The aim of the present paper is to develop an iterative method to solve nonlinear equations. The underlying idea of the proposed method is based on well known Newton-Raphson method and Fixed Point Iteration method. The convergence of the new modified method is discussed in the present work. The...

We develop new tail-trimmed QML estimators for nonlinear GARCH models with possibly heavy tailed errors. Tail-trimming allows both identification of the true parameter and asymptotic normality. In heavy tailed cases the rate of convergence is below but arbitrarily close to root-n, the highest...

With the concept of trend inflation now widely understood as to be important as a measure of the public's perception of the inflation goal of the central bank and important to the accuracy of longer-term inflation forecasts, this paper uses Bayesian methods to assess alternative models of trend...

We propose a multivariate combination approach to prediction based on a distributional state space representation of the weights belonging to a set of Bayesian predictive densities which have been obtained from alternative models. Several specifications of multivariate time-varying weights are...

Observing prices of European put and call options, we calibrate exponential Lévy models nonparametrically. We discuss the implementation of the spectral estimation procedures for Lévy models of finite jump activity as well as for self-decomposable Lévy models and improve these methods....

Effectiveness, cost-efficiency and distribution issues are crucial for any form of future regulation. This results in the need for reliable instruments to assess regulations ex ante. Elasticities are key parameters for such instruments. We consistently estimate substitution elasticities for a...