MODELO EM PROGRAMAÇÃO NÃO-LINEAR PARA DECISÃO DE ORÇAMENTAÇÃO DE CAPITAL EM STARTUPS

Autores

  • Lucas Rodrigues Escola Superior de Agricultura Luiz de Queiroz (ESALQ/USP) https://orcid.org/0000-0002-4496-0391
  • Alex da Silva Alves Escola Superior de Agricultura Luiz de Queiroz (ESALQ/USP)

DOI:

https://doi.org/10.18028/rgfc.v11i3.9232

Palavras-chave:

Capital Empreendedor, Gradiente Reduzido Generalizado, Programação Não Linear, Pequenas e Médias Empresas, Orçamento

Resumo

Obtenção de informações de mercado e dificuldades de acesso a financiamento externo são tradicionais barreiras para um planejamento financeiro que reflita as oportunidades de crescimento de novas empresas de alta tecnologia em mercados emergentes. Há, ainda, uma carência de estudos que proponham uma abordagem metodológica robusta dessas questões. Este artigo desenvolve dois modelos de apoio à decisão baseados no algoritmo de programação não-linear GRG (Generalized Reduced Gradient), cuja aplicação se dá no contexto da orçamentação de capital em pequenas e médias empresas de alta tecnologia. O modelo foi concebido a partir da elaboração de três demonstrativos financeiros básicos, sendo estes o demonstrativo de resultado do exercício (DRE), a demonstração de fluxo de caixa (DFC) e o balanço patrimonial. O estudo permitiu tecer considerações sobre os trade-offs entre estrutura de capital e valor em empresas de alta tecnologia em mercados emergentes, cujas contribuições podem ser úteis para a comunidade de empreendedores, analistas financeiros, investidores e formuladores de políticas públicas envolvidos em modelagem e planejamento de novos mecanismos de financiamento para startups.

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Publicado

2022-12-30

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