This paper provides a selected review of the recent developments and applications of mixtures of normal (MN) distribution models in empirical finance. Once attractive property of the MN model is that it is flexible enough to accommodate various shapes of continuous distributions, and able to...

This paper investigates an e±cient estimation method for a class of switching regressions based on the characteristic function (CF). We show that with the exponential weighting function, the CF based estimator can be achieved from minimizing a closed form distance measure. Due to the...

Viele aktive Entscheidungen bei der Anlage in Wertpapieren werden auf Basis von Informationen getroffen, die mit Hilfe empirischer Analysen historischer Finanzdaten gewonnen wurden. Leider sind die meisten Ergebnisse dieser Analysen sehr anfällig gegenüber einer Änderung der Zeitparameter,...

This article develops an efficient method for estimating the discrete mixtures of normal family based on the continuous empirical characteristic function (CECF). An iterated estimation procedure based on the closed form objective distance function is proposed to improve the estimation...

This paper develops an e±cient method for estimating the discrete mix- tures of normal family based on the continuous empirical characteristic function (CECF). An iterated estimation procedure based on the closed form objective distance function is proposed to improve the estimation effciency....

A central limit theorem for the weighted integrated squared error of kernel type estimators of the first two derivatives of a nonparametric regression function is proved by using results for martingale differences and U-statistics. The results focus on the setting of the Nadaraya-Watson...

A central limit theorem for the weighted integrated squared error of kernel type estimators of the first two derivatives of a nonparametric regression function is proved by using results for martingale differences and U-statistics. The results focus on the setting of the Nadaraya-Watson...

Bandwidth selection in multivariate kernel density estimation has received considerable attention. In addition to classical methods of bandwidth selection, such as plug-in and cross-validation methods, Bayesian approaches have also been previously investigated. Bayesian estimation of adaptive...

It is shown that the integrated squared errors of wavelet projection estimators of a density f satisfy both the central limit theorem and the law of the iterated logarithm under the essentially minimal assumption f∈Lp for some p>2 and very mild conditions on the scaling function.