the macroeconomy: a Markov state-switching approach,’ Journal of Money, Credit and Banking, 29 (2): 193–213.
J.D. Hamilton (1989) ‘A new approach to the economic analysis of nonstationary time series and the business cycle,’ Econometrica, 57 (2): 357–384.
D. Cousineau, S. Brown, A. Heathcote (2004) ‘Fitting distributions using maximum likelihood: methods and packages,’ Behavior Research Methods, Instruments, & Computers, 36: 742–756.
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© 2015 Desheng Dash Wu and David L. Olson
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Wu, D.D., Olson, D.L. (2015). Volatility Forecasting of the Crude Oil Market. In: Enterprise Risk Management in Finance. Palgrave Macmillan, London. https://doi.org/10.1057/9781137466297_19
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DOI: https://doi.org/10.1057/9781137466297_19
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