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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">10.26794/2587-5671-2025-29-4-163-176</article-id><article-id custom-type="elpub" pub-id-type="custom">finance-3848</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>ЦЕНООБРАЗОВАНИЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>PRICING</subject></subj-group></article-categories><title-group><article-title>Анализ ценообразования российских ипотечных ценных бумаг</article-title><trans-title-group xml:lang="en"><trans-title>Pricing Analysis of Russian Mortgage-Backed Securities</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6834-334X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Панова</surname><given-names>С. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Panova</surname><given-names>S. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Светлана Анатольевна Панова —  доктор технических наук, кандидат экономических наук, кандидат химических наук, профессор кафедры финансовых рынков и финансово го инжиниринга</p><p>Москва</p></bio><bio xml:lang="en"><p>Svetlana A. Panova —  Dr. Sci. (Eng.), Cand. Sci. (Econ.), Cand. Sci. (Chem.), Prof., Department of Financial Markets and Financial Engineering</p><p>Moscow</p></bio><email xlink:type="simple">sapanova@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/0009-0007-6853-7516</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Куимов</surname><given-names>Д. Л.</given-names></name><name name-style="western" xml:lang="en"><surname>Kuimov</surname><given-names>D. L.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Дмитрий Леонидович Куимов —  главный специалист подразделения «Планирование и сопровождение розничного бизнеса»</p><p>Москва</p></bio><bio xml:lang="en"><p>Dmitry L. Kuimov —  Chief specialist of Retail business planning and support division</p><p>Moscow</p></bio><email xlink:type="simple">kuimovd@bk.ru</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4606-1226</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Переход</surname><given-names>С. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Perekhod</surname><given-names>S. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сергей Александрович Переход —  заведующий лабораторией «Фининвест»</p><p>Москва</p></bio><bio xml:lang="en"><p>Sergey A. Perekhod —  head of laboratory “Fininvest”</p><p>Moscow</p></bio><email xlink:type="simple">saperekhod@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 при Правительстве Российской Федерации</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Financial University under the Government of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>АО «Банк ДОМ.РФ»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>JSC  “Bank DOM.RF”</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>31</day><month>08</month><year>2025</year></pub-date><volume>29</volume><issue>4</issue><fpage>163</fpage><lpage>176</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Панова С.А., Куимов Д.Л., Переход С.А., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Панова С.А., Куимов Д.Л., Переход С.А.</copyright-holder><copyright-holder xml:lang="en">Panova S.A., Kuimov D.L., Perekhod S.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/3848">https://financetp.fa.ru/jour/article/view/3848</self-uri><abstract><p>Стремительный рост рынка ипотечного кредитования в последние годы привел к увеличению объемов эмиссии ипотечных облигаций, которые, с одной стороны, представляют собой объект инвестирования, а с другой —  источник фондирования для банковского сектора. В 2023 г. общий объем ипотечного кредитования в России достиг 4 трлн руб., что на 25% больше по сравнению с предыдущим годом. Опыт финансового инжиниринга, приведшего к ипотечному кризису в 2008 г. в США, высокая волатильность российского фондового рынка и ставки Банка России, которые достигли 21% в 2024 г., актуализировали исследование рисков секьюритизации. Цель исследования —  определить ключевые факторы, влияющие на цену российских ипотечных облигаций. Методом наименьших квадратов была построена модель со значимыми показателями: отношение суммы непогашенных обязательств к расчетной общей сумме обязательств; доля кредитов с просроченной задолженностью, взвешенной по объему непогашенной задолженности; спред между ставкой кредита, входящей в пул и взвешенной по объему непогашенной задолженности, и средневзвешенной ставкой по ипотечным кредитам; спред между доходностью ипотечных облигаций и доходностью по 10 гособлигациям. Полученные результаты позволили сделать вывод, что данные факторы существенно влияют на ценообразование ИЦБ и могут быть использованы на практике инвесторами и регулятором для более точного прогнозирования цен на ипотечные облигации.</p></abstract><trans-abstract xml:lang="en"><p>The rapid growth of the mortgage lending market in recent years has resulted in an increase in the issuance of mortgage bonds, which, on the one hand, represent an object of investment and, on the other hand, a source of funding for the banking sector. In 2023, the total volume of mortgage lending in Russia reached 4 trillion rubles, an increase of 25% compared to the previous year. The experience of financial engineering that led to the mortgage crisis in 2008 in the USA, the high volatility of the Russian stock market and the Bank of Russia rates that reached 21% in 2024 have actualized the study of securitization risks. The purpose of this study is to identify the key factors affecting the price of Russian mortgage bonds. The least squares method was used to create a model based on significant indicators: the ratio of outstanding liabilities to the estimated total liabilities; the proportion of overdue loans, weighted by outstanding debt; the spread between the pooled loan rate, weighted by the volume of outstanding debt, and the weighted average mortgage rate; the spread between the yield on mortgage bonds and the yield on 10-year government bonds. The results obtained led to the conclusion that these factors significantly affect the pricing of MBS and can be utilized by investors and the regulators to more accurately forecast prices for mortgage bonds.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>ипотечные облигации</kwd><kwd>ипотечное кредитование</kwd><kwd>секьюритизация</kwd><kwd>ипотека</kwd><kwd>ипотечные активы</kwd><kwd>оценка стоимости ценных бумаг</kwd></kwd-group><kwd-group xml:lang="en"><kwd>mortgage-backed securities</kwd><kwd>mortgage lending</kwd><kwd>securitization</kwd><kwd>mortgage</kwd><kwd>mortgage assets</kwd><kwd>valuation of  securities</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">Гусева М. Оценки равновесной структуры кредитования для России. Деньги и кредит. 2022;81(4):34–51.</mixed-citation><mixed-citation xml:lang="en">Guseva M. 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