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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">finance</journal-id><journal-title-group><journal-title xml:lang="ru">Финансы: теория и практика/Finance: Theory and Practice</journal-title><trans-title-group xml:lang="en"><trans-title>Finance: Theory and Practice</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2587-5671</issn><issn pub-type="epub">2587-7089</issn><publisher><publisher-name>Financial University under The Government of Russian Federation</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26794/2587-5671-2019-23-6-117-130</article-id><article-id custom-type="elpub" pub-id-type="custom">finance-931</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ФИНАНСОВАЯ БЕЗОПАСНОСТЬ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>FINANCIAL SECURITY</subject></subj-group></article-categories><title-group><article-title>Использование фрактальных моделей ценовой динамики активов в целях управления финансовыми рисками</article-title><trans-title-group xml:lang="en"><trans-title>Fractal Asset Pricing Models for Financial Risk Management</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8684-1684</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ярыгина</surname><given-names>И. З.</given-names></name><name name-style="western" xml:lang="en"><surname>Yarygina</surname><given-names>I. Z.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ирина Зотовна Ярыгина — доктор экономических наук, профессор, профессор Департамента мировой экономики и мировых финансов</p></bio><bio xml:lang="en"><p>Irina Z. Yarygina — Dr. Sci. (Econ.), Professor, Department of World Economy and World Finance</p></bio><email xlink:type="simple">jiz4@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7269-0587</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гисин</surname><given-names>В. Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Gisin</surname><given-names>V. B.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Владимир Борисович Гисин — кандидат физико-математических наук, профессор, заведующий кафедрой информационной безопасности</p></bio><bio xml:lang="en"><p>Vladimir B. Gisin — Cand. Sci. (Math.), Professor, Head of the Chair of Information Security</p></bio><email xlink:type="simple">vgisin@fa.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3330-9819</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Путко</surname><given-names>Б. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Putko</surname><given-names>B. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Борис Александрович Путко — кандидат физико-математических наук, доцент, доцент Департамента анализа данных, принятия решений и финансовых технологий</p></bio><bio xml:lang="en"><p>Boris A. Putko — Cand. Sci. (Math.), Associate Professor, Department of Data Analysis, Decision Making, and Financial Technologies</p></bio><email xlink:type="simple">baputko@fa.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Финансовый университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Financial University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2019</year></pub-date><pub-date pub-type="epub"><day>24</day><month>12</month><year>2019</year></pub-date><volume>23</volume><issue>6</issue><fpage>117</fpage><lpage>130</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ярыгина И.З., Гисин В.Б., Путко Б.А., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Ярыгина И.З., Гисин В.Б., Путко Б.А.</copyright-holder><copyright-holder xml:lang="en">Yarygina I.Z., Gisin V.B., Putko B.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://financetp.fa.ru/jour/article/view/931">https://financetp.fa.ru/jour/article/view/931</self-uri><abstract><p>Представлены результаты анализа проблем и перспектив использования теории фрактального рынка в целях математического прогнозирования ценовой динамики активов в рамках реализации стратегии управления финансовыми рисками. Цель статьи — раскрытие особенностей стоимости банковских активов и разработка рекомендаций, направленных на оценку финансовых рисков на базе использования математических методов прогнозирования экономических процессов. Использованы теоретические и эмпирические методы исследования. Раскрыты особенности математического моделирования экономических процессов, связанных с ценообразованием активов в условиях волатильного рынка. Доказано, что использование финансовой математики в банковской практике способствует формированию условий стабильного развития экономики. Методы математического моделирования ценовой динамики финансовых активов строятся на содержательной гипотезе и подкрепляются использованием адекватного аппарата фрактальных парных моделей ценообразования в целях раскрытия особенностей рыночных отношений субъектов хозяйствования. По мнению авторов, использование прогнозных моделей в целях минимизации финансовых рисков производных финансовых инструментов имеет хорошие перспективы. Сделан вывод, что использование рассматриваемых методик способствует управлению финансовыми рисками и улучшению прогнозов, в том числе операций с  деривативами. Кроме того, параметры фрактальной волатильности, исследуемые в  работе, показали предсказательную силу относительно экстремальных явлений на финансовых рынках, таких как крах американского инвестиционного банка LehmanBrothers в 2008 г. Актуальность статьи обусловлена тем, что благоприятный инвестиционный климат и использование современных методов финансирования во многом зависят от эффективного управления финансовыми рисками.</p></abstract><trans-abstract xml:lang="en"><p>The article presents the analysis findings of the problems and prospects of using the fractal markets theory to mathematically predict the price dynamics of assets as part of a financial risk management strategy. The aim of the article is to find out the features of value of bank assets and to develop recommendations for assessing financial risks based on mathematical methods for forecasting economic processes. Theoretical and empirical research methods were used to achieve the aim. The article reveals the features of mathematical modeling of economic processes related to asset pricing in a volatile market. It was proved that using financial mathematics in banking contributes to the stable development of the economy. Mathematical modeling of the price dynamics of financial assets is based on a substantive hypothesis and supported by an adequate apparatus of fractal pair pricing models in order to reveal specific market relations of business entities. According to the authors, the prospects of using forecast models to minimize the financial risks of derivative financial instruments are positive. The authors concluded that the considered methods contribute to managing financial risks and improving forecasts, including operations with derivatives. Besides, the studied fractal volatility parameters proved the predictive power regarding extreme events in financial markets, such as the bankruptcy of Lehman Brothers investment bank in 2008. The relevance of the article is due to the fact that the favorable investment climate and the use of modern financing methods largely depend on the effective financial risk management.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>банковская деятельность</kwd><kwd>оценка стоимости активов</kwd><kwd>экономико-математические методы</kwd><kwd>управление финансовыми рисками</kwd><kwd>хеджирование</kwd></kwd-group><kwd-group xml:lang="en"><kwd>banking</kwd><kwd>asset valuation</kwd><kwd>economic and mathematical methods</kwd><kwd>financial risk management</kwd><kwd>hedging</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Статья подготовлена по результатам исследований, выполненных за счет бюджетных средств по государственному заданию Финуниверситету в рамках НИР по теме «Механизмы создания в базовых отраслях экономики Российской Федерации высокопроизводительного экспортно ориентированного сектора в рамках глобальных дезинтеграционных и евразийских интеграционных процессов». Финансовый университет, Москва, Россия.</funding-statement><funding-statement xml:lang="en">The article is based on the results of budgetary-supported research according to the state task carried out by the Financial University as part of research on the topic “Mechanisms for creating a highly productive export-oriented sector among the basic sectors of the economy of the Russian Federation within the global disintegration and Eurasian integration processes”. Financial University, Moscow, Russia.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Mandelbrot B.B., Van Ness J.W. Fractional Brownian motion, fractional noises and applications. SIAM Review. 1968;10(4):422–437. DOI: 10.1137/1010093</mixed-citation><mixed-citation xml:lang="en">Mandelbrot B.B., Van Ness J.W. Fractional Brownian motion, fractional noises and applications. 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