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Two-factor Rough Bergomi Model: American Call Option Pricing and Calibration by Interior Point Optimization Algorithm

  • Arezou Karimi,
  • Farshid Mehrdoust,
  • Maziar Salahi

摘要

This paper develops the fractional Bergomi model and introduces the two-factor fractional Bergomi model with Hurst index \(H \in (0, \frac{1}{2})\) H ( 0 , 1 2 ) . We examine both the existence and stability of solutions, as well as the convergence of the numerical methods applied to the proposed model. We then conduct the model calibration using the interior point algorithm. A comparison of the proposed model prices with the rough Bergomi and the two-factor fractional Bergomi models with long memory demonstrates its strong alignment with market behavior in both in-sample and out-of-sample datasets. Additionally, the proposed model effectively captures the characteristics of implied volatility, specifically the volatility smile.