In this paper, the problem of calculating covariances and correlations between time series which are observed irregularly and at different points in time, is treated. The problem of dependence between the time stamp process and the return process is especially highlighted and the solution to...

In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance of D. The standard approach is then to determine the order quantity using...

In this paper we give a survey on some basic ideas related to random utility, extreme value theory and multinomial logit models. These ideas are well known within the field of spatial economics, but do not appear to be common knowledge to researchers in probability theory. The purpose of the...

In this note we explore the following surprising fact: In regression with trend and seasonality, the prediction risk is constant for all seasons of a new cycle, despite the fact that it increases with time when the seasons are left out. Awareness of this may be useful to both the practicing...

In this paper some methods to determine the reporting delays for trades on the New York stock exchange are proposed and compared. The most successful method is based on a simple model of the quote revision process and a bootstrap procedure. In contrast to previous methods it accounts for...

In this paper we study bulk shipping of coal between the central regions in the world. We compare the performance of cost-minimizing models with a gravity model approach. The main finding in the paper is that cost minimizing models provide relative poor fits to data. A simple one parameter...

Time series models for count data have found increased interest in recent days. The existing literature refers to the case of data that have been fully observed. In the present paper, methods for estimating the parameters of the first-order integer-valued autoregressive model in the presence of...

In this paper a potential problem with tests for Granger-causality is investigated. If one of the two variables under study, but not the other, is measured with error the consequence is that tests of forecastablity of the variable without measurement error by the variable with measurement error...

Two measures of an error-ridden explanatory variable make it possible to solve the classical errors-in-variable problem by using one measure as an instrument for the other. It is well known that a second IV estimate can be obtained by reversing the roles of the two measures. We explore a simple...

In this paper, we propose a likelihood ratio and Markov chain based method to evaluate density forecasting. This method can jointly evaluate the unconditional forecasted distribution and dependence of the outcomes. This method is an extension of the widely applied evaluation method for interval...