Open Access
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 72, Number 1, January–February 2017
Article Number 3
Number of page(s) 10
Published online 02 February 2017
  • Baek E., Brock W. (1992) A general test for nonlinear Granger causality: bivariate model, Working paper, Iowa State University and University of Wisconsin, Madison. [Google Scholar]
  • Bampinas G., Panagiotidis T. (2015) On the relationship between oil and gold before and after financial crisis: linear, nonlinear and time-varying causality testing, Working paper, WP 15-04, The Rimini Centre for Economic Analysis, Italy. [Google Scholar]
  • Bollerslev T. (1986) Generalized autoregressive conditional heteroskedasticity, J. Econom. 31, 307–327. [Google Scholar]
  • Bredin D., Elder J., Fountas S. (2011) Oil volatility and the option value of waiting: an analysis of the G-7, J. Fut. Mark. 31, 679–702. [CrossRef] [Google Scholar]
  • Chatrath A., Miao H., Ramchander S., Wang T. (2015) The forecasting efficacy of risk-neutral moments for crude oil volatility, J. Forecast. 34, 177–190. [CrossRef] [MathSciNet] [Google Scholar]
  • Dave D., Aye G.C. (2015) Oil price uncertainty and Savings in South Africa, OPEC Energy Review 39, 285–297. [CrossRef] [Google Scholar]
  • Dées S., Gasteuil A., Kaufmann R., Mann M. (2008) Assessing the factors behind oil price changes, Working paper No. 855, European Central Bank. [Google Scholar]
  • Duffie D., Gray S. (1995) Volatility in energy prices, in Managing energy price risk, Jamson R. (ed.), Risk Publications, London, pp. 39–55. [Google Scholar]
  • Elder J., Serletis A. (2010) Oil price uncertainty, J. Money, Credit Bank. 42, 1138–1159. [CrossRef] [Google Scholar]
  • Engle R.F., Granger C.W.J. (1987) Co-integration and error-correction: representation, estimation and testing, Econometrica 55, 251–276. [CrossRef] [MathSciNet] [Google Scholar]
  • Engle R.F. (1982) Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation, Econometrica 50, 987–1007. [Google Scholar]
  • Ewing B.T., Hammoudeh S.M., Thompson M.A. (2006) Examining asymmetric behavior in US petroleum futures and spot prices, Energy J. 27, 9–23. [CrossRef] [Google Scholar]
  • Fattouh B. (2007) Structural model, the demand-supply framework and informal approaches, University of London, London, UK. [Google Scholar]
  • Figlewski S. (1997) Forecasting volatility, Financ. Mark. Inst. Instrum. 6, 2, 1–88. [CrossRef] [Google Scholar]
  • Garefalakis A., Dimitras A., Koemtzopoulos D., Spinthiropoulos K. (2011) Determinant factors of Hong Kong stock market, Inter. J. of Fin. Mar. and Der. 62, 50–64. [Google Scholar]
  • Granger C. (1999) Empirical modeling in economics, Cambridge University Press, UK. [CrossRef] [Google Scholar]
  • Guo H., Kliensen K. (2005) Oil price volatility and US macroeconomic activity, Fed. Res. Bank of St. Louis Rev. 87, 6, 669–683. [Google Scholar]
  • Hiemstra C., Jones J. (1994) Testing for linear and nonlinear Granger causality in the stock price-volume relation, J. Finance 49, 1639–1664. [Google Scholar]
  • Jo S. (2014) The effects of oil price uncertainty on global real economic activity, J. Money, Credit Bank. 46, 1113–1135. [CrossRef] [Google Scholar]
  • Kaufmann R. (2011) The role of market fundamentals and speculation in recent price changes for crude oil, Energy Policy 39, 105–115. [CrossRef] [Google Scholar]
  • Kaufmann R., Ullman B. (2009) Oil prices, speculation and fundamentals: interpreting causal relationship among spot and futures prices, Energy Econ. 31, 550–558. [CrossRef] [Google Scholar]
  • Kuper G. (2002) Measuring oil price volatility, Department of Economics & SOM, University of Groningen, The Netherlands. [Google Scholar]
  • Lemonakis C., Vassakis K., Garefalakis A., Papa P. (2016a) SMEs performance and subsidies in it investments: a vis-à-vis approach, J. of Theor. and App. Infor. Tech. 87, 2, 266–275. [Google Scholar]
  • Lemonakis C., Vassakis K., Garefalakis A., Michailidou D. (2016b) Cooperations characteristics for potential innovative in crisis: the Greek paradigm, Corp. Owner. and Control 14, 1, 30–37. [Google Scholar]
  • Matar W., Al-Fattah S.M., Atalla T., Pierru A. (2013) An introduction to oil market volatility analysis, OPEC Energy Rev. 37, 3, 247–269. [CrossRef] [Google Scholar]
  • Pindyck R.S. (2004) Volatility and commodity price dynamics, J. Fut. Mark. 24, 1029–1047. [CrossRef] [Google Scholar]
  • Plourde A., Watkins G.C. (1998) Crude oil prices between 1985 and 1994: how volatile in relation to other commodities? Resour. Energy Econ. 20, 245–262. [CrossRef] [Google Scholar]
  • Poon S.-H., Granger C.W.J. (2003) Forecasting volatility in financial markets: a review, J. Econ. Lit. 41, 2, 478–539. [CrossRef] [Google Scholar]
  • Robe M.A., Wallen J. (2016) Fundamentals, derivatives market information and oil price volatility, J. Futures Mark. 36, 317–344. [CrossRef] [Google Scholar]
  • Romano A.A., Scandurra G. (2012) Price asymmetries and volatility in the Italian gasoline market, OPEC Energy Rev. 36, 215–229. [CrossRef] [Google Scholar]
  • Salisu A.A. (2014) Modeling oil price volatility before, during and after the global financial crisis, OPEC Energy Rev. 38, 469–495. [CrossRef] [Google Scholar]
  • Salisu A., Fasanya I. (2012) Modelling oil price volatility with structural breaks, Energy Policy 52, 554–562. [CrossRef] [Google Scholar]
  • Sariannidis N., Galyfianakis G., Drimpetas E. (2015) The effect of financial and macroeconomic factors on the oil market, Inter. J. of Ener. Econ. and Pol. 5, 4, 1084–1091. [Google Scholar]
  • Sariannidis N., Koskosas I., Garefalakis A., Antoniadis I. (2009) Volatility of stock returns: the case of the Belgian Stock Exchange, Inter. J. of Bus. For. and Mark. Intel. 1, 111–121. [Google Scholar]
  • Sharma H., Dharmaraja S. (2016) Effect of outliers on volatility forecasting and value at risk estimation in crude oil markets, OPEC Energy Rev. 40, 276–299. [CrossRef] [Google Scholar]
  • Zhang Y.-J., Wei Y.-M. (2010) The crude oil market and the gold market: evidence for co-integration, causality and price discovery, Resour. Policy 35, 3, 168–177. [CrossRef] [Google Scholar]

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