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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">proanaris</journal-id><journal-title-group><journal-title xml:lang="ru">Проблемы анализа риска</journal-title><trans-title-group xml:lang="en"><trans-title>Issues of Risk Analysis</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1812-5220</issn><issn pub-type="epub">2658-7882</issn><publisher><publisher-name>ФГБУ ВНИИ ГОЧС (ФЦ)</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.32686/1812-5220-2017-14-4-68-75</article-id><article-id custom-type="elpub" pub-id-type="custom">proanaris-97</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>УПРАВЛЕНИЕ КРЕДИТНЫМ РИСКОМ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>CREDIT RISK MANAGEMENT</subject></subj-group></article-categories><title-group><article-title>Модели оценки кредитных</article-title><trans-title-group xml:lang="en"><trans-title>THE MODELS OF CREDIT RISK ASSESSMENT</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Арис</surname><given-names>Е. Т.</given-names></name><name name-style="western" xml:lang="en"><surname>Aris</surname><given-names>E. T.</given-names></name></name-alternatives><email xlink:type="simple">ekaterinaaris@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Московский финансово- промышленный университет «Синергия»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Synergy University, Moscow</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2017</year></pub-date><pub-date pub-type="epub"><day>09</day><month>10</month><year>2018</year></pub-date><volume>14</volume><issue>4</issue><fpage>68</fpage><lpage>75</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Арис Е.Т., 2018</copyright-statement><copyright-year>2018</copyright-year><copyright-holder xml:lang="ru">Арис Е.Т.</copyright-holder><copyright-holder xml:lang="en">Aris E.T.</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://www.risk-journal.com/jour/article/view/97">https://www.risk-journal.com/jour/article/view/97</self-uri><abstract><p>Статья посвящена обзору моделей, которые позволяют оценивать кредитный риск. В ли- тературе существует два вида моделей, посвященных кредитным рискам: это струк- турные и редуцированные кредитные модели (модели упрощенной формы, reduced form models). Моделирование дефолта лежит в основе исследования кредитного риска. Структурные модели подразумевают, что вероятность дефолта зависит от рыночной стоимости компании: дефолт происходит, если стоимость падает ниже порогового зна- чения. К таким моделям можно отнести модель Мертона, модель Блэка и Кокса, модель Васичека, CreditMetricsТМ, KMV, которые подробно рассмотрены в статье. Второй подход к моделированию - редуцированный - предполагает стохастические вероятности де- фолта, не зависящие от стоимости фирмы. В статье рассматриваются модели CreditRisk+ и CreditPortfolio View, относящиеся к данному типу моделей.</p></abstract><trans-abstract xml:lang="en"><p>The purpose of this Article is to present overview of models which help to assess credit risks. The methodology for modelling a credit event can be split into two main approaches: the structural approach and the reduced form approach. The basic of credit risk assessment is the concept of default. The structural approach framework, the probability of default depends on the market value of the company: if the value of the company falls below the threshold — the default occurs. There are models of authors: Merton, Black &amp; Cox, Vasicek, CreditMetrics, KMV; are consider in the article. The second approach is based on the computation of the «hazard process»: the probability of default not depends on the market value of the company. In the article we focus on CreditRisk+ &amp; CreditPortfolio models.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>кредитный риск</kwd><kwd>модель Мертона</kwd><kwd>модель Васичека</kwd><kwd>модель KMV</kwd><kwd>модель Credit- MetricsТМ</kwd><kwd>модель CreditRisk+</kwd><kwd>модель CreditPortfolio View</kwd></kwd-group><kwd-group xml:lang="en"><kwd>credit risk assessment</kwd><kwd>Merton</kwd><kwd>Vasicek</kwd><kwd>KMV Model</kwd><kwd>CreditMetrics</kwd><kwd>CreditRisk+</kwd><kwd>CreditPortfolio View</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Monique Jeanblanc, Yann Lecam. Reduced form Model- ling for Credit Risk. (November 12, 2007), 21с http://www. maths.univ-evry.fr/prepubli/260.pdf</mixed-citation><mixed-citation xml:lang="en">Monique Jeanblanc, Yann Lecam. Reduced form Model- ling for Credit Risk. 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