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Regime Switching Entropic Risk Measures on Crude Oil Pricing

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  • Babacar Seck
  • Robert J. Elliott

Abstract

This paper introduces a new type of risk measures, namely regime switching entropic risk measures, and study their applicability through simulations. The state of the economy is incorporated into the entropic risk formulation by using a Markov chain. Closed formulae of the risk measure are obtained for futures on crude oil derivatives. The applicability of these new types of risk measures is based on the study of the risk aversion parameter and the convenience yield. The numerical results show a term structure and a mean-reverting behavior of the convenience yield.

Suggested Citation

  • Babacar Seck & Robert J. Elliott, 2021. "Regime Switching Entropic Risk Measures on Crude Oil Pricing," Papers 2112.13041, arXiv.org.
  • Handle: RePEc:arx:papers:2112.13041
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    1. Dohmen, Thomas & Lehmann, Hartmut & Pignatti, Norberto, 2016. "Time-varying individual risk attitudes over the Great Recession: A comparison of Germany and Ukraine," Journal of Comparative Economics, Elsevier, vol. 44(1), pages 182-200.
    2. Ron Alquist & Gregory Bauer & Antonio Diez de los Rios, 2014. "What Does the Convenience Yield Curve Tell Us about the Crude Oil Market?," Staff Working Papers 14-42, Bank of Canada.
    3. Mason, Charles F. & Wilmot, Neil A., 2020. "Jumps in the convenience yield of crude oil," Resource and Energy Economics, Elsevier, vol. 60(C).
    4. Babacar Seck & Laetitia Andrieu & Michel De Lara, 2012. "Parametric multi-attribute utility functions for optimal profit under risk constraints," Theory and Decision, Springer, vol. 72(2), pages 257-271, February.
    5. Lisa Anderson & Jennifer Mellor, 2009. "Are risk preferences stable? Comparing an experimental measure with a validated survey-based measure," Journal of Risk and Uncertainty, Springer, vol. 39(2), pages 137-160, October.
    6. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    7. Christiane Baumeister & Lutz Kilian, 2016. "Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 139-160, Winter.
    8. Yulia V. Veld‐Merkoulova & Frans A. de Roon, 2003. "Hedging long‐term commodity risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(2), pages 109-133, February.
    9. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    10. Freddy H. Marín Sánchez & Verónica M. Gallego, 2016. "Parameter Estimation in Mean Reversion Processes with Deterministic Long-Term Trend," Journal of Probability and Statistics, Hindawi, vol. 2016, pages 1-8, August.
    11. Goovaerts, Marc J. & Kaas, Rob & Laeven, Roger J.A. & Tang, Qihe, 2004. "A comonotonic image of independence for additive risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 581-594, December.
    12. Kai Detlefsen & Giacomo Scandolo, 2005. "Conditional and dynamic convex risk measures," Finance and Stochastics, Springer, vol. 9(4), pages 539-561, October.
    13. Brandtner, Mario & Kürsten, Wolfgang & Rischau, Robert, 2018. "Entropic risk measures and their comparative statics in portfolio selection: Coherence vs. convexity," European Journal of Operational Research, Elsevier, vol. 264(2), pages 707-716.
    14. Patrick Cheridito & Freddy Delbaen & Michael Kupper, 2005. "Coherent and convex monetary risk measures for unbounded càdlàg processes," Finance and Stochastics, Springer, vol. 9(3), pages 369-387, July.
    15. Babacar Seck & Laetitia Andrieu & Michel de Lara, 2012. "Parametric multi-attribute utility functions for optimal profit under risk constraints," Post-Print hal-00654574, HAL.
    16. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    17. Rashid, Abdul, 2008. "Macroeconomic Variables and Stock Market Performance: Testing for Dynamic Linkages with a Known Structural Break," MPRA Paper 26937, University Library of Munich, Germany.
    18. Kai Detlefsen & Giacomo Scandolo, 2005. "Conditional and Dynamic Convex Risk Measures," SFB 649 Discussion Papers SFB649DP2005-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Gibson, Rajna & Schwartz, Eduardo S, 1990. "Stochastic Convenience Yield and the Pricing of Oil Contingent Claims," Journal of Finance, American Finance Association, vol. 45(3), pages 959-976, July.
    20. 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.
    21. Aharon Ben‐Tal & Marc Teboulle, 2007. "An Old‐New Concept Of Convex Risk Measures: The Optimized Certainty Equivalent," Mathematical Finance, Wiley Blackwell, vol. 17(3), pages 449-476, July.
    22. Hannah Schildberg-Hörisch, 2018. "Are Risk Preferences Stable?," Journal of Economic Perspectives, American Economic Association, vol. 32(2), pages 135-154, Spring.
    23. Almansour, Abdullah, 2016. "Convenience yield in commodity price modeling: A regime switching approach," Energy Economics, Elsevier, vol. 53(C), pages 238-247.
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