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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 5 Issue 9 pp. 873-882 , 2015

Multivariate FIGARCH and long memory process: evidence of oil price markets Pages 873-882 Right click to download the paper Download PDF

Authors: Nadhem Selmi, Nejib Hachicha

DOI: 10.5267/j.msl.2015.6.009

Keywords: ARFIMA, FIGARCH, MGARCH-DCC, Oil price

Abstract: Oil price markets can benefit from a better considerate of how shocks can affect volatility through time. This study assesses the impact of structural changes and outliers on volatility persistence of two crude oil markets WTI and Brent oil price between January 1, 1996 and March 17, 2014. First, we identify the FIGARCH process proposed by Baillie et al. (1996) [Baillie, R.T., Bollerslev, T., & Mikkelsen, H.O., (1996), Fractionally integrated generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 74, 3-30.] and investigate some of its statistical proprieties and then incorporate this information into the volatility modelling. We also show that outliers can bias the estimation of the persistence of the volatility. Taking into account outliers on the volatility modelling process improve the understanding of volatility in crude oil markets.

How to cite this paper
Selmi, N & Hachicha, N. (2015). Multivariate FIGARCH and long memory process: evidence of oil price markets.Management Science Letters , 5(9), 873-882.

Refrences
Askari, H., & Khrichene, N. (2008). Oil price dynamics (2002-2006). Energy Economics, 30, 2134-2153.

Baba, Y., Engle, R.F. Kraft, D.F. & Kroner, K.F. (1989). Multivariate simultaneous generalized ARCH. Department of Economics, University of California, San Diego., Discussion paper 89-57.

Baillie, R. T., Bollerslev, T., & Mikkelsen, H. O. (1996). Fractionally integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 74(1), 3-30.

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.

Breidt, F. J., Crato, N., & De Lima, P. (1998). The detection and estimation of long memory in stochastic volatility. Journal of Econometrics, 83(1), 325-348.

Broner, F., & Gelos, G. (2003). Testing the portfolio channel of contagion: the role of risk aversion. Universitat Pompeu-Fabr.

Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models.Journal of Business & Economic Statistics, 20(3), 339-350.

Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 50(4), 987-1007.

Hosking, J. (1981). Fractional Differencing. Biometrika, 68(1), 165-167.

Huang, Y.C., Li, C., & Ma, W.F. (2005). The dilemma and outlet of China & apos; s oil price risk management. World Economy Study, 10, 22-26.

Granger, C.W.J, & Joyeux, R. (1980). An introduction to long memory time series models and fractional differencing. Journal of Time Series Analysis, 1(1), 15-29.

Kaminsky, G. L., & Reinhart, C. M. (1999). The twin crises: the causes of banking and balance-of-payments problems. American Economic Review, 89(3), 473-500.

Kaminsky, G. L., & Reinhart, C. M. (2000). On crises, contagion, and confusion. Journal of International Economics, 51(1), 145-168.

Larsson, K. & Nossman, M. (2011). Jumps and stochastic volatility in oil prices: Time series evidence. Energy Economics, 33, 504-514.

Li, P.M., Jia, M., & Zhang, G.Y. (2005). China & apos; s strategies for the high oil price. Macroeconomics. 12, 8-14 (in Chinese).

Sans?, A., Arag?, V., & Carrion, J. L. (2004). Testing for changes in the unconditional variance of financial time series. Revista de Econom?a financiera,4, 32-53.

Shiller, R. J. (2000). Measuring bubble expectations and investor confidence.The Journal of Psychology and Financial Markets, 1(1), 49-60.
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Journal: Management Science Letters | Year: 2015 | Volume: 5 | Issue: 9 | Views: 2115 | Reviews: 0

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