Dataset about trade sanctions against Russia for the period 01/01/2014-10/31/2023
Description
1. The dataset represents the time series of SNI from January 1, 2014, to October 31, 2023. SNI is a quantitative index reflecting sanction pressure on financial markets. In earlier studies, we demonstrated that SNI causes changes in domestic financial markets: Rychkov, V. (2023). Estimate of the Impact of Trade Sanctions on the Russian Financial Markets. In: Isaeva, E., Rocha, Á. (eds) Science and Global Challenges of the 21st Century – Innovations and Technologies in Interdisciplinary Applications. Perm Forum 2022. Lecture Notes in Networks and Systems, vol 622. Springer, Cham. https://doi.org/10.1007/978-3-031-28086-3_70 Rychkov, V. (2023). Market Drivers of the Ruble Dollar Market. In: Isaeva, E., Rocha, Á. (eds) Science and Global Challenges of the 21st Century – Innovations and Technologies in Interdisciplinary Applications. Perm Forum 2022. Lecture Notes in Networks and Systems, vol 622. Springer, Cham. https://doi.org/10.1007/978-3-031-28086-3_77 Therefore, an increase in this index indicates an increase in sanction tension and is the cause of financial asset volatility. 2. This index was used to develop a methodology for identifying major sanctions: exceeding the maximum value of SNI for the previous week beyond the established critical level. The calculations are presented on the "Condition" sheet in the document "2. Methodology for identifying the main sanctions". For clarity, we have constructed a graph showing SNI exceedances. In total, we have identified 34 major sanctions for the period from January 1, 2014, to October 31, 2023. The list of sanctions is provided on the "List of sanctions" sheet. For each sanction, the following information is available: the date the sanction was imposed, the number of news articles about the sanction, the number of news articles about plans to impose the sanction, and the temporal range of their publication, the number of news articles about the fact of imposing the sanction, and the temporal range of their publication, the number of cases confirming the importance of the sanction, and the temporal range of their manifestations. Additionally, 8 signal groups were identified that were not related to major sanctions. We separately studied the reason for the news intensity concerning them. The results are presented on the "Exceedance without sanction" sheet. 3. We analyzed the impact of sanctions on the currency, stock, and credit markets. We examined the impact of news on plans and facts of sanctions imposition on USDRUB, IMOEX, RGBI Index. The hypothesis that news about sanctions has a negative impact and is the driving force of financial markets independently of the subsequent fact of their imposition has been confirmed.