Recurrent artificial neural networks for forecasting of forward interest rates

There are numerous method for estimating forward interest rates as well as many studies testing the accuracy of those methods. The approach proposed in this study is similar to the one in previous work in two respects: First, a Monte Carlo simulation is used. Second, in this study, accuracy is measured by estimating the forward rates rather than by exploring bond prices. This is more consistent with user objectives. The method we present here departs from previous work in that it uses a recurrent artificial neural network (RANN) as an alternative technique for forecasting forward interest rates. Its performance is compared to that of a recursive method which has produced some of the best results in previous study for forecasting forward interest rates