This note presents an algorithm that extends a binary choice model to choice among multiple alternatives. Both neoclassical microeconomic theory and Luce choice model are consistent with the proposed algorithm. The algorithm is compatible with several empirical findings (asymmetric dominance and...

We investigate whether alternative asset classes should be included in optimal portfolios of the most prominent investor personae in the Behavioral Finance literature, namely, the Cumulative Prospect Theory, the Markowitz and the Loss Averse types of investors. We develop a stochastic spanning...

We propose a new parametrization of Quantum Decision Theory (QDT), based on Rank Dependent Utility Theory (RDU). Using experimental data made of choices between pairs of lotteries, we compare QDT with "classical" decision theories, RDU and Cumulative Prospect Theory (CPT). At the aggregate...

We investigate whether alternative asset classes should be included in optimal portfolios of the most prominent investor personae in the Behavioral Finance literature, namely, the Cumulative Prospect Theory, the Markowitz and the Loss Averse types of investors. We develop a stochastic spanning...

A decision maker, named Alice, wants to know if an expert has significant information about payoff-relevant probabilities of future events. The expert, named Bob, either knows this probability almost perfectly or knows nothing about it. Hence, both Alice and the uninformed expert face...

Visualization is not only an important part of experimental data analysis process but also an efficient tool for transfer of acquired knowledge in multiple areas including, but not restricted to, ICT, general scientific discussion, innovation, data mining, decision support systems as well as...

We study sequential search without priors. Our interest lies in decision rules that are close to being optimal under each prior and after each history. We call these rules robust. The search literature employs optimal rules based on cutoff strategies, and these rules are not robust. We derive...

The goal programming (GP) is a well-known approach applied to multi-criteria decision making (M-DM). It has been used in many domains and the literature offers diverse extensions of this procedure. On the other hand, so far, some evident analogies between M-DM under certainty and scenario-based...

This paper derives a robust online equity trading algorithm that achieves the greatest possible percentage of the final wealth of the best pairs rebalancing rule in hindsight. A pairs rebalancing rule chooses some pair of stocks in the market and then perpetually executes rebalancing trades so...

This paper formulates and solves an economic decision problem of the acquisition of costly information in data-driven decision making. The paper assumes an agent predicting a random variable utilizing several costly explanatory variables. Prior to the decision making, the agent learns about the...