We discuss a class of risk measures for portfolio optimization with linear loss functions, where the random returns of financial instruments have a multivariate elliptical distribution. Under this setting we pay special attention to two risk measures, Value-at-Risk and Conditional-Value-at-Risk...

In this paper the effect of the break quantity rule on the inventory costs in a 1-warehouse, N-retailers distribution system is analyzed. The break quantity rule is to deliver large orders from the warehouse, and small orders from the nearest retailer, where a so--called break quantity...

Products which are sold through E-commerce or mail sales catalogues tend to have a much higher return rate than traditional products. The returns are especially problematic for seasonal products. To support decision making in these situations we study various options, which may be considered as...

Increased uncertainty is one of the characteristics of product recovery networks. In particular the strategic design of their logistic infrastructure has to take uncertain information into account. In this paper we present stochastic programming based approaches by which a deterministic location...

Several approaches exist to model decision making under risk, where risk can be broadly defined as the effect of variability of random outcomes. One of the main approaches in the practice of decision making under risk uses mean-risk models; one such well-known is the classical Markowitz model,...

Multiplicative interaction models, such as Goodman's RC(M) association models, can be a useful tool for analyzing the content of interaction effects. However, most models for interaction effects are only suitable for data sets with two or three predictor variables. Here, we discuss an optimal...

Abstract. The aim of this paper is to make an attempt to justify the main results from Convex Analysis by one elegant tool, the conification method, which consists of three steps: conify, work with convex cones, deconify. It is based on the fact that the standard operations and facts (`the...

Official forecasts of international institutions are never purely model-based. The preliminary results of models are adjusted with expert opinions. What is the impact of these adjustments for the forecasts? Are they necessary to get ‘optimal’ forecasts? When model-based forecasts...

Many companies collect stated preference data (SP) like intentions and satisfaction as well as revealed preference data (RP) like actual purchasing behavior. It seems relevant to examine the predictive usefulness of this information for future revealed preferences, that is, customer behavior. In...

We discuss specification, frequency domain estimation and application of flexible fractionally integrated seasonal long memory time series models, which allow for 'chi-squared' (seasonal) unit root testing. We suggest periodogram regression and approximate ML estimation. We successfully apply a...