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Федорова Елена Анатольевна

Факультет экономических наук

Профиль на hse.ru ↗ тел.: +7 (495) 772-95-90 | 27443
Публикаций
70
Языков
1
Наград
5
Конференций
0
Профиль Публикации (70) Курсы (3)

Профессиональные интересы

экономико-математические методы и моделифинансовый менеджмент

Должности

  • Профессор — Факультет экономических наук, Школа финансов

Био

  • · Начала работать в НИУ ВШЭ в 2011 году.
  • · Научно-педагогический стаж: 29 лет.

Образование

  • 2011 · Ученое звание: Доцент
  • 2011 · Доктор экономических наук: специальность 08.00.10 «Финансы, денежное обращение и кредит» и 08.00.13 «Математические и инструментальные методы экономики», тема диссертации: Финансовая интеграция фондовых рынков:теория, методология и инструментарий
  • 2004 · Специалитет: Северо-Западная академия государственной службы, специальность «Юриспруденция», квалификация «Юрист»
  • 2003 · Кандидат экономических наук
  • 1999 · Специалитет: Санкт-Петербургский государственный технический университет, специальность «Экономика и управление на предприятии», квалификация «Экономист-менеджер»
  • 1993 · Специалитет: Санкт-Петербургский государственный технический университет, специальность «Электропривод и автоматизация промышленных установок и технологических комплексов», квалификация «Инженер-электрик»

Опыт работы

  • · НИУ ВШЭ по настоящее время

Награды и поощрения

  • · Благодарность факультета экономических наук НИУ ВШЭ (февраль 2024)
  • · Благодарность Школы финансов НИУ ВШЭ (январь 2021)
  • · Надбавка за публикацию в журнале из Списка А (и приравненном к нему научном издании) (2025–2026, 2024–2025, 2023–2024)
  • · Надбавка за публикацию в международном рецензируемом научном издании (2022–2023, 2021–2022, 2020–2022, 2018–2020)
  • · Надбавка за статью в зарубежном рецензируемом научном издании (2016–2018)

Гранты и проекты

  • — · на соискание учёной степени кандидата наук

Идентификаторы исследователя

Публикации (70)

Cross-continental analysis: Culture, ESG disclosure, and bank performance nexus

2026 · ARTICLE · en

This study explores the intersection of culture, ESG disclosures, and financial performance in the banking sector, drawing on cultural relativism and ethical universalism. Analyzing ESG data from 52 European and 52 Asian banks between 2010 and 2020, we assess how the content of ESG disclosures influences financial performance, accounting for cultural differences. Using a robust methodology that combines textual analysis, thematic modeling, and expert review, we develop an ESG-specific dictionary tailored to the banking industry, enabling analysis across 15 topics. Regression analyses, with Tobin's q and ROA as response variables, reveal distinct patterns: social dimension disclosures, particularly human rights, have a greater impact on European banks, reflecting cultural relativism. Conversely, environmental and governance disclosures more significantly affect Asian banks, pointing to the influence of universal ethical values. Our findings also highlight varied and sometimes conflicting impacts of thematic disclosures on financial performance indicators, emphasizing the non-uniform and context-dependent nature of ESG influences. Overall, this study underscores the complex relationship between ESG disclosures and financial performance, with cultural contexts playing a critical role in shaping these dynamics within the banking industry.

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Финансовое моделирование в фирме

2025 · BOOK · ru

Состоит из семи глав, раскрывающих основные положения финансового моделирования в фирме. Каждая тема состоит из теориии практического кейса, представленного в Excel. Кроме стандартных подходов, представлен более сложный материал, основанный на регрессионном анализе, вероятностном подходе (метод Монте-Карло)и охватывающий более узкие области исследования (опционы). Соответствует ФГОС ВО последнего поколения. Для студентов бакалавриатаи магистратуры, обучающихся по экономическим направлениям. Будет полезен как учащимся, так и практикам.

The impact of innovation news coverage on illiquid stocks: the case of US market

2023 · ARTICLE · en

The purpose of this study is to determine stock market reactions to the news about innovations and other types of publications for illiquid stocks. Design/methodology/approach (1) The authors opt for machine learning techniques and expert analysis and propose their own lexicon of innovations based on the news articles published on the professional website; (2) the dataset consists of the data on 2,000 US companies for 6 years; (3) the text analysis including BERT and Top2 Vec models which are superior to Latent Dirichlet allocation (LDA) in information criteria allows for more accurate evaluation of news sentiment and idea; and (4) furthermore, random forest and gradient boosting were applied to increase validity of results and demonstrate factor importance. Findings (1) The paper presents theoretical findings adding to signalling theory and efficient market hypothesis for US illiquid stocks; (2) this study suggests that information on product innovations (unlike other types of innovations) has a direct and significant effect on the return of illiquid stocks; (3) the results also give evidence that under uncertainty innovation-related publications do not affect the return of illiquid stocks; and (4) the analysis of the news topics (narratives) demonstrates that only the narrative related to important corporate announcements has a positive impact on the return of illiquid stocks. Originality/value (1) The authors are the first to conduct a large-scale study of the impact of various information on the return of illiquid stocks; (2) the paper focuses on information on several types of innovations with regard to the return of illiquid stocks; (3) based on Top2 Vec model, this study identifies the key topics-narratives discussed by investors and assesses their impact on the return of illiquid stocks; and (4) as an information source, the authors use the sample comprising a total of 1.4m news articles released on the professional website for investors “Benzinga”.

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Governmental anti-pandemic policies, vaccination, population mobility, Twitter narratives, and the spread of COVID-19: Evidence from the European Union countries

2023 · ARTICLE · en

We provide large-scale empirical evidence on the effects of multiple governmental regulatory and health policies, vaccination, population mobility, and COVID-19-related Twitter narratives on the spread of a new coronavirus infection. Using multiple-level fixed effects panel data model with weekly data for 27 European Union countries in the period of March 2020–June 2021, we show that governmental response policies were effective both in reducing the number of COVID-19 infection cases and deaths from it, particularly, in the countries with higher level of rule of law. Vaccination expectedly helped to decrease the number of virus cases. Reductions in population mobility in public places and workplaces were also powerful in fighting the pandemic. Next, we identify four core pandemic-related Twitter narratives: governmental response policies, people’s sad feelings during the pandemic, vaccination, and pandemic-related international politics. We find that sad feelings’ narrative helped to combat the virus spread in EU countries. Our findings also reveal that while in countries with high rule of law international politics’ narrative helped to reduce the virus spread, in countries with low rule of law the effect was strictly the opposite. The latter finding suggests that trust in politicians played an important role in confronting the pandemic.

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Market reaction to firms’ investments in CSR projects

2023 · ARTICLE · en

Purpose – The purpose of this paper is to determine the impact of corporate investments in corporate social responsibility (CSR), measured by the environmental, social and government (ESG) rating, on the market valuation of a firm’s stocks and to explain the regional differences in the degree of this influence. Design/methodology/approach – The empirical study uses linear and non-linear panel regression models for a panel sample of 951 firms listed in Asia, North America and Europe operating in innovative industries. Findings – The CSR score was found to be significant in terms of stock excess return on the regional level. However, this finding cannot be extrapolated to the global scale. ESG rating is priced by the European and North American markets negatively, while in the Asian market, it is positive. This penalty (negative influence) is greater than the reward for one point increase in ESG rating. Practical implications – The results of this empirical study could be used by firms’ managers to adjust strategies aimed at stock value growth and by investors to select an investment strategy to maximize return. Originality/value – The impact of investments in CSR on stock excess return over a defined benchmark is assessed. The study reveals regional differences in the impact of CSR investment using a sample of Asian, European and North American firms. The authors apply a more advanced lagged CSR performance (d.ESG) assessment based on the methodology of Zhang and Rajagopalan (2010).

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Этика и право: соотношение и механизмы взаимовлияния

2023 · BOOK · ru

Настоящее издание является монографическим трудом коллектива авторов, посвященным теоретическим и практическим проблемам соотношения этики и права как социальных регуляторов. В монографии отражены результаты проекта «Этика и право: соотношение и механизмы взаимовлияния» (блок проекта «Прикладная этика»), выполненного в рамках Программы фундаментальных исследований НИУ ВШЭ в 2022–2023 г. Для специалистов в области теории и философии права, преподавателей, аспирантов и студентов юридических и гуманитарных вузов и факультетов, практических работников органов государственной власти и местного самоуправления, а также всех тех, кто интересуется вопросами эффективного регулирования общественных отношений.

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Bankruptcy factors at different stages of the lifecycle for Russian companies

2022 · ARTICLE · en

Many aspects of bankruptcy have not yet been thoroughly studied, among such issues are the causes that lead to bankruptcy at various stages of the company’s lifecycle. We hypothesize that the most significant factors in- fluencing the probability of company bankruptcy at a particular stage of its lifecycle are those the effectiveness of which is at the lowest level at this stage. These factors include the external environment, the quality of financial, and corporate governance. The methodology of the research consists of the meth- ods PLS-SEM (to determine the impact of factors on bankruptcy) and DEA (to evaluate the effectiveness of factors usage). The empirical database in- cludes 376 Russian public companies. The simulation results support the hypothesis. We also revealed that the external environment exerts a more powerful effect on the probability of bankruptcy at the stage of growth. The role of financial management increases from the initial stage to the final stage of the life cycle. Corporate governance is less important than the other two factors, but its impact is significant at the stage of growth.

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Economic policy uncertainty and bankruptcy filings

2022 · ARTICLE · en

Applying machine learning techniques to predict bankruptcy in the sample of French, Italian, Russian and Spanish firms, the study demonstrates that the inclusion of economic policy uncertainty (EPU) indicator into bankruptcy prediction models notably increases their accuracy. This effect is more pronounced when we use novel Twitter-based version of EPU index instead of original news-based index. We further compare the prediction accuracy of machine learning techniques and conclude that stacking ensemble method outperforms (though marginally) machine learning methods, which are more commonly used for bankruptcy prediction, such as single classifiers and bagging.

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The fundamental drivers of electricity price: a multi-scale adaptive regression analysis

2021 · ARTICLE · en

Is the influence of such fundamental drivers as electricity demand and fossil fuel prices on electricity price time- and scale-dependent? At which time-scales is the influence of electricity demand on electricity price the strongest? Starting at which time-scale do changes in the fuel markets impact the electricity price? To answer these questions, the paper proposes a novel methodology—a multi-scale adaptive regression analysis based on the time-dependent intrinsic regression. Its application is demonstrated both on simulated data and on actual data from three electricity markets: the Europe-Ural price area (ATS EU) and the Siberia price area (ATS SI) in Russia, and the APX power spot exchange in the UK. The obtained results show that the influence of fundamental factors on electricity price does depend on time-scale and for the majority of the time-scales is time-dependent. The influence of electricity demand is most prominent both in the short and long terms for ATS EU and APX, while for ATS SI its impact is significant only in the long term. Finally, for all the electricity exchanges under study, the influence of fuel markets is absent in the short term and becomes prominent only in the medium or long terms.

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STRENGTH OF WORDS: DONALD TRUMP'S TWEETS, SANCTIONS AND RUSSIA'S RUBLE

2021 · ARTICLE · en

We empirically test if the US President Donald Trump's rhetoric towards Russia (represented by his Russia-related tweets) affects ruble's exchange rate. Using three-stepped empirical framework, we find that escalation of negative sentiment of Trump's Russia-related tweets leads to ruble's depreciation (4–10%) in short-term periods (around 3 days). Though these episodes tend to coincide with imposition or announcement of US sanctions, we demonstrate that US sanctions that were not accompanied by negative tweets of Donald Trump, have not caused ruble's depreciation. This highlights the role of emotional factors in economic decision-making behavior.

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Курсы (3)