Forecasting interest rates through Vasicek and CIR models: a\n partitioning approach

The aim of this paper is to propose a new methodology that allows\nforecasting, through Vasicek and CIR models, of future expected interest rates\n(for each maturity) based on rolling windows from observed financial market\ndata. The novelty, apart from the use of those models not for pricing but for\nforecasting the expected rates at a given maturity, consists in an appropriate\npartitioning of the data sample. This allows capturing all the statistically\nsignificant time changes in volatility of interest rates, thus giving an\naccount of jumps in market dynamics. The performance of the new approach is\ncarried out for different term structures and is tested for both models. It is\nshown how the proposed methodology overcomes both the usual challenges (e.g.\nsimulating regime switching, volatility clustering, skewed tails, etc.) as well\nas the new ones added by the current market environment characterized by low to\nnegative interest rates.\n