# IMITATION MODELING FOR THE PURPOSE OF FORMATION OF THE OPTIMUM ASSORTMENT SALES POLICY

## DOI:

https://doi.org/10.22478/ufpb.2179-7137.2019v8n4.48395## Palavras-chave:

simulation modeling, financial stability, scenario analysis, financing strategies, ABC-XYZ analysis, VAR methodology, assortment sales policy## Resumo

Within the framework of the scientific work, the algorithm for formation of an optimal mix of the sold commodity items in the conditions of managing the risk of changing the capital structure and obtaining the required effectiveness of the financial and economic activity of an economic entity is investigated. A methodological algorithm for solving the problem is proposed using the tool of simulation modeling. Consideration of alternative approaches to financing the structure of commodity stocks of an organization taking into account possible scenarios of changing market conditions determining the efficiency of the company's operating activities served as the target for the formation of an array of simulation experiments. Based on the provisions of the corporate finance theory, a functional relationship was established between the productive and factor characteristics of the simulation model. Justification of the author's position on the specific features of the solution of the problem posed stipulated the inclusion in the methodological algorithm of the basics of ABC-XYZ analysis, as well as the VAR toolkit. Analytical processing of the results was based on the interpretation of descriptive statistics indicators, the most important of which was the share of experiments demonstrating the possibility of maintaining the required margin of financial strength, as well as the absolute amount of profit before tax, obtained as a result of the mathematical expectation of profit in conditions of optimistic, probable and pessimistic scenarios### Downloads

## Referências

Abad, P., Benito, S., López, C. (2014) A comprehensive review of Value at Risk methodologies. Spanish Review of Financial Economics. 12 (1), pp.15-32.

Allen, S. (1997) Comparing and contrasting different approaches to computive value at risk. Risk Conference.

Antonelli, S., Iovino , M.G. (2002) Optimization of Monte Carlo procedures for value at risk estimates.Economic Notes. 31 (1), pp.59-78.

Dhoka, D.a (2015) Challenges with multi-dimensional inventory classifications and optimization. Asian Social Science. 11 (4), pp.365-370.

Duffie , D., Pan, J. (1997) An overview of value at risk. Journal of Derivatives. 4 (3). pp. 7-49.

Dyson, R.G., Shale, E.A. (2010) Data envelopment analysis, operational research and uncertainty. Journal of the Operational Research Society. 61 (1). pp. 25-34.

Eppen, Gary D., Matin, R. Kipp, Schrage, Linus (1989) Scenario. Operations Research. 37 (4). pp. 517-527.

Huss, W.R., Honton E.J. (1987) Scenario planning -What style should you use? Long Range Planning.20 (4). pp. 21-29.

Jamshidian, F., Zhu, Y. (1997) Scenario simulation: Theory and methodology. Finance and Stochastics , 1, pp.43-67.

Majewski, G.M., Delak, B., Damij, N. (2014) TK business process simulation: A case study with a Slovenian high-achieving company from the SME sector. Proceeding of the European Conference on Knowledge Management, ECKM. 2. pp.593-608

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## Como Citar

**Gênero & Direito**,

*[S. l.]*, v. 8, n. 4, 2019. DOI: 10.22478/ufpb.2179-7137.2019v8n4.48395. Disponível em: https://periodicos.ufpb.br/ojs2/index.php/ged/article/view/48395. Acesso em: 24 jan. 2022.