In this paper we consider different periodic extensions of regression models with autoregressive fractionally integrated moving average disturbances for the analysis of daily spot prices of electricity. We show that day-of-the-week periodicity and long memory are important determinants for the...

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors should be serially uncorrelated at the single period horizon with...

A common problem in out-of-sample prediction is that there are potentially many relevant predictors that individually have only weak explanatory power. We propose bootstrap aggregation of pre-test predictors (or bagging for short) as a means of constructing forecasts from multiple regression...

In real time forecasting, the sample is usually split into an estimation period of R observations and a prediction period of P observations, where T=R+P. Parameters are often estimated in a recursive manner, initially using R observations, then R+1 observations and so on until T-1 observations...

Recently financial econometricians have shifted their attention from point and interval forecasts to density forecasts mainly to address the issue of the huge loss of information that results from depicting portfolio risk by a measure of dispersion alone. One of the major problems in this area...

Filtering techniques are often applied to the estimation of dynamic latent variable models. However, these techniques are often based on a set assumptions which restrict models to be specified in a linear state-space form. Numerical filtering techniques have been propsed that avoid invoking such...

Decision theorists claim that an ordinal measure of risk may be sufficient for an agent to make a rational choice under uncertainty. We propose a measure of financial risk, namely the Varying Cross-sectional Risk (VCR), that is based on a ranking of returns. VCR is defined as the probability of...

Bootstrap aggregating or Bagging, introduced by Breiman (1996a), has been proved to be effective to improve on unstable forecast. Theoretical and empirical works using classification, regression trees, variable selection in linear and non-linear regression have shown that bagging can generate...

Tests and estimation for changes in the coefficients of linear regression models, particularly the analysis of covariance and the Chow tests, are well known to econometricians and are widely used. This paper demonstrates that analogous estimation can also be constructed in simultaneous equation...

This paper considers the parametric inference of a wide range of structural econometric models. The class of models considered includes those with parameter-dependent support and those derived from game-theoretic models. Inference of those models has raised some important econometric issues....