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Small‐time, large‐time, and H→0 asymptotics for the Rough Heston model

Author

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  • Martin Forde
  • Stefan Gerhold
  • Benjamin Smith

Abstract

We characterize the behavior of the Rough Heston model introduced by Jaisson and Rosenbaum (2016, Ann. Appl. Probab., 26, 2860–2882) in the small‐time, large‐time, and α→12 (i.e., H→0) limits. We show that the short‐maturity smile scales in qualitatively the same way as a general rough stochastic volatility model , and the rate function is equal to the Fenchel–Legendre transform of a simple transformation of the solution to the same Volterra integral equation (VIE) that appears in El Euch and Rosenbaum (2019, Math. Financ., 29, 3–38), but with the drift and mean reversion terms removed. The solution to this VIE satisfies a space–time scaling property which means we only need to solve this equation for the moment values of p=1 and p=−1 so the rate function can be efficiently computed using an Adams scheme or a power series, and we compute a power series in the log‐moneyness variable for the asymptotic implied volatility which yields tractable expressions for the implied vol skew and convexity which is useful for calibration purposes. We later derive a formal saddle point approximation for call options in the Forde and Zhang (2017) large deviations regime which goes to higher order than previous works for rough models. Our higher‐order expansion captures the effect of both drift terms, and at leading order is of qualitatively the same form as the higher‐order expansion for a general model which appears in Friz et al. (2018, Math. Financ., 28, 962–988). The limiting asymptotic smile in the large‐maturity regime is obtained via a stability analysis of the fixed points of the VIE, and is the same as for the standard Heston model in Forde and Jacquier (2011, Finance Stoch., 15, 755–780). Finally, using Lévy's convergence theorem, we show that the log stock price Xt tends weakly to a nonsymmetric random variable Xt(12) as α→12 (i.e., H→0) whose moment generating function (MGF) is also the solution to the Rough Heston VIE with α=12, and we show that Xt(12)/t tends weakly to a nonsymmetric random variable as t→0, which leads to a nonflat nonsymmetric asymptotic smile in the Edgeworth regime, where the log‐moneyness z=kt as t→0, and we compute this asymptotic smile numerically. We also show that the third moment of the log stock price tends to a finite constant as H→0 (in contrast to the Rough Bergomi model discussed in Forde et al. (2020, Preprint) where the skew flattens or blows up) and the V process converges on pathspace to a random tempered distribution which has the same law as the H=0 hyper‐rough Heston model, discussed in Jusselin and Rosenbaum (2020, Math. Finance, 30, 1309–1336) and Abi Jaber (2019, Ann. Appl. Probab., 29, 3155–3200).

Suggested Citation

  • Martin Forde & Stefan Gerhold & Benjamin Smith, 2021. "Small‐time, large‐time, and H→0 asymptotics for the Rough Heston model," Mathematical Finance, Wiley Blackwell, vol. 31(1), pages 203-241, January.
    • Handle: RePEc:bla:mathfi:v:31:y:2021:i:1:p:203-241
    DOI: 10.1111/mafi.12290
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    References listed on IDEAS

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    1. Peter Friz & Stefan Gerhold & Arpad Pinter, 2018. "Option pricing in the moderate deviations regime," Mathematical Finance, Wiley Blackwell, vol. 28(3), pages 962-988, July.
    2. Antoine Jacquier & Alexandre Pannier, 2020. "Large and moderate deviations for stochastic Volterra systems," Papers 2004.10571, arXiv.org, revised Apr 2022.
    3. Martin Forde & Antoine Jacquier & Aleksandar Mijatović, 2011. "A note on essential smoothness in the Heston model," Finance and Stochastics, Springer, vol. 15(4), pages 781-784, December.
    4. Omar El Euch & Mathieu Rosenbaum, 2019. "The characteristic function of rough Heston models," Mathematical Finance, Wiley Blackwell, vol. 29(1), pages 3-38, January.
    5. Masaaki Fukasawa, 2017. "Short-time at-the-money skew and rough fractional volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 189-198, February.
    6. Stefan Gerhold & Christoph Gerstenecker & Arpad Pinter, 2019. "Moment explosions in the rough Heston model," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(2), pages 575-608, December.
    7. Jim Gatheral & Antoine Jacquier, 2011. "Convergence of Heston to SVI," Quantitative Finance, Taylor & Francis Journals, vol. 11(8), pages 1129-1132.
    8. Martin Forde & Antoine Jacquier, 2011. "The large-maturity smile for the Heston model," Finance and Stochastics, Springer, vol. 15(4), pages 755-780, December.
    9. Christian Bayer & Peter K. Friz & Archil Gulisashvili & Blanka Horvath & Benjamin Stemper, 2017. "Short-time near-the-money skew in rough fractional volatility models," Papers 1703.05132, arXiv.org, revised Mar 2018.
    10. Aleksandar Mijatović & Peter Tankov, 2016. "A New Look At Short-Term Implied Volatility In Asset Price Models With Jumps," Mathematical Finance, Wiley Blackwell, vol. 26(1), pages 149-183, January.
    11. Peter K. Friz & Paul Gassiat & Paolo Pigato, 2018. "Precise asymptotics: robust stochastic volatility models," Papers 1811.00267, arXiv.org, revised Nov 2020.
    12. Kun Gao & Roger Lee, 2014. "Asymptotics of implied volatility to arbitrary order," Finance and Stochastics, Springer, vol. 18(2), pages 349-392, April.
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    15. Forde, Martin, 2011. "Large-time asymptotics for an uncorrelated stochastic volatility model," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1230-1232, August.
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    Cited by:

    1. Martin Friesen & Peng Jin, 2022. "Volterra square-root process: Stationarity and regularity of the law," Papers 2203.08677, arXiv.org, revised Oct 2022.

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