Tid: 8 juni 2018 kl 15.15-15.50.

Föredragshållare: Markus Berg (Master thesis)

Titel: Modeling the Term Structure of Interest Rates with Restricted Boltzmann Machines

Abstract This thesis investigates if Gaussian restricted Boltzmann machines can be used to model the Swedish term structure of interest rates. The tested models are evaluated based on the ability to make one-day-ahead forecasts and the ability to generate plausible long term scenarios. The results are compared with simple benchmark models, such as assuming a random walk. The eects of principal component analysis as data preprocessing are also investigated. The results show that the ability to make one-day-ahead forecasts, measured as a mean squared error, is comparable to a random walk benchmark both in-sample and out-of-sample. The ability to generate long term scenarios show promising results based on visual properties and one-yearahead forecast error on semi-out-of-sample data. The main focus of the thesis is not to optimize performance of the models, but instead to serve as an introduction to modeling the term structure of interest rates with Gaussian restricted Boltzmann machines.

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