IDEAS home Printed from https://ideas.repec.org/a/scn/accntn/y2018i1p44-55.html
   My bibliography  Save this article

Научно-методический аспект учета рисков организации // Scientific and Methodological Aspectsof Risk Accounting in an Organization

Author

Listed:
  • Tat’yana Serebryakova Yur’evna

    (Cheboksary cooperative institute (branch) of Russian University of Cooperation)

  • Татьяна Серебрякова Юрьевна

    (Чебоксарский кооперативный институт (филиал) Российского университета кооперации)

Abstract

Subject. The article deals with the current trend towards applying the risk-based approach to all managerial and control processes. It systemizes the basic models of risk management and their elements, analyzes the rules of risk accounting applied in tax and financial accounting and eventually concludes that existing standards of risk management do not contain requirements to risk accounting and that risk accounting for financial and tax accounting purposes does not take into consideration the tasks of risk management. Purpose. The objective of the research is to study the category of accounting as a tool of risk management in order to understand the importance and necessity of risk accounting in a special accounting system and to determine the main principles for such accounting. Methodology. The author uses general scientific methods of cognition: a systematic approach, logic synthesis, legal analysis, linguistic analysis, hypothesis. Results. To manage risk means to control it and take prompt actions. Control is not possible without taking into account the object of control and its special features. To account for risks it is necessary to build a system in which the object of accounting would be risks. Strictly speaking, risk by itself is not a financial indicator. In the system of financial accounting of risks the accounting object should be the anticipated consequences of risks, expressed in monetary terms. All accounting systems are based on the goals, events and indicators that are subject to monitoring. The same principles can be used as a foundation for a system of risk accounting in monetary terms, where the accounting unit would be positive and negative consequences of events that carry risk. Conclusions. It is necessary to create a special system of risk accounting based on the principles of modeling, balance generalization, evaluation and double entry. On the basis of risk management understanding and the author’s classification of the events involving risks the article makes proposals about the organization of risk accounting for risk management purposes. Предмет. Статья посвящена наблюдающейся в последние десятилетия тенденции риск-ориентированного подхода ко всем управленческо-контрольным процессам. Систематизированы основные модели риск-менеджмента и составляющие их элементы, проанализированы применяемые в бухгалтерском и налоговом учете правила учета рисков, что позволило в итоге сделать вывод об отсутствии в имеющихся стандартах риск-менеджмента требований к учету рисков, а тот учет рисков, который имеет место в бухгалтерском и налоговом учете, осуществляется вне задач менеджмента рисков. Цель. Поставлена цель - исследовать категорию «учет» как инструмент управления рисками для понимания важности и необходимости учета рисков в специальной учетной системе и определения основных принципов такого учета. Методология. В работе использовались общенаучные методы познания: системный подход, логическое обобщение, правовой, лингвистический анализ, гипотеза. Результаты. Управлять рисками - значит их контролировать и своевременно воздействовать. Контроль невозможен без учета объекта контроля, его характерных показателей. Для учета рисков необходимо построить такую систему, в которой объектом учета были бы риски. Однако сами по себе риски не являются, безусловно, финансовым показателем. Если же говорить о финансовой учетной системе рисков, то объектом учета должны стать предполагаемые последствия рисков, выраженные в денежной форме. Любые учетные системы основываются на целях, событиях и показателях, подверженных контролю. На этих же принципах можно построить систему учета рисков в денежном выражении, учетной единицей в которой будут выступать негативные и позитивные последствия событий, несущих риски. Выводы. Необходимо создание собственной учетной системы рисков на принципах моделирования, балансового обобщения, оценки и двойной записи. Основываясь на понимании риск-менеджмента и авторской классификации событий, провоцирующих риски, сделаны предложения по организации учета рисков для целей управления ими.

Suggested Citation

  • Tat’yana Serebryakova Yur’evna & Татьяна Серебрякова Юрьевна, 2018. "Научно-методический аспект учета рисков организации // Scientific and Methodological Aspectsof Risk Accounting in an Organization," Учет. Анализ. Аудит // Accounting. Analysis. Auditing, ФГОБУВО "Финансовый университет при Правительстве Российской Федерации" // Financial University under The Government of Russian Federation, vol. 5(1), pages 44-55.
  • Handle: RePEc:scn:accntn:y:2018:i:1:p:44-55
    as

    Download full text from publisher

    File URL: https://accounting.fa.ru/jour/article/viewFile/219/220.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pierre Giot & Sébastien Laurent, 2003. "Value-at-risk for long and short trading positions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
    2. Jeremy C. Stein & Stephen E. Usher & Daniel LaGattuta & Jeff Youngen, 2001. "A Comparables Approach To Measuring Cashflow‐At‐Risk For Non‐Financial Firms," Journal of Applied Corporate Finance, Morgan Stanley, vol. 13(4), pages 100-109, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    2. Brooks, Robert, 2007. "Power arch modelling of the volatility of emerging equity markets," Emerging Markets Review, Elsevier, vol. 8(2), pages 124-133, May.
    3. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    4. Jeroen Rombouts & Marno Verbeek, 2009. "Evaluating portfolio Value-at-Risk using semi-parametric GARCH models," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 737-745.
    5. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    6. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    7. Grané, Aurea & Veiga, Helena, 2010. "Outliers in Garch models and the estimation of risk measures," DES - Working Papers. Statistics and Econometrics. WS ws100502, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    9. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    10. Matthew Pritsker, 2001. "The hidden dangers of historical simulation," Finance and Economics Discussion Series 2001-27, Board of Governors of the Federal Reserve System (U.S.).
    11. Alexander, Carol & Sheedy, Elizabeth, 2008. "Developing a stress testing framework based on market risk models," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2220-2236, October.
    12. Mr. Selim A Elekdag & Sheheryar Malik & Ms. Srobona Mitra, 2019. "Breaking the Bank? A Probabilistic Assessment of Euro Area Bank Profitability," IMF Working Papers 2019/254, International Monetary Fund.
    13. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Bernardo León & Andrés Mora, 2011. "CDS: relación con índices accionarios y medida de riesgo," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(64), pages 178-211, July.
    15. Pitera, Marcin & Schmidt, Thorsten, 2018. "Unbiased estimation of risk," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 133-145.
    16. Stavros Degiannakis & Alexandra Livada & Epaminondas Panas, 2008. "Rolling-sampled parameters of ARCH and Levy-stable models," Applied Economics, Taylor & Francis Journals, vol. 40(23), pages 3051-3067.
    17. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    18. Haas, Markus, 2008. "The autocorrelation structure of the Markov-switching asymmetric power GARCH process," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1480-1489, September.
    19. Laura Garcia‐Jorcano & Alfonso Novales, 2021. "Volatility specifications versus probability distributions in VaR forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 189-212, March.
    20. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:scn:accntn:y:2018:i:1:p:44-55. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Алексей Скалабан (email available below). General contact details of provider: http://accounting.fa.ru .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.