In this article, we study nonparametric estimation of regression function by using the weighted Nadaraya-Watson approach. We establish the asymptotic normality and weak consistency of the resulting estimator for [alpha]-mixing time series at both boundary and interior points, and we show that...

Let X1,X2,... be real-valued random variables forming a strictly stationary sequence, and satisfying the basic requirement of being positively or negatively associated. Let [xi]p denote the pth quantile of the marginal distribution function of the Xi's, which is estimated by a smooth...

One of the advantages for the varying-coefficient model is to allow the coefficients to vary as smooth functions of other variables and the model can be estimated easily through a simple local quasi-likelihood method. This leads to a simple one-step estimation procedure. We show that such a...

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric...

We suggest using a class of semiparametric dynamic panel data models to capture individual variations in panel data. The model assumes linearity in some continu ous/discrete variables which can be exogenous/endogenous, and allows for nonlinearity in other weakly exogenous variables. We propose a...

We study a new class of semiparametric instrumental variables models with the structural function represented by a partially varying coefficient functional form. Under this representation, the models are linear in the endogenous/exogenous components with unknown constant or functional...

We study nonparametric estimation of regression function with nonstationary (integrated or nearly integrated) covariates and the error series of the regressor process following a fractional ARIMA model. A local linear estimation method is developed to estimate the unknown regression function....

This paper gives a selective overview on the functional coefficient models with their particular applications in economics and finance. Functional coefficient models are very useful analytic tools to explore complex dynamic structures and evolutions for functional data in various areas,...