**:** ..
**:** CC-VaR

**:** 100
**:**
**:** 2022
**:** .. CC-VaR // . 100. .: , 2022. .36-58. DOI: https://doi.org/10.25728/ubs.2022.100.2

** :** , VaR (CC-VaR), (...), , , ࠖ, , ,

** (.):** underliers, continuous VaR-criterion (CC-VaR), risk preferences function (r.f.p.), forecast and cost densities, returns relative function, Newman-Pearson procedure, forecast and cost functions, randomization, combine portfolio, idealistic portfolio.

**:** VaR (CC-VaR) . , , ⠖ . . , . , . CC-VaR CB, , (...) , CC-VaR. , , -. . , .

** (.):** The work continues studying application of the continuous VaR-criterion (CC-VaR) in a collection of financial markets. This time the theoretical generality of the approach supposed before is tested on some more complicated collection of three multidimensional theoretical option markets, one of which is two-dimensional and two are two-dimensional. However, now some qualitative new in principle technical problems must to be solved. The randomization of basis structure for model feasibility is necessary as well, but is conducted for two-dimensional markets. At forming initial data with full analytical description, the econometric approach added by heuristic constructions is used. Here the more convenient for CC-VaR problemCB with the unknown initial investment amount and risk preferences functions not depended on scale parameter is solved. The regular combined portfolio that achieves the minimum of the general cost with fulfilling the CC-VaR need to be found. For purposes of methods illustration for marginal random values describing forecast and cost data of the problem, beta-distributions are used. In addition, an idealistic version of the optimal portfolio combined of instruments from markets of different dimensions is formed. It allows plotting two-dimension integrated surface income diagrams that overlap two-dimension parts of the optimal portfolio and arbitrary two-dimension sections of its three-dimension part.

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