This paper discusses nonparametric kernel regression with the regressor being a d-dimensional ß-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate p n(T)hd, where n(T) is the number of regenerations...

The term structure of interest rates is used to price defaultable bonds and credit derivatives, as well as to infer the quality of bonds for risk management purposes. We introduce a model that jointly estimates term structures by means of a Bayesian hierarchical model with a prior probability...

This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rate. This method is compared in its ability to capture the dynamics of short rate volatility to a class of one-factor diffusion models where the conditional variance is serially correlated and...

In this paper we consider a novel procedure for forecasting the US yield curve by using the methodology of nonparametric kernel estimation of functional data (NP-FDA). Within this approach, each element of the sample is a monthly yield curve, evaluated at points corresponding to maturities. In...

It is well documented in the literature that individual saving decisions vary with the life cycle and at the macroeconomic level, a changing demographic age structure affects aggregated savings, which then drives a slow movement of interest rates. In this paper, we propose a semiparametric...

The traditional approach to bond portfolio immunization usually assumes that the possible future changes of the term structure of interest rates lie within a suitable parametric class of functions. The quantities of interest are the sensitivities of the portfolio value with respect to these...

We propose a nonparametric test that distinguishes 'depressions' and 'booms' from ordinary recessions and expansions. Depressions and booms are defined as coming from another underlying process than recessions and expansions. We find four depressions and booms in the NBER business cycle between...

High-dimensional regression problems which reveal dynamic behavior are typically analyzed by time propagation of a few number of factors. The inference on the whole system is then based on the low-dimensional time series analysis. Such highdimensional problems occur frequently in many different...

We consider two semiparametric models for the weight function in a bias sample model. The object of our interest parametrizes the weight function, and it is either Euclidean or non Euclidean. One of the models discussed in this paper is motivated by the estimation the mixing distribution of...