In this study, we address the ambiguity in portfolio optimization, particularly focusing on the uncertainty related to the statistical parameters governing asset returns. We propose a novel method that combines robust optimization with artificial neural networks (ANNs). Our approach effectively...

This paper characterizes those preferences over bounded infinite utility streams that satisfy the time value of money principle and an additivity property, and the subset of these preferences that, in addition, are either impatient or patient. Based on this characterization, the paper introduces...

This paper rationalizes the LASSO algorithm based on uncertain fat-tail priors and max-min robust optimization. Our rationalization excludes heuristic learning or restrictive prior assumptions in the original interpretation of LASSO (Tibshirani (1996)). In our setting, economic agents...

Optimal experimental designs are used in chemical engineering to obtain precise mathematical models. The optimal design consists of design points with a maximal amount of information and thus lead to more precise models than statistical designs. In general, the optimal design depends on an...

We study the problem of integrated pallet retrieval and successive processing in warehouses motivated by a practical company setting. A set of pallets has to be retrieved in a warehouse having a single stacker crane and multiple input/output-points, and the goal is to minimize the makespan....

Optimal experimental designs are used in chemical engineering to obtain precise mathematical models. The optimal design consists of design points with a maximal amount of information and thus lead to more precise models than statistical designs. In general, the optimal design depends on an...

In this paper, we propose a novel optimization model for portfolio selection that integrates the classical mean-variance criterion with a second-order Tsallis entropy term. This approach enables a trade-off between expected return, risk, and diversification, extending Markowitz's theory to...

Recent advances in healthcare technologies have led to the availability of large amounts of biological samples across several techniques and applications. In particular, in the last few years, Raman spectroscopy analysis of biological samples has been successfully applied for early-stage...

Multi-Criteria Decision-Making (MCDM) methods, particularly TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) (Multicriteria Optimization and Compromise Solution), are extensively used in logistics for...

This paper introduces two methodological improvements to the Hodrick- Prescott (HP) filter for decomposing GDP into trend and cycle components. First, we propose a robust univariate filter that accounts for extreme observations - such as the COVID-19 pandemic - by treating them as additive...

How should researchers adjust for covariates? We show that if the propensity score is estimated using a specific covariate balancing approach, inverse probability weighting (IPW), augmented inverse probability weighting (AIPW), and inverse probability weighted regression adjustment (IPWRA)...

How should researchers adjust for covariates? We show that if the propensity score is estimated using a specific covariate balancing approach, inverse probability weighting (IPW), augmented inverse probability weighting (AIPW), and inverse probability weighted regression adjustment (IPWRA)...

Wage growth is a key indicator of labor market conditions, but common measures often conflate individual wage changes with shifts in workforce composition. This paper develops a composition-adjusted measure of wage growth using nonparametric decomposition and program evaluation methods. The...

The presence of autocorrelated financial returns has major implications for investment decisions. Unsurprisingly, therefore, numerous studies have sought to shed light on whether returns are autocorrelated or not, to what extent, and when. Standard tests for autocorrelation rely on the...

We study the impact of a teacher strike on students still in compulsory school and about to choose their secondary education track. Using administrative data and a difference-in-differences approach, we estimate the effect of a regional strike in Finland on educational attainment and long-term...