Issue |
EPJ Web Conf.
Volume 248, 2021
V International Conference “Modeling of Nonlinear Processes and Systems“ (MNPS-2020)
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|
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Article Number | 03001 | |
Number of page(s) | 5 | |
Section | Mathematical Models in Economics, Social and Humanitarian Sciences | |
DOI | https://doi.org/10.1051/epjconf/202124803001 | |
Published online | 26 April 2021 |
https://doi.org/10.1051/epjconf/202124803001
Mathematical Estimation Methods and Models for Industrial Companies
Moscow State Technological University “STANKIN”, RU-127055, Moscow, Russia
* Corresponding author: olgitast2011@mail.ru
Published online: 26 April 2021
The collateralized debt obligations and credit default swaps applications are shown in this paper. The industry obligations secondary market risk estimation methods are considered in this work. The new methods taking into account statistically significant parameters for industrial credit derivatives portfolio are offered for single-name investment risks numerical experiments realization. The mathematical estimation of tranche were shown. The single and multiple name default obligations necessary mathematical modeling methods and formulae for the industrial materials manufacturers derivative credit tools market are shown. It is determined that the portfolio of synthetic debt tools is made of the given parameters. The task of a loss derivative tranches mathematical estimation is solved. Late defaults raise the equity tranches payment required sums with high spreads, early defaults reduce. Also the functional characteristics required for an estimation huge debts problem solving are partly considered in this paper. The problem of the default modeling for market tools and numerical simulation of the obligations influence on conditions of current bistability mode are shown here. Some credit derivatives of industrial manufacturers are demonstrated in the modeling process of default as an example. It is found that the model is an additional factor help us to estimate the default opportunity.
© The Authors, published by EDP Sciences, 2021
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