Lookback option pricing under the double Heston model using a deep learning algorithm

To price floating strike lookback options, we obtain a partial differential equation (PDE) according to the double Heston model. To solve the PDE, we employ a deep learning algorithm called the deep Galerkin method (DGM), which is well-suited for high-dimensional PDEs. Finally, we compare the obtained results from mentioned method with the option price under the Monte Carlo simulation method.