| Issue |
E3S Web Conf.
Volume 175, 2020
XIII International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness – INTERAGROMASH 2020”
|
|
|---|---|---|
| Article Number | 12006 | |
| Number of page(s) | 6 | |
| Section | Environmental Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202017512006 | |
| Published online | 29 June 2020 | |
Enterprise growth simulation model
Don State Technical University, 1, Gagarin Square, 344003, Rostov-on-Don, Russia
* Corresponding author: avlas333@mail.ru
Simulation mathematical model of small enterprise functioning is under analysis in this article. It is assumed that annual working capital profitability and loan rate are random variables with normal distribution, the amount of borrowed capital does not exceed the amount of own working capital. Given the value of its working capital at the beginning of time, its dependence on time is constructed as a random process. The parameters of random variables are estimated based on the processing of statistical data on the previous activities of this enterprise. The implementation of the random process is statistically modeled. With the help of the statistical tests, implementations of random function of growth of own working capital are built and the probability of bankruptcy is estimated as relative frequency of cases of adoption of negative value by random function. It is proposed to use the built simulation model of the enterprise to estimate the probability of bankruptcy of the studied enterprise in the coming period (a given number ofyears).
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.