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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
