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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">10.26794/2587-5671-2024-28-2-239-252</article-id><article-id custom-type="elpub" pub-id-type="custom">finance-2827</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>МЕЖДУНАРОДНЫЕ ФИНАНСЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INTERNATIONAL FINANCE</subject></subj-group></article-categories><title-group><article-title>Прогнозирование курсов турецкой лиры с помощью одномерных методов: могут ли простые модели превзойти сложные?</article-title><trans-title-group xml:lang="en"><trans-title>Forecasting the Turkish lira Exchange Rates Through Univariate Techniques: Can the Simple Models Outperform the Sophisticated Ones?</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4612-6875</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Саркандиз</surname><given-names>М. Р.</given-names></name><name name-style="western" xml:lang="en"><surname>Sarkandiz</surname><given-names>M. R.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Саркандиз Мостафа Р. — аспирант, Высшая школа прикладной математики, Ближневосточный технический университет.</p><p>Анкара</p></bio><bio xml:lang="en"><p>Mostafa R. Sarkandiz — Postgraduate Student, Graduate School of Applied Mathematics, Middle East Technical University.</p><p>Ankara</p></bio><email xlink:type="simple">Mostafa.raeisi.sarkandiz@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0004-1362-5760</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гаехлу</surname><given-names>С.</given-names></name><name name-style="western" xml:lang="en"><surname>Ghayekhloo</surname><given-names>S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Гаехлу Сара — аспирантка, факультет математики и компьютерных наук, Университет Калабрии.</p><p>Ренде</p></bio><bio xml:lang="en"><p>Sara Ghayekhloo — Postgraduate Student, Department of Mathematics and Computer Science, University of Calabria.</p><p>Rende</p></bio><email xlink:type="simple">Sara.ghayekhloo@rwth-aachen.de</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Ближневосточный технический университет</institution><country>Турция</country></aff><aff xml:lang="en"><institution>Middle East Technical University</institution><country>Turkey</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>Университет Калабрии</institution><country>Италия</country></aff><aff xml:lang="en"><institution>University of Calabria</institution><country>Italy</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>30</day><month>04</month><year>2024</year></pub-date><volume>28</volume><issue>2</issue><fpage>239</fpage><lpage>252</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Саркандиз М.Р., Гаехлу С., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Саркандиз М.Р., Гаехлу С.</copyright-holder><copyright-holder xml:lang="en">Sarkandiz M.R., Ghayekhloo S.</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/2827">https://financetp.fa.ru/jour/article/view/2827</self-uri><abstract><p>На протяжении 2022 г. политика центрального банка Турции по снижению номинальной процентной ставки вызывала эпизоды сильных колебаний курса турецкой лиры. В этих условиях ежедневная доходность пары USD/TRY привлекала внимание инвесторов, склонных к риску. Поэтому неопределенность в отношении ставок подтолкнула алгоритмических трейдеров к поиску наилучшей модели прогнозирования. Несмотря на растущую тенденцию к использованию сложных моделей для прогнозирования финансовых временных рядов, в большинстве случаев простые модели могут дать более точные прогнозы. Чтобы проверить это утверждение, в данном исследовании было использовано несколько моделей для прогнозирования ежедневных валютных курсов в краткосрочной перспективе. Интересно, что простая модель экспоненциального сглаживания превзошла все остальные альтернативы. Кроме того, в отличие от первоначальных предположений, временные ряды не имели ни структурного разрыва, ни признаков эффектов ARCH и левериджа. Несмотря на такое поведение, существуют неоспоримые доказательства наличия тренда с длинной памятью. Это означает, что ряд имеет тенденцию сохранять движение, по крайней мере, в течение короткого периода. В итоге исследование пришло к выводу, что простые модели дают лучшие прогнозы для валютных курсов, чем сложные подходы.</p></abstract><trans-abstract xml:lang="en"><p>The Central Bank of Turkey’s policy to decrease the nominal interest rate has caused episodes of severe fluctuations in Turkish lira exchange rates during 2022. According to these conditions, the daily return of the USD/TRY have attracted the risk-taker investors’ attention. Therefore, the uncertainty about the rates has pushed algorithmic traders toward finding the best forecasting model. While there is a growing tendency to employ sophisticated models to forecast financial time series, in most cases, simple models can provide more precise forecasts. To examine that claim, present study has utilized several models to predict daily exchange rates for a short horizon. Interestingly, the simple exponential smoothing model outperformed all other alternatives. Besides, in contrast to the initial inferences, the time series neither had structural break nor exhibited signs of the ARCH and leverage effects. Despite that behavior, there was undeniable evidence of a long-memory trend. That means the series tends to keep a movement, at least for a short period. Finally, the study concluded the simple models provide better forecasts for exchange rates than the complicated approaches.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>валютный курс</kwd><kwd>прогнозирование</kwd><kwd>авторегрессия</kwd><kwd>экспоненциальное сглаживание</kwd><kwd>структурный разрыв</kwd></kwd-group><kwd-group xml:lang="en"><kwd>exchange rate</kwd><kwd>forecasting</kwd><kwd>autoregressive</kwd><kwd>exponential smoothing</kwd><kwd>structural break</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">Fetai B., Koku P. S., Caushi A., Fetai A. The relationship between exchange rate and inflation: The case of Western Balkans countries. Journal of Business Economics and Finance. 2016;5(4):360–364. DOI: 10.17261/Pressacademia.2017.358</mixed-citation><mixed-citation xml:lang="en">Fetai B., Koku P. S., Caushi A., Fetai A. 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