This chapter summarizes recent literature on asymptotic inference about forecasts. Both
analytical and simulation based methods are discussed. The emphasis is on techniques …

This paper gives a brief overview of the nonparametric techniques that are useful for
financial econometric problems. The problems include estimation and inference for …

We consider quantile autoregression (QAR) models in which the autoregressive coefficients
can be expressed as monotone functions of a single, scalar random variable. The models …

This paper presents analytical, Monte Carlo and empirical evidence concerning out-of-
sample tests of Granger causality. The environment is one in which the relative predictive …

The varying coefficient models are very important tool to explore the dynamic pattern in
many scientific areas, such as economics, finance, politics, epidemiology, medical science …

This book contains a up-to-date overview of nonlinear time series models and their
application to modelling economic relationships. It considers nonlinear models in stationary …

This paper studies a time-varying coefficient time series model with a time trend function and
serially correlated errors to characterize the nonlinearity, nonstationarity, and trending …

This article introduces a data-driven Box–Pierce test for serial correlation. The proposed test
is very attractive compared to the existing ones. In particular, implementation of this test is …

We suggest quantile regression methods for a class of smooth coefficient time series
models. We use both local polynomial and local constant fitting schemes to estimate the …

Varying-coefficient linear models arise from multivariate nonparametric regression, non-
linear time series modelling and forecasting, functional data analysis, longitudinal data …