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«Финансовая аналитика: проблемы и решения»
 

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ЭКОНОМИЧЕСКИЕ НАУКИ:
5.2.1. Экономическая теория
5.2.3. Региональная и отраслевая экономика
5.2.4. Финансы
5.2.5. Мировая экономика
5.2.6. Менеджмент


ЭКОНОМИЧЕСКИЕ,
ФИЗИКО-МАТЕМАТИЧЕСКИЕ НАУКИ:
5.2.2. Математические, статистические и инструментальные методы в экономике

Реферирование и индексирование

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Referativny Zhurnal VINITI RAS
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Biblioclub

Evaluating the effectiveness of companies' financial policies using logistic regression: A case study of electric power companies

т. 14, вып. 2, июнь 2021

Получена: 11.02.2021

Получена в доработанном виде: 22.02.2021

Одобрена: 08.03.2021

Доступна онлайн: 28.05.2021

Рубрика: МОНИТОРИНГ ЭКОНОМИЧЕСКИХ ПРОЦЕССОВ

Коды JEL: G3, G17, G32, M21

Страницы: 208–217

https://doi.org/10.24891/fa.14.2.208

Kirill E. PIVNYK Plekhanov Russian University of Economics (PRUE), Moscow, Russian Federation 
kirillpivnyk@gmail.com

Subject. This article assesses the effectiveness of companies' financial policies using logistic regression. It considers the financial policy assessment as a comprehensive analysis that helps evaluate the company's financial performance and make a conclusion based on a single criterion.
Objectives. The article aims to develop a single (universal) criterion helping conclude of the company's financial policy effectiveness.
Methods. For the study, I used a comprehensive approach based on the developed logit model, financial analysis, systems approach, and an overview of literature sources on the subject.
Results. The article presents a developed methodology for evaluating the effectiveness of financial policy determined by the effectiveness of financial policy (EFP) equation for Russian electric power companies.
Relevance. The results obtained can be used in practice to evaluate the financial policy by company external and internal users.

Ключевые слова: company, financial policy, logistic regression, performance assessment, analysis

Список литературы:

  1. Pivnyk K.E. [Creating a group of financial ratios to evaluate financial policy of companies]. Finansy i kredit = Finance and Credit, 2020, vol. 26, iss. 5, pp. 1039–1053. (In Russ.) URL: Link
  2. Zhdanov V.Yu., Afanas'eva O.A. [Bankruptcy risk diagnostics model for aviation enterprises]. Korporativnye finansy, 2011, no. 4, pp. 77–89. (In Russ.) URL: Link
  3. Khaidarshina G.A. [The efficiency of the modern bankruptcy risk evaluation methods in the Russian practice of financial management: logit- and SVM-models]. Ekonomicheskie nauki = Economic Sciences, 2008, no. 7, pp. 300–304. URL: Link (In Russ.)
  4. Ohlson J.A. Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 1980, vol. 18, iss. 1, pp. 109–131. URL: Link
  5. Saati T. Prinyatie reshenii. Metod analiza ierarkhii [Decision Making. Hierarchy Analysis Method]. Moscow, Radio i svyaz' Publ., 1993, 314 p.
  6. Malykhin A.L., Gorokhov A.A., Nokhrina T.A. Optimal'noe chislo sushchestvuyushchikh priznakov pri opisanii slozhnykh ob"ektov: Problemy teorii i praktiki menedzhmenta: sbornik statei. Vyp. 2 [The optimal number of existing features when describing complex objects: Problems of management theory and practice: a collection of articles. Iss. 2]. Tyumen, TSU Publ., 2000.
  7. Slepov V.A., Pivnyk K.E. [Evaluating the effectiveness of financial policy of companies using the generalized Harrington's function]. Finansy i kredit = Finance and Credit, 2020, vol. 26, iss. 2, pp. 270–284. (In Russ.) URL: Link

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ISSN 2311-8768 (Online)
ISSN 2073-4484 (Print)

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т. 17, вып. 3, сентябрь 2024

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