The ability of financial markets to bear risk is central to economic welfare and stability. Growth and economic wellbeing is inhibited if financial markets are unable to transfer resources efficiently from the suppliers of liquiditz to entrepreneurs.

The word “TENSOR” in this project is understood as a multidimensional linear array of a rectangular shape, whose entries are either real or complex numbers. Such data structures are encountered, e.g., in chemometrics, telecommunication, biomedicine (fMRI, EEG) , data mining, kinetic theory of descriptions of materials, and so on.

Economic and financial activities are often influenced simultaneously by a decision and random factors. Since the decision parameter must be constructed mostly without knowledge of a random element realization, an optimization problem depending on a probability measure corresponds to this situation. Usually in applications this measure must be replaced by an empirical one.

Decision making (DM) is a targeted choice of actions based on given knowledge and preferences. Normatively, Bayesian DM, maximising expected utility, should be used under uncertainty but this happens less than desirable. Often, imperfection of the DM participant can be blamed as it limits the deliberation effort spent.