The topic of this chapter is forecasting with nonlinear models. First, a number of well-known
nonlinear models are introduced and their properties discussed. These include the smooth …

Forecast evaluation often compares a parsimonious null model to a larger model that nests
the null model. Under the null that the parsimonious model generates the data, the larger …

We address some of the key questions that arise in forecasting the price of crude oil. What
do applied forecasters need to know about the choice of sample period and about the …

We propose a new test for superior predictive ability. The new test compares favorably to the
reality check (RC) for data snooping, because it is more powerful and less sensitive to poor …

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 …

It is widely known that significant in-sample evidence of predictability does not guarantee
significant out-of-sample predictability. This is often interpreted as an indication that in …

We consider using out-of-sample mean squared prediction errors (MSPEs) to evaluate the
null that a given series follows a zero mean martingale difference against the alternative that …

Forecasts guide decisions in all areas of economics and finance and their value can only be
understood in relation to, and in the context of, such decisions. We discuss the central role of …

We propose an encompassing test for comparing conditional quantile forecasts in an out-of-
sample framework. Our test provides a basis for forecast combination when encompassing …

Evidence exists that emerging market stock returns are influenced by a different set of factors
than those that influence the returns for stocks traded in developed countries. This study …