<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<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">voprecotest</journal-id><journal-title-group><journal-title xml:lang="ru">Вопросы экономики</journal-title><trans-title-group xml:lang="en"><trans-title>Voprosy Ekonomiki</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">0042-8736</issn><publisher><publisher-name>Voprosy Ekonomiki, NP</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.32609/0042-8736-2022-10-37-65</article-id><article-id custom-type="elpub" pub-id-type="custom">voprecotest-3747</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 ЭКОНОМИКА</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>FINANCIAL ECONOMICS</subject></subj-group></article-categories><title-group><article-title>Формирование Ломбардного списка как искажающий сигнал Банка России</article-title><trans-title-group xml:lang="en"><trans-title>Lombard List formation as a distorting signal of the Bank of Russia</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8212-5103</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Телегин</surname><given-names>О. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Telegin</surname><given-names>O. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Телегин Олег Валерьевич, стажер-исследователь Международной лаборатории макроэкономического анализа, ассистент Департамента теоретической экономики</p><p>Москва</p><p> </p></bio><bio xml:lang="en"><p>Oleg V. Telegin </p><p>Moscow</p></bio><email xlink:type="simple">otelegin@hse.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Национальный исследовательский университет "Высшая школа экономики"</institution><country>Россия</country></aff><aff xml:lang="en"><institution>HSE University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>09</day><month>10</month><year>2022</year></pub-date><volume>0</volume><issue>10</issue><fpage>37</fpage><lpage>65</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Voprosy Ekonomiki, NP, 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Voprosy Ekonomiki, NP</copyright-holder><copyright-holder xml:lang="en">Voprosy Ekonomiki, NP</copyright-holder><license xlink:href="https://www.vopreco.ru/jour/about/submissions#copyrightNotice" xlink:type="simple"><license-p>https://www.vopreco.ru/jour/about/submissions#copyrightNotice</license-p></license></permissions><self-uri xlink:href="https://www.vopreco.ru/jour/article/view/3747">https://www.vopreco.ru/jour/article/view/3747</self-uri><abstract><p>Каким образом участники российского рынка реагируют на решения Банка России об изменениях Ломбардного списка? В данной работе исследуется взаимосвязь включения ценных бумаг в список и изменения доходностей и волатильности акций компаний Московской Биржи. Для моделирования поведения волатильности акций компаний использовались видоизмененные HAR-модели, для моделирования доходностей – рыночная модель, исследование было проведено для 5-минутных, часовых и дневных временных интервалов. В результате было установлено, что в период с 2014 по 2020 год добавление облигации в Ломбардный список, произошедшее быстрее, чем за 3 недели с момента эмиссии, приводит к значимому увеличению доходности акций компаний и к значимому уменьшению их волатильности, при этом эффекты наблюдаются в течение нескольких часов. Таким образом, участники рынка воспринимают подобные новости как значимые сигналы о состоянии дел в отдельных частных компаниях, несмотря на отсутствие подобной цели у регулятора. Исходя из результатов проведенного анализа, были также сформулированы рекомендации Банку России по изменению механизма включения ценных бумаг в Ломбардный список.</p></abstract><trans-abstract xml:lang="en"><p>How do Russian market participants react to the decisions of the Bank of Russia on changes to the Lombard List? This paper examines the relationship between the inclusion of securities in the list and changes in returns and volatility of shares in Moscow Stock Exchange companies. To model the behavior of the volatility of stocks of companies, modified HAR-models were used, to model returns — a market model; the study was carried out for 5-minute, hourly and daily time intervals. As a result, it was found that in the period from 2014 to 2020, the addition of a security to the Lombard List, which occurred faster than 3 weeks from the date of issue, led to a significant increase in returns of stocks of companies and to a significant decrease in their volatility and the effects might be observed during several hours. Thus, market participants perceive such news as significant signals about the state of affairs in private companies, despite the initial goal of the regulator. Based on the results of the analysis, recommendations were also formulated for the Bank of Russia to change the mechanism of including securities in the Lombard List.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>Ломбардный список</kwd><kwd>коммуникационная политика</kwd><kwd>HAR-модели</kwd><kwd>модели волатильности</kwd><kwd>центральный банк</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Lombard List</kwd><kwd>communication policy</kwd><kwd>HAR-models</kwd><kwd>volatility models</kwd><kwd>central bank</kwd><kwd>Bank of Russia</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Статья подготовлена в рамках Программы фундаментальных исследований НИУ ВШЭ</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">Аганин А. Д. (2017). Сравнение GARCH и HAR-RV моделей для прогноза реализованной волатильности на российском рынке // Прикладная эконометрика. Т. 48. C. 63—84. [Aganin A.D. (2017). Forecast comparison of volatility models on Russian stock market. Applied Econometrics, Vol. 48, pp. 63—84. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Aganin A.D. (2017). Forecast comparison of volatility models on Russian stock market. Applied Econometrics, Vol. 48, pp. 63—84. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Жемков М. И., Кузнецова О. С. (2019). Вербальные интервенции как фактор формирования инфляционных ожиданий в России // Журнал Новой экономической ассоциации. Т. 2, № 42. С. 49—69. [Zhemkov M. I., Kuznetsova O. S. (2019). Verbal interventions as a factor of inflation expectations in Russia. Journal of the New Economic Association, Vol. 2, No. 42, pp. 49—69. (In Russian).] https://doi.org/10.31737/2221-2264-2019-42-2-3</mixed-citation><mixed-citation xml:lang="en">Zhemkov M. I., Kuznetsova O. S. (2019). Verbal interventions as a factor of inflation expectations in Russia. Journal of the New Economic Association, Vol. 2, No. 42, pp. 49—69. (In Russian).] https://doi.org/10.31737/2221-2264-2019-42-2-3</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Кузнецова О. С., Ульянова С. Р. (2016). Влияние вербальных интервенций Банка России на фондовые индексы // Журнал экономической теории. № 4. С. 18—27. [Kuznetsova O. S., Ulyanova S. R. (2016). The impact of a central bank’s verbal interventions on stock exchange indices. Zhurnal Ekonomicheskoy Teorii, No. 4, pp. 18—27. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Kuznetsova O. S., Ulyanova S. R. (2016). The impact of a central bank’s verbal interventions on stock exchange indices. Zhurnal Ekonomicheskoy Teorii, No. 4, pp. 18—27. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Кузнецова О. С., Ульянова С. Р. (2018). Валютный курс и вербальные интервенции Банка России и органов государственной власти // Экономический журнал Высшей школы экономики. Т. 22, №. 2. С. 228—250. [Kuznetsova O. S., Ulyanova S. R. (2018). The exchange rate and the verbal interventions by the government and the Bank of Russia. HSE Economic Journal, Vol. 22, No. 2, pp. 228—250. (In Russian).] https://doi.org/10.17323/1813-8691-2018-22-2-228-250</mixed-citation><mixed-citation xml:lang="en">Kuznetsova O. S., Ulyanova S. R. (2018). The exchange rate and the verbal interventions by the government and the Bank of Russia. HSE Economic Journal, Vol. 22, No. 2, pp. 228—250. (In Russian).] https://doi.org/10.17323/1813-8691-2018-22-2-228-250</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Мерзляков С., Хабибуллин Р. (2017). Информационная политика Банка России: анализ воздействия пресс-релизов о ключевой ставке на межбанковскую ставку // Вопросы экономики. № 11. С. 141—151. [Merzlyakov S., Habibullin R. (2017). Information policy of the Bank of Russia: The influence of the press releases on the interbank rate. Voprosy Ekonomiki, No. 11, pp. 141—151. (In Russian).] https://doi.org/10.32609/0042-8736-2017-11-141-151</mixed-citation><mixed-citation xml:lang="en">Merzlyakov S., Habibullin R. (2017). Information policy of the Bank of Russia: The influence of the press releases on the interbank rate. Voprosy Ekonomiki, No. 11, pp. 141—151. (In Russian).] https://doi.org/10.32609/0042-8736-2017-11-141-151</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Мусаев Р. А., Клешко Д. В. (2015). Развитие системы рефинансирования банковского сектора России // Финансовый журнал. № 2. С. 42—51. [Musaev R. A., Kleshko D. V. (2015). Development of refinancing system of the Russian banking sector. Financial Journal, No. 2, pp. 42—51. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Musaev R. A., Kleshko D. V. (2015). Development of refinancing system of the Russian banking sector. Financial Journal, No. 2, pp. 42—51. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Телегин О. В., Мерзляков С. А. (2019). Вербальные интервенции Банка России и структура процентных ставок // Журнал экономической теории. Т. 16, № 4. С. 654—672. [Telegin O. V., Merzlyakov S. A. (2019). Verbal interventions of the Bank of Russia and the interest rate structure. Zhurnal Ekonomicheskoy Teorii, Vol. 16, No. 4, pp. 654—672. (In Russian).] https://www.doi.org/10.31063/2073-6517/2019.16-4.5</mixed-citation><mixed-citation xml:lang="en">Telegin O. V., Merzlyakov S. A. (2019). Verbal interventions of the Bank of Russia and the interest rate structure. Zhurnal Ekonomicheskoy Teorii, Vol. 16, No. 4, pp. 654—672. (In Russian).] https://www.doi.org/10.31063/2073-6517/2019.16-4.5</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Телегин О. В. (2022). Регулярные коммуникации Банка России и краткосрочные эффекты волатильности на финансовых рынках // Журнал Новой экономической ассоциации. № 2. С. 130—155. [Telegin O. V. (2022). Bank of Russia regular communications and volatility short-term effects in financial markets. Journal of the New Economic Association, No. 2, pp. 130—155. (In Russian). https://doi.org/10.31737/2221-2264-2022-54-2-7</mixed-citation><mixed-citation xml:lang="en">Telegin O. V. (2022). Bank of Russia regular communications and volatility short-term effects in financial markets. Journal of the New Economic Association, No. 2, pp. 130—155. (In Russian). https://doi.org/10.31737/2221-2264-2022-54-2-7</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Теплова Т. В., Соколова Т. В. (2017). Непараметрический метод оболочечного анализа для портфельных построений на российском рынке облигаций // Экономика и математические методы. Т. 53, №. 3. С. 110—128. [Teplova T. V., Sokolova T. V. (2017). The non-parametric data envelopment analysis method for portfolio design in the Russian bond market. Economics and Mathematical Methods, Vol. 53, No. 3, pp. 110—128. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Teplova T. V., Sokolova T. V. (2017). The non-parametric data envelopment analysis method for portfolio design in the Russian bond market. Economics and Mathematical Methods, Vol. 53, No. 3, pp. 110—128. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Чайковская Е. (2015). Красный апельсин, или Успеть за 24 часа // Cbonds Review. Т. 4. С. 52—55. [Chaykovskaya E. (2015). Red orange, or catch in 24 hours. Cbonds Review, Vol. 4, pp. 52—55. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Chaykovskaya E. (2015). Red orange, or catch in 24 hours. Cbonds Review, Vol. 4, pp. 52—55. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Чиркова Е. В., Петров В. В. (2017). Диагностирование инсайдерской торговли акциями и депозитарными расписками российских компаний // Экономический журнал Высшей школы экономики. Т. 21, № 3. С. 482—514. [Chirkova E. V., Petrov V. V. (2017). Testing for insider trading in the depositary receipts and common shares of the Russian public companies. HSE Economic Journal, Vol. 21, No. 3, pp. 482—514. (In Russian).</mixed-citation><mixed-citation xml:lang="en">Chirkova E. V., Petrov V. V. (2017). Testing for insider trading in the depositary receipts and common shares of the Russian public companies. HSE Economic Journal, Vol. 21, No. 3, pp. 482—514. (In Russian).</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Andersen T., Bollerslev T., Diebold F., Vega C. (2003). Micro effects of macro announcements: Real-time price discovery in foreign exchange. American Economic Review, Vol. 93, No. 1, pp. 38—62. https://doi.org/10.1257/000282803321455151</mixed-citation><mixed-citation xml:lang="en">Andersen T., Bollerslev T., Diebold F., Vega C. (2003). Micro effects of macro announcements: Real-time price discovery in foreign exchange. American Economic Review, Vol. 93, No. 1, pp. 38—62. https://doi.org/10.1257/000282803321455151</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Bernanke B. S., Kuttner K. N. (2005). What explains the stock market’s reaction to Federal Reserve policy? Journal of Finance, Vol. 60, No. 3, pp. 1221—1257. https://doi.org/10.1111/j.1540-6261.2005.00760.x</mixed-citation><mixed-citation xml:lang="en">Bernanke B. S., Kuttner K. N. (2005). What explains the stock market’s reaction to Federal Reserve policy? Journal of Finance, Vol. 60, No. 3, pp. 1221—1257. https://doi.org/10.1111/j.1540-6261.2005.00760.x</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Bollerslev T., Hood B., Huss J., Pedersen L. H. (2018). Risk everywhere: Modeling and managing volatility. Review of Financial Studies, Vol. 31, No. 7, pp. 2729—2773. https://doi.org/10.1093/rfs/hhy041</mixed-citation><mixed-citation xml:lang="en">Bollerslev T., Hood B., Huss J., Pedersen L. H. (2018). Risk everywhere: Modeling and managing volatility. Review of Financial Studies, Vol. 31, No. 7, pp. 2729—2773. https://doi.org/10.1093/rfs/hhy041</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Bullard J. B., Schaling E. (2002). Why the Fed should ignore the stock market. Review, Vol. 84, No. 2, pp. 35—42. Federal Reserve Bank of St. Louis. https://doi.org/10.20955/r.84.35-42</mixed-citation><mixed-citation xml:lang="en">Bullard J. B., Schaling E. (2002). Why the Fed should ignore the stock market. Review, Vol. 84, No. 2, pp. 35—42. Federal Reserve Bank of St. Louis. https://doi.org/10.20955/r.84.35-42</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Cassola N., Koulischer F. (2019). The collateral channel of open market operations. Journal of Financial Stability, Vol. 41, pp. 73—90. https://doi.org/10.1016/j.jfs.2019.03.002</mixed-citation><mixed-citation xml:lang="en">Cassola N., Koulischer F. (2019). The collateral channel of open market operations. Journal of Financial Stability, Vol. 41, pp. 73—90. https://doi.org/10.1016/j.jfs.2019.03.002</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Chailloux A., Gray S. T., McCaughrin R. (2008). Central bank collateral frameworks: Principles and policies. IMF Working Paper, No. 222.</mixed-citation><mixed-citation xml:lang="en">Chailloux A., Gray S. T., McCaughrin R. (2008). Central bank collateral frameworks: Principles and policies. IMF Working Paper, No. 222.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Clements A., Preve D. P. A. (2021). A practical guide to harnessing the HAR volatility model. Journal of Banking &amp; Finance, Vol. 133, article 106285. https://doi.org/10.1016/j.jbankfin.2021.106285</mixed-citation><mixed-citation xml:lang="en">Clements A., Preve D. P. A. (2021). A practical guide to harnessing the HAR volatility model. Journal of Banking &amp; Finance, Vol. 133, article 106285. https://doi.org/10.1016/j.jbankfin.2021.106285</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Corradin S., Rodriguez-Moreno M. (2016). Violating the law of one price: The role of non-conventional monetary policy. European Central Bank Working Paper Series, No. 1927. https://doi.org/10.2866/585712</mixed-citation><mixed-citation xml:lang="en">Corradin S., Rodriguez-Moreno M. (2016). Violating the law of one price: The role of non-conventional monetary policy. European Central Bank Working Paper Series, No. 1927. https://doi.org/10.2866/585712</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Corsi F., Audrino F., Renó R. (2012). HAR modeling for realized volatility forecasting. In: L. Bauwens, C. Hafner, S. Laurent (eds.). Handbook of volatility models and their applications. Hoboken, NJ: John Wiley &amp; Sons, pp. 363—382. https://doi.org/10.1002/9781118272039.ch15</mixed-citation><mixed-citation xml:lang="en">Corsi F., Audrino F., Renó R. (2012). HAR modeling for realized volatility forecasting. In: L. Bauwens, C. Hafner, S. Laurent (eds.). Handbook of volatility models and their applications. Hoboken, NJ: John Wiley &amp; Sons, pp. 363—382. https://doi.org/10.1002/9781118272039.ch15</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Enikolopov R., Petrova M., Sonin K. (2018). Social media and corruption. American Economic Journal: Applied Economics, Vol. 10, No. 1, pp. 150—174. https://doi.org/10.1257/app.20160089</mixed-citation><mixed-citation xml:lang="en">Enikolopov R., Petrova M., Sonin K. (2018). Social media and corruption. American Economic Journal: Applied Economics, Vol. 10, No. 1, pp. 150—174. https://doi.org/10.1257/app.20160089</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Fama E. F., French K. R. (2015) A five-factor asset pricing model. Journal of Financial Economics, Vol. 116, No. 1, pp. 1—22. https://doi.org/10.1016/j.jfineco.2014.10.010</mixed-citation><mixed-citation xml:lang="en">Fama E. F., French K. R. (2015) A five-factor asset pricing model. Journal of Financial Economics, Vol. 116, No. 1, pp. 1—22. https://doi.org/10.1016/j.jfineco.2014.10.010</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Fiordelisi F., Galloppo G., Ricci O. (2014). The effect of monetary policy interventions on interbank markets, equity indices and G-SIFIs during financial crisis. Journal of Financial Stability, Vol. 11, pp. 49—61. https://doi.org/10.1016/j.jfs.2013.12.002</mixed-citation><mixed-citation xml:lang="en">Fiordelisi F., Galloppo G., Ricci O. (2014). The effect of monetary policy interventions on interbank markets, equity indices and G-SIFIs during financial crisis. Journal of Financial Stability, Vol. 11, pp. 49—61. https://doi.org/10.1016/j.jfs.2013.12.002</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Forsberg L., Ghysels E. (2007). Why do absolute returns predict volatility so well? Journal of Financial Econometrics, Vol. 5, No. 1, pp. 31—67. https://doi.org/10.1093/jjfinec/nbl010</mixed-citation><mixed-citation xml:lang="en">Forsberg L., Ghysels E. (2007). Why do absolute returns predict volatility so well? Journal of Financial Econometrics, Vol. 5, No. 1, pp. 31—67. https://doi.org/10.1093/jjfinec/nbl010</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Haitsma R., Unalmis D., de Haan J. (2016). The impact of the ECB’s conventional and unconventional monetary policies on stock markets. Journal of Macroeconomics, Vol. 48, pp. 101—116. https://doi.org/10.1016/j.jmacro.2016.02.004</mixed-citation><mixed-citation xml:lang="en">Haitsma R., Unalmis D., de Haan J. (2016). The impact of the ECB’s conventional and unconventional monetary policies on stock markets. Journal of Macroeconomics, Vol. 48, pp. 101—116. https://doi.org/10.1016/j.jmacro.2016.02.004</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Li Y., Khashanah K. M. (2015). The predictive power of volatility pattern recognition in stock market. 2015 IEEE Symposium Series on Computational Intelligence, pp. 742—748. https://doi.org/10.1109/SSCI.2015.112</mixed-citation><mixed-citation xml:lang="en">Li Y., Khashanah K. M. (2015). The predictive power of volatility pattern recognition in stock market. 2015 IEEE Symposium Series on Computational Intelligence, pp. 742—748. https://doi.org/10.1109/SSCI.2015.112</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">McCredie B., Docherty P., Easton S., Uylangco K. (2016). The channels of monetary policy triggered by central bank actions and statements in the Australian equity market. International Review of Financial Analysis, Vol. 46, pp. 46—61. https://doi.org/10.1016/j.irfa.2016.04.008</mixed-citation><mixed-citation xml:lang="en">McCredie B., Docherty P., Easton S., Uylangco K. (2016). The channels of monetary policy triggered by central bank actions and statements in the Australian equity market. International Review of Financial Analysis, Vol. 46, pp. 46—61. https://doi.org/10.1016/j.irfa.2016.04.008</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Nyborg K. G. (2017). Central bank collateral frameworks. Journal of Banking &amp; Finance, Vol. 76, pp. 198—214. https://doi.org/10.1016/j.jbankfin.2016.12.010</mixed-citation><mixed-citation xml:lang="en">Nyborg K. G. (2017). Central bank collateral frameworks. Journal of Banking &amp; Finance, Vol. 76, pp. 198—214. https://doi.org/10.1016/j.jbankfin.2016.12.010</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Pinho C., Sousa C. F. F., Maldonado I. (2017). The impact of ECB announcements on the Eurozone financial markets. Unpublished manuscript.</mixed-citation><mixed-citation xml:lang="en">Pinho C., Sousa C. F. F., Maldonado I. (2017). The impact of ECB announcements on the Eurozone financial markets. Unpublished manuscript.</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Rosa C. (2011). Words that shake traders: The stock market’s reaction to central bank communication in real time. Journal of Empirical Finance, Vol. 18, No. 5, pp. 915—934. https://doi.org/10.1016/j.jempfin.2011.07.005</mixed-citation><mixed-citation xml:lang="en">Rosa C. (2011). Words that shake traders: The stock market’s reaction to central bank communication in real time. Journal of Empirical Finance, Vol. 18, No. 5, pp. 915—934. https://doi.org/10.1016/j.jempfin.2011.07.005</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Sorescu A., Warren N. L., Ertekin L. (2017). Event study methodology in the marketing literature: An overview. Journal of the Academy of Marketing Science, Vol. 45, No. 2, pp. 186—207. https://doi.org/10.1007/s11747-017-0516-y</mixed-citation><mixed-citation xml:lang="en">Sorescu A., Warren N. L., Ertekin L. (2017). Event study methodology in the marketing literature: An overview. Journal of the Academy of Marketing Science, Vol. 45, No. 2, pp. 186—207. https://doi.org/10.1007/s11747-017-0516-y</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Tian F., Yang K., Chen L. (2017). Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity. International Journal of Forecasting, Vol. 33, No. 1, pp. 132—152. https://doi.org/10.1016/j.ijforecast.2016.08.002</mixed-citation><mixed-citation xml:lang="en">Tian F., Yang K., Chen L. (2017). Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity. International Journal of Forecasting, Vol. 33, No. 1, pp. 132—152. https://doi.org/10.1016/j.ijforecast.2016.08.002</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
