Nonparametric conditional density estimation of short-term interest rate movements: procedures, results and risk management implications

This article shows how to estimate the conditional density of daily changes in the 3-month T-bill rate, using an extension of the kernel-based estimator proposed by Rosenblatt (1969). The shape of the estimated density is allowed to vary with both the level and the lagged change in rates. Due to the nonparametric character of the estimation procedure, the model produces conditional quantile estimates that are based only on the data and are independent of the modellers’ assumptions. The obtained results do not support the assumption of systematically mean-reverting behaviour underlying some theoretical models of short-term interest rate dynamics. However, they clearly indicate the presence of nonlinear first-order autocorrelation and volatility clustering effects, as well as a positive relationship between yield volatility and level.