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Jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility

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  • Christopher F Baum

    (Boston College
    DIW Berlin)

  • Paola Zerilli

    (Department of Economics and Related Studies, University of York)

Abstract

We evaluate alternative models of the volatility of commodity futures prices based on high-frequency intraday data from the crude oil futures markets for the October 2001-December 2012 period. These models are implemented with a simple GMM estimator that matches sample moments of the realized volatility to the corresponding population moments of the integrated volatility. Models incorporating both stochastic volatility and jumps in the returns series are compared on the basis of the overall fit of the data over the full sample period and subsamples. We also find that jumps in the returns series add to the accuracy of volatility forecasts.

Suggested Citation

  • Christopher F Baum & Paola Zerilli, 2014. "Jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility," Boston College Working Papers in Economics 860, Boston College Department of Economics.
    • Handle: RePEc:boc:bocoec:860
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    References listed on IDEAS

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    1. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    2. Anders B. Trolle & Eduardo S. Schwartz, 2009. "Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4423-4461, November.
    3. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    4. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    5. Pindyck, Robert S, 1991. "Irreversibility, Uncertainty, and Investment," Journal of Economic Literature, American Economic Association, vol. 29(3), pages 1110-1148, September.
    6. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    7. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
    8. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    9. Christiane Baumeister & Lutz Kilian, 2011. "Real-Time Forecasts of the Real Price of Oil," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 326-336, September.
    10. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    11. Jaime Casassus & Pierre Collin‐Dufresne, 2005. "Stochastic Convenience Yield Implied from Commodity Futures and Interest Rates," Journal of Finance, American Finance Association, vol. 60(5), pages 2283-2331, October.
    12. Robert S. Pindyck, 2004. "Volatility and commodity price dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(11), pages 1029-1047, November.
    13. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous‐Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    14. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    15. Bollerslev, Tim & Zhou, Hao, 2002. "Estimating stochastic volatility diffusion using conditional moments of integrated volatility," Journal of Econometrics, Elsevier, vol. 109(1), pages 33-65, July.
    16. Ole E. Barndorff-Nielsen, 2004. "Power and Bipower Variation with Stochastic Volatility and Jumps," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 1-37.
    17. Larsson, Karl & Nossman, Marcus, 2011. "Jumps and stochastic volatility in oil prices: Time series evidence," Energy Economics, Elsevier, vol. 33(3), pages 504-514, May.
    18. Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
    19. Askari, Hossein & Krichene, Noureddine, 2008. "Oil price dynamics (2002-2006)," Energy Economics, Elsevier, vol. 30(5), pages 2134-2153, September.
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    Cited by:

    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Virbickaitė, Audronė & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian predictive distributions of oil returns using mixed data sampling volatility models," Resources Policy, Elsevier, vol. 86(PA).
    3. Weijermars, R. & Sun, Z., 2018. "Regression analysis of historic oil prices: A basis for future mean reversion price scenarios," Global Finance Journal, Elsevier, vol. 35(C), pages 177-201.
    4. Seiji Harikae & James S. Dyer & Tianyang Wang, 2021. "Valuing Real Options in the Volatile Real World," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 171-189, January.
    5. Laurini, Márcio Poletti & Mauad, Roberto Baltieri & Aiube, Fernando Antônio Lucena, 2020. "The impact of co-jumps in the oil sector," Research in International Business and Finance, Elsevier, vol. 52(C).
    6. Rangan Gupta & Chi Keung Marco Lau & Seong-Min Yoon, 2019. "OPEC News Announcement Effect on Volatility in the Crude Oil Market: A Reconsideration," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(4), pages 1-23, December.
    7. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    8. Baum, Christopher F. & Zerilli, Paola & Chen, Liyuan, 2021. "Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data," Energy Economics, Elsevier, vol. 93(C).
    9. Bonaccolto, G. & Caporin, M. & Gupta, R., 2018. "The dynamic impact of uncertainty in causing and forecasting the distribution of oil returns and risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 446-469.
    10. Kang, Boda & Nikitopoulos, Christina Sklibosios & Prokopczuk, Marcel, 2020. "Economic determinants of oil futures volatility: A term structure perspective," Energy Economics, Elsevier, vol. 88(C).
    11. Demirer, Riza & Gupta, Rangan & Suleman, Tahir & Wohar, Mark E., 2018. "Time-varying rare disaster risks, oil returns and volatility," Energy Economics, Elsevier, vol. 75(C), pages 239-248.
    12. He, Huizi & Sun, Mei & Gao, Cuixia & Li, Xiuming, 2021. "Detecting lag linkage effect between economic policy uncertainty and crude oil price: A multi-scale perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    13. Xu Gong & Boqiang Lin, 2022. "Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 610-640, January.
    14. Wen, Jun & Zhao, Xin-Xin & Chang, Chun-Ping, 2021. "The impact of extreme events on energy price risk," Energy Economics, Elsevier, vol. 99(C).
    15. Zhu, Xuehong & Zhang, Hongwei & Zhong, Meirui, 2017. "Volatility forecasting using high frequency data: The role of after-hours information and leverage effects," Resources Policy, Elsevier, vol. 54(C), pages 58-70.
    16. Jo-Hui & Chen & Sabbor Hussain, 2022. "Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-7.
    17. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    18. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2020. "Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction," Energy Economics, Elsevier, vol. 92(C).
    19. Liu, Feng & Zhang, Chuanguo & Tang, Mengying, 2021. "The impacts of oil price shocks and jumps on China's nonferrous metal markets," Resources Policy, Elsevier, vol. 73(C).
    20. Rashid Khan, Haroon Ur & Islam, Talat & Yousaf, Sheikh Usman & Zaman, Khalid & Shoukry, Alaa Mohamd & Sharkawy, Mohamed A. & Gani, Showkat & Aamir, Alamzeb & Hishan, Sanil S., 2019. "The impact of financial development indicators on natural resource markets: Evidence from two-step GMM estimator," Resources Policy, Elsevier, vol. 62(C), pages 240-255.
    21. Márcio Poletti Laurini & Roberto Baltieri Mauad & Fernando Antonio Lucena Aiube, 2016. "Multivariate Stochastic Volatility-Double Jump Model: an application for oil assets," Working Papers Series 415, Central Bank of Brazil, Research Department.
    22. Ignatieva, Katja & Wong, Patrick, 2022. "Modelling high frequency crude oil dynamics using affine and non-affine jump–diffusion models," Energy Economics, Elsevier, vol. 108(C).
    23. Ayben Koy, 2017. "Modelling Nonlinear Dynamics of Oil Futures Market," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 23-42, June.
    24. Andreas Kaloudis & Dimitrios Tsolis, 2019. "Capital Structure and Speed of Adjustment in U.S. Firms. Α Comparative Study in Microeconomic and Macroeconomic Conditions-A Quantile Regression Approach," International Business Research, Canadian Center of Science and Education, vol. 12(10), pages 98-109, October.

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    More about this item

    Keywords

    stochastic volatility; commodity futures prices; crude oil futures;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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