DECOMPOSITION FORMULA FOR ROUGH VOLTERRA STOCHASTIC VOLATILITY MODELS

The research presented in this paper provides an alternative option pricing approach for a class of rough fractional stochastic volatility models. These models are increasingly popular between academics and practitioners due to their surprising consistency with financial markets. However, they bring several challenges alongside. Most noticeably, even simple nonlinear derivatives as vanilla European options typically priced by means Monte–Carlo (MC) simulations which more computationally demanding than similar MC schemes standard In paper, we provide proof the prediction law general Gaussian Volterra processes. is then utilized obtain adapted projection future squared — cornerstone proposed approximation. Firstly, decomposition formula prices under introduced. Then focus on particular derive explicit semi-closed approximation formula. Numerical properties model rBergomi studied propose hybrid calibration scheme combines alongside simulations. This can significantly speed up markets illustrated set AAPL options.