Robust Forecasting of Multiple Yield Curves

In this paper, we develop robust methods for forecasting term structures of interest rates. We implement a deep long short-term memory (LSTM) neural network based on keras. Our input data is based on the bootstrapped bid, mid and ask multiple (tenor-dependent) yield curves reflecting different risk categories over the period 2005–2018. We use the bid-ask spreads as an additional input factor modelling the market depth. Since there is only a limited amount of data available, there is a lack of a sufficiently large training data set. We cope with that difficulty by generating data based on fitted time series models in order to enlarge the training data. Furthermore, we apply support vector machines to predict trends in the term structures. For this approach, we include different market variables to investigate the relationship of these quantities to future yields.

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