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The Additive Bachelier model with an application to the oil option market in the Covid period

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  • Roberto Baviera
  • Michele Domenico Massaria

Abstract

In April 2020, the Chicago Mercantile Exchange temporarily switched the pricing formula for West Texas Intermediate oil market options from the Black model to the Bachelier model. In this context, we introduce an Additive Bachelier model that provides a simple closed-form solution and a good description of the Implied volatility surface. This new Additive model exhibits several notable mathematical and financial properties. It ensures the no-arbitrage condition, a critical requirement in highly volatile markets, while also enabling a parsimonious synthesis of the volatility surface. The model features only three parameters, each one with a clear financial interpretation: the volatility term structure, vol-of-vol, and a parameter for modelling skew. The proposed model supports efficient pricing of path-dependent exotic options via Monte Carlo simulation, using a straightforward and computationally efficient approach. Its calibration process can follow a cascade calibration: first, it accurately replicates the term structures of forwards and At-The-Money volatilities observed in the market; second, it fits the smile of the volatility surface. Overall this model provides a robust and parsimonious description of the oil option market during the exceptionally volatile first period of the Covid-19 pandemic.

Suggested Citation

  • Roberto Baviera & Michele Domenico Massaria, 2025. "The Additive Bachelier model with an application to the oil option market in the Covid period," Papers 2506.09760, arXiv.org.
  • Handle: RePEc:arx:papers:2506.09760
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    References listed on IDEAS

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    1. repec:bla:jfinan:v:58:y:2003:i:2:p:753-778 is not listed on IDEAS
    2. Michele Azzone & Roberto Baviera, 2021. "A fast Monte Carlo scheme for additive processes and option pricing," Papers 2112.08291, arXiv.org, revised Jul 2023.
    3. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    4. Peter Carr & Lorenzo Torricelli, 2021. "Additive logistic processes in option pricing," Finance and Stochastics, Springer, vol. 25(4), pages 689-724, October.
    5. Roberto Baviera & Michele Domenico Massaria, 2025. "Smile asymptotic for Bachelier Implied Volatility," Papers 2506.08067, arXiv.org.
    6. Peter Carr & Liuren Wu, 2003. "The Finite Moment Log Stable Process and Option Pricing," Journal of Finance, American Finance Association, vol. 58(2), pages 753-777, April.
    7. Alexey Medvedev & Olivier Scaillet, 2007. "Approximation and Calibration of Short-Term Implied Volatilities Under Jump-Diffusion Stochastic Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 20(2), pages 427-459.
    8. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    9. Michele Azzone & Roberto Baviera, 2023. "A fast Monte Carlo scheme for additive processes and option pricing," Computational Management Science, Springer, vol. 20(1), pages 1-34, December.
    10. Azzone, Michele & Baviera, Roberto, 2021. "Synthetic forwards and cost of funding in the equity derivative market," Finance Research Letters, Elsevier, vol. 41(C).
    11. Roger W. Lee, 2004. "The Moment Formula For Implied Volatility At Extreme Strikes," Mathematical Finance, Wiley Blackwell, vol. 14(3), pages 469-480, July.
    12. Madan, Dilip B & Seneta, Eugene, 1990. "The Variance Gamma (V.G.) Model for Share Market Returns," The Journal of Business, University of Chicago Press, vol. 63(4), pages 511-524, October.
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