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What causes price volatility and regime shifts in the natural gas market

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  • Lin, Boqiang
  • Wesseh, Presley K.

Abstract

Gas sector volatility is of interest because it affects decisions made by producers and consumers and also influences investors' decision in gas-related investments, portfolio allocation and risk management. This paper therefore attempts to explain the behavior of natural gas index returns and in so doing proposes application of a pure Markov-switching volatility model whose variance is subject to shift in regime. We show that regime-switching is clearly present in the natural gas market and such should not be ignored. All ARCH effects that show up in weekly natural gas index returns data die out almost completely after allowing for Markov-switching variance. Volatility regimes identified by our model correlate well with major events affecting supply and demand for natural gas. Out-of-sample tests indicate that the regime switching model performs noticeably better than a wide range of volatility models considered regardless of evaluation criteria, thus providing a better framework for the policy maker or financial historian interested in studying factors behind the evolution of volatility and to natural gas futures traders interested in short-term volatility forecasts. As risk-hedging decisions rely critically on assumptions about volatility, policies based on the transition probabilities are likely to be more conservative.

Suggested Citation

  • Lin, Boqiang & Wesseh, Presley K., 2013. "What causes price volatility and regime shifts in the natural gas market," Energy, Elsevier, vol. 55(C), pages 553-563.
  • Handle: RePEc:eee:energy:v:55:y:2013:i:c:p:553-563
    DOI: 10.1016/j.energy.2013.03.082
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    as
    1. Brandt, Adam R. & Plevin, Richard J. & Farrell, Alexander E., 2010. "Dynamics of the oil transition: Modeling capacity, depletion, and emissions," Energy, Elsevier, vol. 35(7), pages 2852-2860.
    2. Jammazi, Rania, 2012. "Cross dynamics of oil-stock interactions: A redundant wavelet analysis," Energy, Elsevier, vol. 44(1), pages 750-777.
    3. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    4. Danielsson, Jon, 1994. "Stochastic volatility in asset prices estimation with simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 375-400.
    5. Garcia, Rene & Perron, Pierre, 1996. "An Analysis of the Real Interest Rate under Regime Shifts," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 111-125, February.
    6. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.
    7. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    8. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    9. Fong, Wai Mun & See, Kim Hock, 2002. "A Markov switching model of the conditional volatility of crude oil futures prices," Energy Economics, Elsevier, vol. 24(1), pages 71-95, January.
    10. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
    11. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    12. Shiller, Robert J, 1981. "The Use of Volatility Measures in Assessing Market Efficiency," Journal of Finance, American Finance Association, vol. 36(2), pages 291-304, May.
    13. Smith, Daniel R, 2002. "Markov-Switching and Stochastic Volatility Diffusion Models of Short-Term Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 183-197, April.
    14. Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
    15. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    16. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    17. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    18. Sadeghi, Mehdi & Shavvalpour, Saeed, 2006. "Energy risk management and value at risk modeling," Energy Policy, Elsevier, vol. 34(18), pages 3367-3373, December.
    19. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    20. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
    21. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
    22. Zhang, Chuanguo & Chen, Xiaoqing, 2011. "The impact of global oil price shocks on China’s stock returns: Evidence from the ARJI(-ht)-EGARCH model," Energy, Elsevier, vol. 36(11), pages 6627-6633.
    23. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    24. Fornari, Fabio & Mele, Antonio, 1997. "Sign- and Volatility-Switching ARCH Models: Theory and Applications to International Stock Markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 49-65, Jan.-Feb..
    25. Wesseh, Presley K. & Zoumara, Babette, 2012. "Causal independence between energy consumption and economic growth in Liberia: Evidence from a non-parametric bootstrapped causality test," Energy Policy, Elsevier, vol. 50(C), pages 518-527.
    26. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    27. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
    28. Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
    29. Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
    30. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    31. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    32. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    33. Robert E. McCulloch & Ruey S. Tsay, 1994. "Statistical Analysis Of Economic Time Series Via Markov Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(5), pages 523-539, September.
    34. Fornari, Fabio & Mele, Antonio, 1996. "Modeling the changing asymmetry of conditional variances," Economics Letters, Elsevier, vol. 50(2), pages 197-203, February.
    35. Brooks, Chris & Burke, Simon P., 1998. "Forecasting exchange rate volatility using conditional variance models selected by information criteria," Economics Letters, Elsevier, vol. 61(3), pages 273-278, December.
    36. Arouri, Mohamed El Hedi & Jouini, Jamel & Nguyen, Duc Khuong, 2012. "On the impacts of oil price fluctuations on European equity markets: Volatility spillover and hedging effectiveness," Energy Economics, Elsevier, vol. 34(2), pages 611-617.
    37. Enrique Sentana, 1995. "Quadratic ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 62(4), pages 639-661.
    38. Cao, C Q & Tsay, R S, 1992. "Nonlinear Time-Series Analysis of Stock Volatilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 165-185, Suppl. De.
    39. Zhuliang Chen & Peter Forsyth, 2010. "Implications of a regime-switching model on natural gas storage valuation and optimal operation," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 159-176.
    40. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    41. Chang, Ting-Huan & Su, Hsin-Mei, 2010. "The substitutive effect of biofuels on fossil fuels in the lower and higher crude oil price periods," Energy, Elsevier, vol. 35(7), pages 2807-2813.
    42. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    43. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    44. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    45. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    46. Gallo, Andres & Mason, Paul & Shapiro, Steve & Fabritius, Michael, 2010. "What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price," Energy, Elsevier, vol. 35(10), pages 4126-4141.
    47. Hou, Aijun & Suardi, Sandy, 2012. "A nonparametric GARCH model of crude oil price return volatility," Energy Economics, Elsevier, vol. 34(2), pages 618-626.
    48. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
    49. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
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