Derivatives were created to offset losses from changes in the price of underlying assets, and several stochastic models were presented to explain the movements of underlying assets on derivatives. To compensate for the limitations of the classical Bla...
Derivatives were created to offset losses from changes in the price of underlying assets, and several stochastic models were presented to explain the movements of underlying assets on derivatives. To compensate for the limitations of the classical Black-Scholes model, the Heston Model, a stochastic volatility model, is proposed as an alternative, and the Double Heston Model (DH model) and the Rescaled Double Heston model (RDH model) are also presented to overcome the limitations of the existing model, better capturing volatility in the real market. In this paper, we derive a closed solution of the fair price of the European option in the three models, and conduct a numerical analysis of the three models using Python. The motion visualization of the three models using Monte Carlo simulation method, sensitivity analysis of parameters, model calibration using market data of the VIX index, and the theoretical and actual market prices of the options are compared around Mean Square Error and Computing time. As a result, we show that the RDH model efficiently captures market volatility while having less computing time than the DH model.