Forecasting Interest Rates Through Vasicek and CIR Models: A Partitioning Approach
G. Orlando, R.M. Mininni and M. Bufalo"Forecasting interest rates through Vasicek and CIR models: a partitioning approach" with - Journal of Forecasting, 12 December 2019
Posted: 8 Jan 2020
Date Written: December 12, 2019
The aim of this paper is to propose a new methodology that allows forecasting, through Vasicek and CIR models, of future expected interest rates based on rolling windows from observed financial market data. The novelty, apart from the use of those models not for pricing but for forecasting the expected rates at a given maturity, consists in an appropriate partitioning of the data sample. This allows capturing all the statistically significant time changes in volatility of interest rates, thus giving an account of jumps in market dynamics. The performance of the new approach is carried out for different term structures and is tested for both models. It is shown how the proposed methodology overcomes both the usual challenges (e.g. simulating regime switching, volatility clustering, skewed tails, etc.) as well as the new ones added by the current market environment characterized by low to negative interest rates.
Keywords: CIR Model, Vasicek Model, Interest Rates, Forecasting and Simulation
JEL Classification: G12, E43, E47
Suggested Citation: Suggested Citation