The Scientific Research Group on ESG, Corporate Events and Machine Learning Held an Introductory Seminar
On March 11, an introductory seminar was held in the scientific and educational group "The impact of ESG disclosures, news and corporate events on stock prices and corporate bond spreads: event and sentiment analysis using machine learning", which opened a series of scientific meetings of the group. The NOUGAT research project is dedicated to a comprehensive analysis of how ESG factors, the news background and corporate events affect the dynamics of the Russian stock market and the corporate debt market.
The main purpose of the research conducted by the group is to study the complex impact of sustainability factors, including environmental, social and managerial aspects (ESG), on the financial activities of Russian enterprises. The Group is investigating how disclosure of environmental responsibility, social initiatives and management quality affects companies' market performance, such as share price dynamics and credit rating. Special attention is paid to the role of data analytics and machine learning methods for assessing the emotional perception of news by the market ("sentiment analysis").
The research includes the use of statistical models aimed at identifying patterns in the behaviour of investors and creditors responding to corporate events and environmental changes. This work is aimed at creating tools that allow companies to adapt their strategy and improve the effectiveness of communications with investors and creditors.
Seminar Programme
The head of the NAG, Varvara Vadimovna Nazarova, introduced the group, introduced the key participants of the project and outlined the goals of the upcoming seminars. She stressed the importance of an interdisciplinary approach combining finance, economics and computer science, and shared plans to expand cooperation with international partners.
The next stage was the performance of Iya Yurievna Churakova. She explained in detail the structure of the group, the distribution of responsibilities among the team members and the format of future events. The importance of the participation of young scientists and students in the group's projects aimed at developing innovative approaches to financial data analysis was emphasised.
The most important event was the presentation of a report by Roman Podlevskikh, a 2nd-year master's degree in Finance, on the study of factors affecting stock returns after the issue of convertible bonds. His research focuses on the Indian and Chinese markets, examining differences in the reactions of shareholders and issuers to the issuance of this type of debt. The main conclusions of the report were related to the identified factors leading to significant fluctuations in the value of shares after the placement of convertible bonds. Among them were noted:
- The company's transparency level,
- Reputational risks,
- Investment attractiveness of the region,
- The reaction of national regulators.
The presentation sparked a lively discussion among the audience, many of whom expressed interest in further studying similar phenomena in the Russian market.
One of the highlights of the event was the role of Vishal Kumar, a graduate student and lecturer at the HSE Finance Department. Being a specialist in the field of financial engineering and quantitative analysis, he presented a critical view on the methodology of studying corporate events and suggested a number of promising areas for further scientific research.
The introductory seminar became an important starting point in the work of the NAG: the participants presented a general research framework, outlined plans for further meetings and discussed the first report in the logic of an academic seminar. This format allows not only to introduce the audience to the group's current projects, but also to build a meaningful discussion of research at the intersection of finance, data analysis and machine learning.
