This paper considers the class of p-dimensional elliptic distributions (p ≥ 1) satisfying the consistency property (Kano, 1994) and within this general frame work presents a two-stage semiparametric estimator for the Lebesgue density based on Gaussian mixture sieves. Under the online...

This paper considers the class of p-dimensional elliptic distributions (p≥1) satisfying the consistency property (Kano, 1994)  [23] and within this general framework presents a two-stage nonparametric estimator for the Lebesgue density based on Gaussian mixture sieves. Under the on-line...

This paper considers the class of p-dimensional elliptic distributions (p ≥ 1) satisfying the consistency property (Kano, 1994) and within this general framework presents a two-stage semiparametric estimator for the Lebesgue density based on Gaussian mixture sieves. Under the online...

Suppose we observe a Markov chain taking values in a functional space. We are interested in exploiting the time series dependence in these infinite dimensional data in order to make non-trivial predictions about the future. Making use of the Karhunen–Loève (KL) representation of functional...

A conference titled 'Forecasting in Rio' was held at the Graduate School of Economics of Getulio Vargas Foundation, Rio de Janeiro, Brazil, in July 2008 to focus on most recent developments in forecasting. One of the papers presented during the conference was titled, 'Predictability of Stock...

This paper studies the estimation of a semi-strong GARCH(1,1) model when it does not have a stationary solution, where semi-strong means that we do not require the errors to be independent over time. We establish necessary and sufficient conditions for a semi-strong GARCH(1,1) process to have a...

We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted estimator are defined. All the estimators are proved to be asymptotically normal,...

We propose estimators of previous termfeatures of the distributionnext term of an unobserved random variable W. What is observed is previous termanext term sample of Y,V,X where previous termanext term binary Y equals one when W exceeds previous termanext term threshold V determined by...

This article is concerned with evaluating Value-at-Risk estimates. It is well known that using only binary variables, such as whether or not there was an exception, sacrifices too much information. However, most of the specification tests (also called backtests) available in the literature, such...

We investigate a class of semiparametric ARCH models that includes as a special case the partially nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible function form with regard to the 'news impact' function. We show that the...