Stock picking is the field of financial analysis that is of particular interest for many professional investors and researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the crucial factor in forecasting performance of the...

The purpose of this paper is to propose a new likelihood-based panel cointegration testin the presence of a linear time trend in the data generating process. This new test is an extensionof the likelihood ratio (LR) test of Saikkonen & L¨utkepohl (2000) for trend-adjusteddata to the panel data...

We introduce new stylometry tools based on the sliced conditional compression complexity of literary texts which are inspired by the nearly optimal application of the incomputable Kolmogorov conditional complexity (and presumably approximates it). Whereas other stylometry tools can occasionally...

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic terms suggested by Saikkonen & Lüutkepohl (2000b) and Saikkonen,Lütkepohl & Trenkler (2006). The asymptotic properties of the bootstrap test procedures are derived and their...

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...

The behaviour of market agents has always been extensively covered in the literature. Risk averse behaviour, described by von Neumann and Morgenstern (1944) via a concave utility function, is considered to be a cornerstone of classical economics. Agents prefer a fixed profit over uncertain...

In this paper, we review the most common specifications of discrete-time stochasticvolatility (SV) models and illustrate the major principles of corresponding MarkovChain Monte Carlo (MCMC) based statistical inference. We provide a hands-on approachwhich is easily implemented in empirical...

Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most...

A great proportion of stock dynamics can be explained using publicly availableinformation. The relationship between dynamics and public information may be ofnonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...