This paper proposes a straightforward Markov-switching asset allocation model, which reduces the market exposure to periods of high volatility. The main purpose of the study is to examine the performance of a regime-based asset allocation strategy under realistic assumptions, compared to a buy...

A d-dimensional nonparametric additive regression model with dependent observations is considered. Using the marginal integration technique and wavelets methodology, we develop a new adaptive estimator for a component of the additive regression function. Its asymptotic properties are...

We investigate the estimation of the ?-fold convolution of the density of an unob- served variable X from n i.i.d. observations of the convolution model Y = X + ?. We first assume that the density of the noise ? is known and define nonadaptive estimators, for which we provide bounds for the mean...

Autin [2007. Maxisets for [mu]-thresholding rules. Test, to appear, see <http://www.seio.es/test/Archivos/issues/Ab_TESTAutin.html>] has established the following estimation result: by considering the Gaussian white noise model and the Besov risk , the BlockShrink estimator is better in the maxiset sense than the hard thresholding estimator. In the...</http://www.seio.es/test/archivos/issues/ab_testautin.html>

The density estimation problem under bias and multiplicative censoring is considered. Adopting the wavelet approach, we construct a linear nonadaptive estimator and a nonlinear adaptive estimator. The adaptive one belongs to the family of the hard thresholding estimators. We evaluate their...

This paper proposes a straightforward Markov-switching asset allocation model, which reduces the market exposure to periods of high volatility. The main purpose of the study is to examine the performance of a regime-based asset allocation strategy under realistic assumptions, compared to a buy...

The problem of estimating a regression function based on a regression model with (known) random design is considered. By adopting the framework of wavelet analysis, we establish the asymptotic minimax rate of convergence under the risk over Besov balls. A part of this paper is devoted to the...