We introduce a novel criterion for performance measure combination designed to be used as an equity screening algorithm. The proposed approach follows the general idea of linearly combining existing performance measures with positive weights and the combination weights are determined by means of...

In the trade policy debate, the complete liberalisation of world trade for agricultural products is one of the most relevant issues. European Union is a free trade area where agricultural products are protected and supported from the world market forces, more than any other good or service. The...

We investigate in this paper differences in productive efficiency across sixteen European countries. In order to assess differences in productive efficiency, we have built a dynamic input-output model and computed for each country the balanced growth rate and the balanced output composition....

We consider an agent who has to repeatedly make choices in an uncertain and changing environment, who has full information of the past, who discounts future payoffs, but who has no prior. We provide a learning algorithm that performs almost as well as the best of a given finite number of experts...

The Analytic Hierarchy Process (Saaty 1977, 1980) is a decision-making procedure for establishing priorities in multi-criteria decision making. Underlying the AHP is the theory of ratio-scale measures developed by psychophysicist Stanley S. Stevens (1946, 1951) in the middle of the last century....

The Analytic Hierarchy Process (AHP) ratio-scaling approach is re-examined in view of the recent developments in mathematical psychology based on the so-called separable representations. The study highlights the distortions in the estimates based on the maximum eigenvalue method used in the AHP...

This paper introduces a mixture model based on the beta distribution, without preestablished means and variances, to analyze a large set of Beauty-Contest data obtained from diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a better t of the experimental data, and more...

Minimax lower bounds for concept learning state, for example, that for each sample size $n$ and learning rule $g_n$, there exists a distribution of the observation $X$ and a concept $C$ to be learnt such that the expected error of $g_n$ is at least a constant times $V/n$, where $V$ is the VC...

The classical binary classification problem is investigated when it is known in advance that the posterior probability function (or regression function) belongs to some class of functions. We introduce and analyze a method which effectively exploits this knowledge. The method is based on...

This paper presents a theoretical framework to model the evolution of a portfolio whose weights vary over time. Such a portfolio is called a dynamic portfolio. In a first step, considering a given investment policy, we define the set of the investable portfolios. Then, considering portfolio...