Peter’s research interests are numerical methods as well as machine learning in option pricing, trading strategies, and risk management. His research investigates neural networks applied to contingent claims, where the aim is more accurate prices and a better understanding of neural networks. Peter`s first paper investigates the feature selection issue in the LSM model for pricing American-style options. The paper shows the neural network model FNNMC price estimates are more accurate for basket options. Furthermore, the method overcomes the feature selection issue by training the network. Website: Github: LinkedIn: ©