Investment Strategies of Russian Investors under the Exposure to News Shocks: Event Study Methodology
- Authors: Yastrebova S.S.1
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Affiliations:
- Lomonosov Moscow State University
- Issue: Vol 20, No 3 (2024)
- Pages: 152-161
- Section: Mathematical, Statistical and Instrumental Methods in Economics
- URL: https://journals.eco-vector.com/2541-8025/article/view/635695
- DOI: https://doi.org/10.33693/2541-8025-2024-20-3-152-161
- EDN: https://elibrary.ru/DFVEDQ
- ID: 635695
Cite item
Abstract
In this paper an issue of assessing the reactions of Russian investors in the stock market to news shocks in an industry context is considered. The problem of studying investors' reactions to news shocks is related to the difficulty of tracking the effect of publishing news that can announce the probability of an event. In order to determine the reactions in the form of investors’ actions stimulated by news publications, it is necessary to consider a short period of time both before and after the occurrence of a news event. This effect can be clearly determined in a stock market, where it is important for investors to make fast decisions on buying and selling shares after the news publication. The purpose of this paper is to explain the impact of news shocks on investors’ behavior strategies. Within the framework of this paper, solutions to the following tasks are presented:
- Specific characteristics of investors’ behavior in the stock market are determined;
- The impact of news shocks on investors’ behavior has been determined;
- An intersectoral analysis of changes in investment strategies on the Moscow Stock Exchange under the influence of news shocks was carried out;
- Investment strategies of Russian investors under the influence of shocks are characterized.
In this work, both qualitative and quantitative research methods were used. The first ones include the synthesis and analysis of scientific literature, comparative and statistical analysis. The second is to conduct an Event Study analysis based on data obtained from open sources. Statistical data analysis was carried out using the R programming language and the Gretl program.
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About the authors
Svetlana S. Yastrebova
Lomonosov Moscow State University
Author for correspondence.
Email: ssyastrebova@gmail.com
ORCID iD: 0009-0003-5460-1768
Faculty of Economics, Department of Finance and Credit
Russian Federation, MoscowReferences
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