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The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 5/2024.  Finance.

Georgiy A. Borisenko

Postgraduate student, Faculty of Economics, Lomonosov Moscow State University, Moscow, Russia

ORCID: 0009-0000-8430-7744

 

NEURAL NETWORKS TO FORECAST STOCK PRICES BASED ON NEWS DATA

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Abstract

This work is devoted to forecasting the movement of the stock prices of large Russian companies represented in the Moscow Exchange Index, based on news data. Transformer neural networks as well as classical machine learning are used as forecast models. Large Russian news sources and Telegram channels on economics and finance concerns are used as news data. The problem is solved in two settings: classification into 2 classes (the share price will be higher/lower than the current one) and classification into 3 classes (the share price will be higher/approximately at the same level/lower than the current one). As a result of the study, it was found that classical machine learning methods cope better with this task in the general case, but neural networks also show good quality for large companies.

Keywords: stock price, news, neural networks.

JEL: С63, G14

EDN: KJVYKJ

DOI: https://doi.org/10.52180/2073-6487_ 2024_5_211_232

References

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Manuscript submission date: 12.09.2024

 

For citation:

Borisenko G.A. Neural networks to forecast stock prices based on news data // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2024. № 5. Pp. 211-232. (In Russ.).  https://doi.org/10.52180/2073-6487_ 2024_5_211_232 EDN: KJVYKJ

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The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 5/2024.  Finance.

Daria A. Dinets

Dr. Sci. (Econ.), Associate Professor, Head of the Department of the Finance and Credit, Peoples’ Friendship University of Russia named after Patrice Lumumba;

Leading Researcher, Institute for Research of Socio-Economic Transformations and Financial Policy, Financial University under the Government of the Russian Federation, Moscow, Russia

ORCID: 0000-0001-8734-8998

 

CONTRADICTIONS BETWEEN MONETARY AND FISCAL POLICIES: ANALYSIS OF THE CURRENT SITUATION AND POSSIBILITIES OF REDUCING THE LEVEL OF INTERGENERATIONAL DEBT

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Abstract

The article proposes the author’s approach to grouping countries according to the level of use of resources inherited from past generations, as well as resources “borrowed” from future generations. The sample of countries was grouped based on the increase in production capacity compared to the level of past generations, which characterized the degree of use of those achievements that were formed by past generations, or formed their own reproduction circuit based on the achievements of engineering trends and future technologies. Further, these countries were grouped on the basis of “predatory” use of resources to the detriment of future generations. At the junction of two grouping characteristics, the author’s grouping of countries according to the level of intergenerational debt was formed. An analysis of the influence of monetary and fiscal policies on the economies of the countries of each group was carried out. Conclusions are drawn about the possibility of reducing the level of intergenerational debt through policy coordination without the use of automatic rules or recommendations of the Washington Consensus. For each group of countries, their own characteristic features of the fiscal and monetary policies combination have been identified, which have a stronger impact on the dynamics of intergenerational debt.

Keywords: monetary policy, fiscal policy, resource consumption, productivity, growth, intergenerational debt.

JEL: H10, H60

EDN: UATXCM

DOI: https://doi.org/10.52180/2073-6487_ 2024_5_172_210

References

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Manuscript submission date: 11.09.2024 

 

For citation:

Dinets D.A. Contradictions between Monetary and Fiscal Policies: Analysis of the Current Situation and Possibilities of Reducing the Level of Intergenerational Debt // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2024. № 5. Pp. 172-210. (In Russ.).  https://doi.org/10.52180/2073-6487_ 2024_5_172_210 EDN: UATXCM

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 4/2024.  Finance.

Anastasia M. Matevosova

student of the Faculty of Economics of Moscow State University, Senior Laboratory Assistant at the Center for International Macroeconomics Research and Foreign Economic Relations, Institute of Economics of the Russian Academy of Sciences, Moscow, Russia

ORCID: 0009-0004-7490-5248

 

HIGH-FREQUENCY MODELING OF THE IMPACT OF SANCTIONS ON INFLATION EXPECTATIONS OF THE RUSSIAN POPULATION

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Abstract

This article examines the impact of sanctions concerns on the inflation expectations of the Russian population during the period of large-scale sanctions in 2022–2023. Using the methods of text processing of data from posts and comments on the social network, indicators of inflation expectations and sanctions concern were built with a weekly frequency and then used in econometric modeling. By evaluating autoregressive models of the integrated moving average with generalized autoregressive conditional heteroscedasticity in residuals and exogenous regressors (ARIMA-X-GARCH-X), an attempt has been made to model both the value and volatility of inflation expectations. As a result, it was revealed that increased sanctions concern, other things being equal, leads to an increase in inflation expectations, but does not affect the uncertainty of the population regarding inflation expectations. Despite the detection of weak structural changes, the degree of impact of sanctions concern on the inflation expectations of the Russian population is relatively stable in the period from March 2022 to December 2023.

Keywords: inflation expectations, sanctions, indicator, AutoRegressive Integrated Moving Average (ARIMA), Generalized AutoRegressive Conditional Heteroskedasticity (GARCH).

JEL: C22, C55, C58, C82, D84, E31, F51

EDN: VYHHCE

DOI: https://doi.org/10.52180/2073-6487_ 2024_4_139_158

References

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Manuscript submission date: 22.07.2024 

For citation:

Matevosova A.M. High-Frequency Modeling of the impact of sanctions on inflation expectations of the Russian population // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2024. № 4. Pp. 139-158. (In Russ.).  https://doi.org/10.52180/2073-6487_ 2024_4_139_158 EDN: VYHHCE

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 5/2024.  Finance.

Dmitry A. Kochergin

Dr. Sci. (Econ.), Assistant Professor, Chief Researcher, Institute of Economics of the Russian Academy of Sciences, Moscow, Russia

ORCID: 0000-0002-7046-1967

 

GLOBAL EXPERIENCE IN IMPLEMENTING CENTRAL BANKS DIGITAL CURRENCIES FOR RETAIL PAYMENTS IN EMERGING MARKETS AND DEVELOPING COUNTRIES

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Abstract

The article is devoted to the definition of current trends in the development of retail payments, the study of the motives for the introduction of digital currencies, the architecture and design features of retail CBDC systems in emerging markets and developing countries (EMDCs), as well as possible risks. Proposals have been formulated to improve the digital ruble project. As a result of the study, conclusions are drawn about the global trend of more and more expanding use of non-cash payment instruments and the growing competition between private payment service providers and the government. The key motives for the introduction of retail CBDCs are: expanding financial accessibility, improving the security of payments, offering digital money of universal use, etc. Having analyzed the experience of implementing rCBDC systems in developing economies we conclude that these countries use a two-tier architecture, hybrid infrastructure and different types of digital wallets. The main difficulties facing the adoption of rCBDCs in EMDCs include risks of cyber security, bank disintermediation, low adoption, etc. For widespread the adoption of rCBDCs in EMDCs, including in Russia, it is necessary to: eliminate fees for CBDC payments; expand storage limits and transaction amounts; support anonymous low-denomination payments; encourage the use of digital currency in government payments, etc.

Keywords: non-cash payments, central bank digital currencies (CBDCs), retail CBDCs, CBDC systems, digital wallets, disintermediation of banks, financial inclusion, monetary regulation, digital rouble.

JEL: E42, E50, E58

EDN: XGGDXK

DOI: https://doi.org/10.52180/2073-6487_ 2024_5_130_171

References

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Manuscript submission date: 27.06.2024 

 

For citation:

Kochergin D.A. Global experience in implementing central banks digital currencies for retail payments in emerging markets and developing countries // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2024. № 5. Pp. 130-171. (In Russ.).  https://doi.org/10.52180/2073-6487_ 2024_5_130_171 EDN: XGGDXK

  Creative Commons 4.0

The Bulletin of the Institute of Economics of the Russian Academy of Sciences № 4/2024.  Finance.

Sergey A. Perekhod

Lecturer at the Department of Financial Markets and Financial Engineering, Financial University under the Government of the Russian Federation, Moscow, Russia

ORCID: 0000-0002-4606-1226

 

Anna V. Mkhitaryan

Leading Software Engineer of the Department for Ensuring the Functioning and Development of the Digital Platform «Water Data» of the Sector for the Development of the CPU Water Components, Russian Research Institute for Integrated Use and Protection of Water Resources, Moscow, Russia

 

Daria S. Selifonkina

Leading Expert of the Second Department of Administrative and Economic Support of the Case Management, FAS of Russia, Moscow, Russia

 

INTERNATIONAL SANCTIONS AGAINST RUSSIA (2014–2024): ASSESSMENT AND IMPLICATIONS FOR THE FINANCIAL MARKET

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Abstract

In 2024, it has been exactly 10 years since the Russian financial market was under the influence of economic sanctions from the leading countries of the world economy. Despite attempts to destabilize and degrade the Russian market, the shocks from international sanctions have not had a serious destructive effect on it. The purpose of the study is to assess the impact of sanctions restrictions on various segments of the Russian financial market and determine the extent to which sanctions can contribute to its transformation and stable development. Statistical analysis for 2004–2023 showed that international sanctions have a negative impact: volatility in the money and capital markets has increased, the Russian ruble has devalued, and inflation has surged. At the same time, the sanctions contributed to the sovereignization of the Russian financial market, the growth of which began to be determined by internal sources of financing. The further development of the Russian financial market should be associated with reforms aimed at attracting domestic investment into the economy, unconventional monetary policy and reducing the outflow of private capital, as well as appealing to financial investments from friendly countries.

Keywords: sanctions, financial marker, bonds, rate, Bank of Russia, exchange rate.

JEL: G12, G21, G11

EDN: RWIZLA

DOI: https://doi.org/10.52180/2073-6487_ 2024_4_116_138

References

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Manuscript submission date: 13.07.2024 

For citation:

Perekhod S.A., Mkhitaryan A.V., Selifonkina D.S.  International sanctions against Russia (2014–2024): assessment and implications for the financial market // Vestnik Instituta Ekonomiki Rossiyskoy Akademii Nauk. 2024. № 4. Pp. 116-138. (In Russ.).  https://doi.org/10.52180/2073-6487_ 2024_4_116_138 EDN: RWIZLA

  Creative Commons 4.0

  1. Voskanian R.O. ECONOMIC ESSENCE OF MULTIPLE VOTING SHARES AND THE FEASIBILITY OF INTRODUCING THEM ON THE RUSSIAN FINANCIAL MARKET
  2. Lomonosov A.A. PROSPECTS FOR AN ACTIVE INVESTMENT STRATEGY USING THE EXAMPLE OF HEDGE FUNDS
  3. Osadchenko E.A. PROSPECTS FOR THE ORGANIZATION, REGULATION AND TAXATION OF MINING IN RUSSIA
  4. Rychkov V.V. ANALYSIS OF THE IMPACT OF THE SANCTIONS NEWS ON RUSSIAN FINANCIAL MARKETS

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