Option Pricing Using Forward Curves From Arbitrage Free Autoencoders
This thesis evaluates the feasibility of arbitrage free autoencoder models for forward curve simulation using European bond data. In the model, an autoencoder is used to learn a low dimensional factor representation of forward curves. The risk neutral evolution of forward curves can be calculated by introducing a stochastic process in this low dimensional latent space. A correction factor is added
