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Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data

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  • Baum, Christopher F.
  • Zerilli, Paola
  • Chen, Liyuan

Abstract

In this paper, we propose a model for futures returns that has the potential to provide both individual investors and firms who have positions in financial and energy commodity futures a valid tail risk management tool. In doing so, we also aim to explore the commonalities between these markets and the degree of financialization of energy commodities. While empirical studies in energy markets embed either leverage or jumps in the futures return dynamics, we show that the introduction of both features improves the ability to forecast volatility as an indicator for risk for both the S&P500 and natural gas futures markets.

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  • 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).
    • Handle: RePEc:eee:eneeco:v:93:y:2021:i:c:s0140988319302622
    DOI: 10.1016/j.eneco.2019.104481
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    Cited by:

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    2. Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Modeling the electricity spot price with switching regime semi-nonparametric distributions," Documentos de Trabajo de Valor Público 17618, Universidad EAFIT.
    3. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    4. 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.
    5. Xinjie Lu & Feng Ma & Jiqian Wang & Jing Liu, 2022. "Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 853-868, July.
    6. Shen, Lihua & Lu, Xinjie & Luu Duc Huynh, Toan & Liang, Chao, 2023. "Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 224-239.

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    More about this item

    Keywords

    Stochastic volatility; Energy futures; VaR; CVaR; High frequency data; Leverage effect; Jumps;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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