<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE root>
<article 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" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Economics and Mathematical Methods</journal-id><journal-title-group><journal-title xml:lang="en">Economics and Mathematical Methods</journal-title><trans-title-group xml:lang="ru"><trans-title>Экономика и математические методы</trans-title></trans-title-group></journal-title-group><issn publication-format="print">0424-7388</issn><issn publication-format="electronic">3034-6177</issn><publisher><publisher-name xml:lang="en">The Russian Academy of Sciences</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">653344</article-id><article-id pub-id-type="doi">10.31857/S042473880025861-6</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Articles</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Статьи</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Optimal solution for immunizing arbitrarily scheduled multiple liabilities</article-title><trans-title-group xml:lang="ru"><trans-title>Оптимальное решение задачи иммунизации потока множественных платежей произвольной структуры</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Kurochkin</surname><given-names>Sergey Vladimirovich</given-names></name><name xml:lang="ru"><surname>Курочкин</surname><given-names>Сергей Владимирович</given-names></name></name-alternatives><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="en"><surname>Rodina</surname><given-names>Victoria Alekseevna</given-names></name><name xml:lang="ru"><surname>Родина</surname><given-names>Виктория Алексеевна</given-names></name></name-alternatives><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">HSE University</institution></aff><aff><institution xml:lang="ru">НИУ ВШЭ</institution></aff></aff-alternatives><pub-date date-type="pub" iso-8601-date="2023-06-15" publication-format="electronic"><day>15</day><month>06</month><year>2023</year></pub-date><volume>59</volume><issue>2</issue><issue-title xml:lang="en">VOL 59, NO2 (2023)</issue-title><issue-title xml:lang="ru">ТОМ 59, №2 (2023)</issue-title><fpage>87</fpage><lpage>99</lpage><history><date date-type="received" iso-8601-date="2025-02-03"><day>03</day><month>02</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2023, Russian Academy of Sciences</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2023, Российская академия наук</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="en">Russian Academy of Sciences</copyright-holder><copyright-holder xml:lang="ru">Российская академия наук</copyright-holder></permissions><self-uri xlink:href="https://journals.eco-vector.com/0424-7388/article/view/653344">https://journals.eco-vector.com/0424-7388/article/view/653344</self-uri><abstract xml:lang="en"><p>Immunization, a control tool for interest rate dependent changes in the value of an asset portfolio given a similar dependency for a target liability portfolio, is central to portfolio management. A vast body of academic literature describes various immunization models either for the case of a single liability payout or assuming a specific change in the yield curve, or both. This paper is the first to propose an immunization solution for the case of multiple liability payouts assuming arbitrary changes in the yield curve. For the case of multiple liability payouts, we generalize M-Absolute, which is a risk measure proposed by Nawalkha и Chambers (1996), and estimate the proximity of payment streams with EMD (the Wasserstein distance) which is a well-known tool in machine learning. In line with Fong and Vasicek (1984), it is shown that portfolio’s interest rate risk is constrained to a product of two factors with one factor, EMD between asset and liability streams, being only dependent on the portfolio structure and the other factor, the sup-norm of the function of interest rate shocks, being solely determined by changes in the yield curve. We also show the unimprovability of the estimate and obtain, in an explicit form, a computational procedure for the optimal immunizing portfolio. The results are practically applicable as exemplified by the immunization of an annuity-type security with a portfolio of government bonds.</p></abstract><trans-abstract xml:lang="ru"><p>Одной из центральных задач в управлении портфелем активов с фиксированной доходностью является иммунизация, т.е. контроль изменения стоимости портфеля при колебаниях процентных ставок с учетом аналогичной зависимости портфеля обязательств. В многочисленных исследованиях были предложены различные модели иммунизации для обязательства cединичным платежом и/или при предположении определенного вида сдвигов кривой спот-ставок. В настоящей работе впервые предложено решение проблемы иммунизации портфеля облигаций для множественных платежей по обязательствам и сдвигов кривой доходности произвольной структуры. Введенная Навалкой и Чемберсом, мера риска M-Absoluteобобщается на случай потока множественных платежей по обязательствам. В качестве меры близости потоков платежей используется известная в машинном обучении метрика EarthMover’sDistance (EMD), или расстояние Монжа–Канторовича–Вассерштейна. Доказана оценка типа Фонга–Васичека — процентный риск портфеля ограничен произведением двух факторов, один из которых будет EMD-расстоянием между активами и обязательствами (т.е. зависит только от структуры портфеля), а другой — sup-норма функции шока ставок — зависит только от изменения кривой бескупонной доходности. Доказана неулучшаемость оценки. Получен явный вид и алгоритм расчета оптимального иммунизирующего портфеля. Практическая применимость метода продемонстрирована на примере иммунизации портфеля облигаций федерального займа при структуре потока обязательств типа аннуитета.</p></trans-abstract><kwd-group xml:lang="en"><kwd>ALM</kwd><kwd>ALM</kwd><kwd>immunization</kwd><kwd>interest rate risk</kwd><kwd>dispersion measure</kwd><kwd>Wasserstein distance</kwd><kwd>Monge–Kantorovich–Rubinstein metric</kwd><kwd>EMD.</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>иммунизация</kwd><kwd>процентный риск</kwd><kwd>мера разброса</kwd><kwd>метрика Монжа–Канторовича–Вассерштейна</kwd><kwd>EMD-расстояние.</kwd></kwd-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>﻿Бешенов С.В, Лапшин В.А. (2019). Параметрическая иммунизация процентного риска на основе моделей срочной структуры процентных ставок // Экономический журнал ВШЭ. Т. 23 (1). С. 9–31.</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Богачев В.И., Колесников А.В. (2012). Задача Монжа–Канторовича: достижения, связи и перспективы // Успехи математических наук. Т. 67. Вып. 5 (407). С. 3–110.</mixed-citation></ref><ref id="B3"><label>3.</label><mixed-citation>Валландер С.С. (1973). Вычисление расстояния по Вассерштейну между распределениями вероятностей на прямой // Теория вероятностей и ее применения. Т. 18. Вып. 4. С. 824–827.</mixed-citation></ref><ref id="B4"><label>4.</label><mixed-citation>Balbas A., Ibanez A. (1998). When can you immunize a bond portfolio? Journal of Banking and Finance, 22, 1571–1595.</mixed-citation></ref><ref id="B5"><label>5.</label><mixed-citation>Balbas A., Ibanez A., Lopez S. (2002). Dispersion measures as immunization risk measures. Journal of Banking and Finance, 26 (6), 1229–1244.</mixed-citation></ref><ref id="B6"><label>6.</label><mixed-citation>Bayliss C., Serra M., Nieto A., Juan A. (2020). Combining a matheuristic with simulation for risk management of stochastic assets and liabilities. Risks 8 (4), 131.</mixed-citation></ref><ref id="B7"><label>7.</label><mixed-citation>Bierwag G. (1977). Immunization, duration, and the term structure of interest rates. Journal of Financial and Quantitative Analysis, 12 (5), 725–742.</mixed-citation></ref><ref id="B8"><label>8.</label><mixed-citation>Bierwag G., Fooladi I., Roberts G. (1993). Designing an immunized portfolio: Is M-squared the key? Journal of Banking and Finance, 17, 1147–1170.</mixed-citation></ref><ref id="B9"><label>9.</label><mixed-citation>Bierwag G., Kaufman G., Toevs A. (1983). Immunization strategies for funding multiple liabilities. Journal of Financial and Quantitative Analysis, 18 (1), 113–123.</mixed-citation></ref><ref id="B10"><label>10.</label><mixed-citation>Chizat L. (2018). Unbalanced optimal transport: Dynamic and Kantorovich formulations. Journal of Functional Analysis, 274 (11), 3090–3123.</mixed-citation></ref><ref id="B11"><label>11.</label><mixed-citation>De La Peña J.I., Iturricastillo I., Moreno R., Roman F., &amp; Trigo E. (2021). Towards an immu-nization perfect model? International Journal of Finance &amp; Economics, 26 (1), 1181–1196.</mixed-citation></ref><ref id="B12"><label>12.</label><mixed-citation>Dutta G., Rao H., Basu S., Tiwari M. (2019). Asset liability management model with decision support system for life insurance companies: Computational results. Computers &amp; Industrial Engineering, 128, 985–98.</mixed-citation></ref><ref id="B13"><label>13.</label><mixed-citation>Fabozzi F.J., Fong H.G. (1985). Fixed income portfolio management. Appendix E: Derivation of risk immunization measures. Homewood Illinois: Dow Jones-Irwin.</mixed-citation></ref><ref id="B14"><label>14.</label><mixed-citation>Fisher L., Weil R. (1971). Coping with the risk of interest rate fluctuations: Returns to bond-holders from naïve and optimal strategies. Journal of Business, 44 (4), 408–431.</mixed-citation></ref><ref id="B15"><label>15.</label><mixed-citation>Fong G., Vasicek O. (1984). A risk minimizing strategy for portfolio immunization. Journal of Finance, 39 (5), 1541–1546.</mixed-citation></ref><ref id="B16"><label>16.</label><mixed-citation>Ford P. (1991). Some Further Investigations into Cashflow Matching. AFIR Colloquium, Rome, Italy, 539–551.</mixed-citation></ref><ref id="B17"><label>17.</label><mixed-citation>Ford P.E.B. (1991). Cashflow matching using modified linear programming. AFIR Colloquium, Brighton, United Kingdom, 3, 301–322.</mixed-citation></ref><ref id="B18"><label>18.</label><mixed-citation>Gangbo W., Li W., Osher S., Puthawala M. (2019). Unnormalized Optimal transport. Journal of Computational Physics, 399, 108940.</mixed-citation></ref><ref id="B19"><label>19.</label><mixed-citation>Hürlimann W. (2002). On immunization, stop-loss order and the maximum shiu measure. Insur-ance: Mathematics and Economics, 31, 315–325.</mixed-citation></ref><ref id="B20"><label>20.</label><mixed-citation>Ingersoll J.Jr., Skelton J., Weil W. (1978). Duration forty years later. Journal of Financial and Quantitative Analysis, 13 (4), 627–650.</mixed-citation></ref><ref id="B21"><label>21.</label><mixed-citation>Khang C. (1979). Bond immunization when short-term interest rates fluctuate more than long-term rates. Journal of Financial and Quantitative Analysis, 14 (5), 1085–1090.</mixed-citation></ref><ref id="B22"><label>22.</label><mixed-citation>Kopa M., Rusý T. (2021). A decision-dependent randomness stochastic program for asset-liability management model with a pricing decision. Annals of Operations Research, 299, 241–271.</mixed-citation></ref><ref id="B23"><label>23.</label><mixed-citation>Leibowitz M. (1986). The dedicated bond portfolio in pension funds – Part I: Motivations and ba-sics. Financial Analysts Journal, 42 (1), 68–75.</mixed-citation></ref><ref id="B24"><label>24.</label><mixed-citation>Monge G. (1781). Mémoire sur la théorie des déblais et des remblais. Paris : De l'Imprimerie Royale.</mixed-citation></ref><ref id="B25"><label>25.</label><mixed-citation>Montrucchio M., Peccati L. (1991). A note on shiu-fisher-weil immunization theorem. Insurance: Mathematics and Economics, 10, 125–131.</mixed-citation></ref><ref id="B26"><label>26.</label><mixed-citation>Nawalkha S., Chambers D. (1996). An improved immunization strategy: M-absolute. Financial Analysts Journal, 52 (5), 69–76.</mixed-citation></ref><ref id="B27"><label>27.</label><mixed-citation>Nawalkha S., Chambers D. (1997). The M-vector model: Derivation and testing of extensions to M-square. Journal of Portfolio Management, 23 (2), 92–98.</mixed-citation></ref><ref id="B28"><label>28.</label><mixed-citation>Nawalkha S., Soto G., Zhang J. (2003). Generalized M-vector models for hedging interest rate risk. Journal of Banking and Finance, 27 (8), 1581–1604.</mixed-citation></ref><ref id="B29"><label>29.</label><mixed-citation>Panaretos V., Zemel Y. (2019). Statistical aspects of wasserstein distances. Annual Review of Statistics and Its Application, 6, 405–431.</mixed-citation></ref><ref id="B30"><label>30.</label><mixed-citation>Redington F. (1952). Review of the principles of life-office valuations. Journal of the Institute of Actuaries, 78 (3), 286–340.</mixed-citation></ref><ref id="B31"><label>31.</label><mixed-citation>Rosenbloom E., Shiu E. (1990). The matching of assets with liabilities by goal programming. Managerial Finance, 16 (1), 23–26.</mixed-citation></ref><ref id="B32"><label>32.</label><mixed-citation>Shiu E. (1987). On the Fisher–Weil immunization theorem. Insurance: Mathematics and Economics, 6, 259–266.</mixed-citation></ref><ref id="B33"><label>33.</label><mixed-citation>Shiu E. (1990). On Redington’s theory of immunization. Insurance: Mathematics and Economics, 9, 171–175.</mixed-citation></ref><ref id="B34"><label>34.</label><mixed-citation>Theobald M., Yallup P. (2009). Liability-driven investment: Multiple Liabilities and the question of the number of moments. European Journal of Finance, 16 (5), 413–435.</mixed-citation></ref><ref id="B35"><label>35.</label><mixed-citation>Torres L., Pereira L., Amini H. (2021). A survey on optimal transport for machine learning: Theory and applications. arXiv: 2106.01963. DOI: 10.48550/arXiv.2106.01963</mixed-citation></ref><ref id="B36"><label>36.</label><mixed-citation>Van der Meer R., Smink M. (1993). Strategies and techniques for asset-liability management: An overview. Geneva Papers on Risk and Insurance, s and Practice, 18 (67), 144–157.</mixed-citation></ref><ref id="B37"><label>37.</label><mixed-citation>Vanderhoof I. (1972). The interest rate assumption and the maturity structure of the assets of a life insurance company. Transactions of Society of Actuaries, 24 (69), 157–192.</mixed-citation></ref><ref id="B38"><label>38.</label><mixed-citation>Weil R. (1973). Macaulay's duration: An appreciation. Journal of Business, 46 (4), 589–592.</mixed-citation></ref></ref-list></back></article>
