In this paper we propose a generalisation of the noise trader transmission mechanism to examine the impact of central bank intervention on exchange rates. Within a heterogeneous expectations exchange rate model intervention operations are supposed to provide support to either chartist or...

For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly. A common strategy to deal with this problem within the context of design is to construct maximin...

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian...

This paper explores the theory behind the rich and robust family of »-stable distributions to estimate parameters from financial asset log-returns data. We discuss four-parameter estimation methods including the quantiles, logarithmic moments method, maximum likelihood (ML), and the empirical...

This paper provides a complete program for the valuation of aggregate non-life insurance liability cash flows based on claims triangle data. The valuation is fully consistent with the principle of valuation by considering the costs associated with a transfer of the liability to a so-called...

A class of semiparametric fractional autoregressive GARCH models (SEMIFAR-GARCH), which includes deterministic trends, difference stationarity and stationarity with short-and long-range dependence, and heteroskedastic model errors, is very powerful for modelling ?nancial time series. This paper...

This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters. Specifically, the filter is designed for the situation where...

In this article, our goal is to improve the estimation of the parameters of solar photovoltaic models, we propose a method based on Simulated Annealing (SA) Optimization, the proposed algorithm takes into account the uncertainties of measurements. This algorithm consists of three steps such as...

Recently, the application of the proton exchange membrane fuel cells (PEMFCs) is extensively increasing as a popular renewable energy source. PEMFCs need low temperature for the operation along with high power density and easy implementation ability. These characteristics turned them into the...

This paper presents a new optimal method for model estimation of the unknown parameters of circuit-based proton exchange membrane fuel cells (PEMFCs). The main idea is to minimize the sum of squared error (SSE) value between the actual data and the estimated results. The optimization process...