When a company releases earnings results or makes announcements, a dominant sectoral wide lead-lag effect from the stock on the entire system may occur. To improve the estimation of a system experiencing dominant system-wide lead-lag effects from one or a few asset in the presence of short time...

Methods of dimension reduction are very helpful and almost a necessity if we want to analyze high-dimensional time series since otherwise modelling affords many parameters because of interactions at various time-lags. We use a dynamic version of Sliced Inverse Regression (SIR; Li (1991)), which...

In this paper, we will consider the semiparametric regression model introduced by Duan and Li (1991). The response variable y will be linked to an index x′β (i.e. a linear combination of the explanatory variables x) through an unknown function. In order to estimate the direction of the...

Methods of dimension reduction are very helpful and almost a necessity if we want to analyze high-dimensional time series since otherwise modelling affords many parameters because of interactions at various time-lags. We use a dynamic version of Sliced Inverse Regression (SIR; Li (1991)), which...

In most situations, modern technological developments give rise to the cases where samples are drawn from a population of real random functions. Functional Data Analysis (FDA) is an appropriate multivariate statistical approximation since the classical multivariate methods can not be used when a...

Microeconomic theory often yields models with multiple nonlinear equations, nonseparable unobservables, nonlinear cross equation restrictions, and many potentially multicollinear covariates. We show how statistical dimension reduction techniques can be applied in models with these features. In...

In this paper we provide a review of copula theory with applications to finance. We illustrate the idea on the bivariate framework and discuss the simple, elliptical and Archimedean classes of copulae. Since the cop- ulae model the dependency structure between random variables, next we explain...

One of the most studied questions in economics and finance is whether equity returns or premiums can be predicted by empirical models. While many authors favor the historical mean or other simple parametric methods, this article focuses on nonlinear relationships. A straightforward...

Methods of dimension reduction are very helpful and almost a necessity if we want to analyze high-dimensional time series since otherwise modelling affords many parameters because of interactions at various time-lags. We use a dynamic version of Sliced Inverse Regression (SIR; Li (1991)), which...