Subject. This article discusses the issues related to the macroeconomic balance of the Russian financial market. Objectives. The article aims to analyze the macroeconomic balance of the Russian financial market and describe it. Methods. For the study, I used the general scientific and specialized economic and mathematical methods. Results. The article emphasizes the relevance of analyzing the macroeconomic balance of Russia's financial market to ensure the stability of the country's financial system and create favorable conditions for economic growth. It finds that over the past five years, the Russian financial market has shown a significant increase in the banking system's demands on other sectors. There is a significant increase in the issuance of debt securities on the domestic market at market value, accompanied by a decrease in the ratio of short-term debt securities to long-term ones. Conclusions and Relevance. The information obtained reflects the complexity of financial and economic problems and the need for an interdisciplinary approach to ensure the macroeconomic balance of Russia's financial market. The identified characteristics of the macroeconomic balance of Russia's financial market may be useful to government authorities, investors, commercial banks, and issuing companies when developing an effective financial strategy and responding wisely to economic challenges.
Keywords: stocks, banks, bonds, balance, finance
References:
Ivanova N., Popova S., Styrin K. Bank market power and monetary policy transmission: Evidence from loan-level data. Emerging Markets Review, 2025, vol. 66, 101280. DOI: 10.1016/j.ememar.2025.101280
Roy S. What drives the systemic banking crises in advanced economies? Global Finance Journal, 2022, vol. 54, 100746. DOI: 10.1016/j.gfj.2022.100746 EDN: HFBZKR
Bernanke B.S., Gertler M. Inside the Black Box: The Credit Channel of Monetary Policy Transmission. National Bureau of Economic Research Working Paper Series. NBER Working Paper No. w5146, 1995. DOI: 10.3386/w5146.https
El-Shagi M., Tochkov K. Divisia monetary aggregates for Russia: Money demand, GDP nowcasting and the price puzzle. Economic Systems, 2022, vol. 46, iss. 4, 101054. DOI: 10.1016/j.ecosys.2022.101054 EDN: OJBNAJ
Chen Zh., Zheng H. Herding in the Chinese and US stock markets: Evidence from a micro-founded approach. International Review of Economics & Finance, 2022, vol. 78, pp. 597–604. DOI: 10.1016/j.iref.2021.11.015 EDN: BWFBVF
Day R.H., Huang W. Bulls, bears and market sheep. Journal of Economic Behavior & Organization, 1990, vol. 14, iss. 3, pp. 299–329. DOI: 10.1016/0167-2681(90)90061-H
Chiarella C., He X.-Zh., Wang D., Zheng M. The stochastic bifurcation behaviour of speculative financial markets. Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, iss. 15, pp. 3837-3846. DOI: 0.1016/j.physa.2008.01.078
Evans G. Pitfalls in Testing for Explosive Bubbles in Asset Prices. The American Economic Review, 1991, vol. 81, iss. 4, pp. 922-930. URL: Link
Follmer H., Horst U., Kirman A. Equilibria in financial markets with heterogeneous agents: a probabilistic perspective. Journal of Mathematical Economics, 2005, vol. 41, iss. 1-2, pp. 123–155. DOI: 10.1016/j.jmateco.2004.08.001
Fama E.F. Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 1970, vol. 25, iss. 2, pp. 383–417. DOI: 10.1111/j.1540-6261.1970.tb00518.x
Askari A., Hajizadeh E. A novel method for analyzing financial market efficiency through fuzzy set theory. Finance Research Letters, 2025, vol. 78, 107243. DOI: 10.1016/j.frl.2025.107243
Lo A.W. The Adaptive Market Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 2004, 33 p. URL: Link
Lo A.W. Efficient market hypothesis. The New Palgrave: A Dictionary of Economics, 2007, vol. 46, no. 5, pp. 1-28. URL: Link
Urquhart A., Hudson R. Efficient or adaptive markets? Evidence from major stock markets using very long run historic data. International Review of Financial Analysis, 2013, vol. 28, pp. 130–142. DOI: 10.1016/j.irfa.2013.03.005
Urquhart A., McGroarty F. Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data. International Review of Financial Analysis, 2014, vol. 35, pp. 154–166. DOI: 10.1016/j.irfa.2014.08.003
Wang J., Wang X. COVID-19 and financial market efficiency: Evidence from an entropy-based analysis. Finance Research Letters, 2021, vol. 42, 101888. DOI: 10.1016/j.frl.2020.101888 EDN: LKVWCH
Alvarez-Ramirez J., Rodriguez E., Alvarez J. A multiscale entropy approach for market efficiency. International Review of Financial Analysis, 2012, vol. 21, pp. 64–69. DOI: 10.1016/j.irfa.2011.12.001
Tee Ch.-M., Wong W.-Y., Hooy Ch.-W. Financial sanctions and global stock market reaction: Evidence from the Russia-Ukraine conflict. Finance Research Letters, 2023, vol. 58, Part B, 104398. DOI: 10.1016/j.frl.2023.104398 EDN: LBNMMB
Boubaker S., Goodell J.W., Pandey D.K., Kumari V. Heterogeneous impacts of wars on global equity markets: Evidence from the invasion of Ukraine. Finance Research Letters, 2022, vol. 48, 102934. DOI: 10.1016/j.frl.2022.102934 EDN: SYKRHS
Qureshi A., Rizwan M.S., Ahmad G., Ashraf D. Russia-Ukraine war and systemic risk: Who is taking the heat? Finance Research Letters, 2022, vol. 48, 103036. DOI: 10.1016/j.frl.2022.103036 EDN: DMDJVX
Gaio L.E., Stefanelli N.O., Pimenta T., Bonacim C.A.G., Gatsios R.C. The impact of the Russia-Ukraine conflict on market efficiency: Evidence for the developed stock market. Finance Research Letters, 2022, vol. 50, 103302. DOI: 10.1016/j.frl.2022.103302 EDN: DXIRPF
