Probabilistic model of limited period liquidity goods sales dynamics-Reference-Cited by-同舟云学术

Probabilistic model of limited period liquidity goods sales dynamics

Published:2023-11-09 Issue:4 Volume:2023 Page:68-80
ISSN:2072-9502
Container-title:Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics
language:en
Short-container-title:

Author:

Mikheev Andrej Vyacheslavovich¹

Affiliation:

1. Kazan National Research Technological University

Abstract

A probabilistic approach to accounting the impact of a limited period of liquidity on the volume of goods sales has been developed. The approach is based on the assumption of the random nature of economic factors deter-mining the sales dynamics of goods: production moments, purchases moments, liquidity period, quantity of goods and number of consumers. Analytical expressions for the probability function and expected value of the time dependence of the quantity of sold goods in two cases were found: without taking into account and with taking into account the moments of goods production. Numerical modelling of the dynamics of the expected value of the quantity of sold goods is carried out. It is shown that as the number of buyers grows, the market of goods becomes more and more manageable, as the real dynamics of the quantity of sold goods and the dynamics of the expected value of this quantity cease to differ from each other. The general patterns of the joint effect of the parameters of probabilistic distribution laws of the five economic factors mentioned above on the value and dynamics of the sales volume of goods were determined. Within the framework of the proposed probabilistic model, a time dependence approximating the real dynamics of sales of Lada Vesta cars on the Russian market in the period from October 2015 to May 2023 were found.

Publisher

Astrakhan State Technical University

Subject

General Medicine

Reference7 articles.

1. Пионткевич Н. С., Шатковская Е. Г., Долгих Ю. А. и др. Финансовый анализ: учеб. пособие. Екатеринбург: Изд-во Урал. ун-та, 2022. 190 с., Piontkevich N. S., Shatkovskaia E. G., Dolgikh Iu. A.i dr. Finansovyi analiz: uchebnoe posobie [Financial Analysis: Textbook]. Ekaterinburg, Izd-vo Ural. un-ta, 2022. 190 p.

2. Тюленева Н. А. Современная методика анализа ликвидности бухгалтерского баланса // Проблемы учета и финансов. 2013. № 4 (12). С. 61–65., Tiuleneva N. A. Sovremennaia metodika analiza lik-vidnosti bukhgalterskogo balansa [Modern methodology for analyzing the liquidity of the balance sheet]. Problemy ucheta i finansov, 2013, no. 4 (12), pp. 61-65.

3. Barardehi Y. H., Bernhardt D., Davies R. J. Trade-Time Measures of Liquidity // The Review of Financial Studies. 2019. V. 32, no. 1. P. 126–179., Barardehi Y. H., Bernhardt D., Davies R. J. TradeTime Measures of Liquidity. The Review of Financial Studies, 2019, vol. 32, no. 1, pp. 126-179.

4. Papoulis A., Pillai U. Probability, random variables and stochastic processes. N. Y.: McGraw-Hill, 2002. 852 p., Papoulis A., Pillai U. Probability, random variables and stochastic processes. New York, McGraw-Hill, 2002. 852 p.

5. Olver F. W. J., Lozier D. W., Boisvert R. F., Clark C. W. NIST Handbook of Mathematical Functions. Cambridge; N. Y.; Melbourne: Cambridge University Press, 2010. 951 p., Olver F. W. J., Lozier D. W., Boisvert R. F., Clark C. W. NIST Handbook of Mathematical Functions. Cambridge; New York; Melbourne, Cambridge University Press, 2010. 951 p.