Basharina, Olga and Baranova, Nina and Larin, Sergey (2023): Разработка и апробация цифровой модели принятия эффективных инвестиционных решений для формирования стратегий развития экономических субъектов. Published in: Economic Analysis: Theory and Practice , Vol. 22, No. 9 (28 September 2023): pp. 1699-1724.
Preview |
PDF
MPRA_paper_119334.pdf Download (1MB) | Preview |
Abstract
Subject. Sanction restrictions sharply decreased possibilities to attract external borrowings and substantiated the expediency of internal investments. This necessitated software tools enabling calculations and investment decisions. The developed a digital model of ISPI (Information System Portfolio Investor) will help make smart investment decisions, including at the government level. Objectives. The study aims to build a digital model to identify the most attractive investment areas at the regional, country, and cross-country level. Methods. The ISPI model is based on the Markowitz portfolio theory, the Profitability-Risk Model (PRM), and optimization methods. For our calculations, we used yields on Major and Sector Indices of the UK, India, China, USA, France, South Africa for 2014–2021, in one-month increments. Results. Using the developed ISPI model, we constructed scatter plots of leading stock market indices and identified the leading sectors of national economies of the studied countries and the most attractive investment areas. We solved the problem of finding a global optimum for the studied countries, differentiated the leading economic sectors by the level of investment risk, determined that an international portfolio is the most preferable for investment. Conclusions. Our ISPI model helps investors identify a region or country for smart investments. The model enables to determine industries in which investing is most justified within the nearest investment horizon. The model also helps identify the most appropriate financial instruments for investing in individual countries.
Item Type: | MPRA Paper |
---|---|
Original Title: | Разработка и апробация цифровой модели принятия эффективных инвестиционных решений для формирования стратегий развития экономических субъектов |
English Title: | Building and testing a digital model for effective investment decisions to form strategies for development of economic entities |
Language: | Russian |
Keywords: | economic entity, economic development, ISPI digital model, effective investment solution. |
Subjects: | E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E22 - Investment ; Capital ; Intangible Capital ; Capacity F - International Economics > F6 - Economic Impacts of Globalization > F63 - Economic Development G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation O - Economic Development, Innovation, Technological Change, and Growth > O5 - Economywide Country Studies |
Item ID: | 119334 |
Depositing User: | Mr. Sergey Larin |
Date Deposited: | 11 Dec 2023 15:33 |
Last Modified: | 11 Dec 2023 15:33 |
References: | 1. Apergis, N., Hayat, T. & Saeed, T. (2019) The Role of Happiness in Financial Decisions: Evidence from Financial Portfolio Choice and Five European Countries // Atl Econ J., Vol. 47, P. 343-360. https://doi.org/10.1007/s11293-019-09629-2 2. Binyan Jiang, Cheng Liu, Cheng Yong Tang (2023) Dynamic Covariance Matrix Estimation and Portfolio Analysis with High-Frequency Data // Journal of Financial Econometrics, nbad003. https://doi.org/10.1093/jjfinec/nbad003 3. Burger, J.D., Warnock, F.E., & Warnock, V.C. (2018) Benchmarking Portfolio Flows // IMF Econ Rev, Vol. 66, P. 527–563. https://doi.org/10.1057/s41308-018-0062-8 4. Chen, J.M. (2016) Modern Portfolio Theory. In: Postmodern Portfolio Theory. Quantitative Perspectives on Behavioral Economics and Finance. New York: Palgrave Macmillan https://doi.org/10.1057/978-1-137-54464-3_2 5. Dantzig, G.B. (1963) Linear Programming and Extensions Princeton. N.J.: Princeton Univ. Press 6. Gandolfo, G. (2016) Portfolio and Macroeconomic Equilibrium in an Open Economy. In: International Finance and Open-Economy Macroeconomics. Springer Texts in Business and Economics. Berlin, Heidelberg: Springer, P. 265-310. https://doi.org/10.1007/978-3-662-49862-0_13 7. Gercekovich D.A (2017) Construction of optimal investment portfolio based on efficient portfolios complex // Moscow University Economics Bulletin, Iss. 5, P. 86-101. (In Russ.). 8. Gercekovich, D.A, & Babushkin, R.V. (2019) Dynamic portfolio analysis of stock indices // The world of economy and management, Vol. 19, No 4, P. 14-30. (In Russ.). 9. Gertsekovich D.A., Podlinyaev O.L., Chumak N.A., Larin S.N. (2021a) Formation of an integrated system of investment strategies based on the use of basic and sectoral stock market indices developed and developing countries // Journal of Economy and entrepreneurship, Vol. 15, No. 7. P. 41-46 DOI: 10.34925/EIP.2021.132.7.004. (In Russ.). 10. Gercekovich D.A, Gorbachevskaya E.Yu., Shilnikova I.S. (2021b) Identification of basic criteria of portfolio analysis based on the rolling verification principle. Conference: 1st International Workshop on AICTS, P. 57-63. Doi: 10.47350/AICTS.2020.06. 11. Graham B. (2018) The Intelligent Investor. New York: HarperCollins Publishers. 12. Ivesting.com – quotes and financial news. URL: https://www. investing.com, accessed on 30 September 2022 13. Jeyachitra, A., Selvam, M., & Gayathri, J. (2010) Portfolio Risk and Return Relationship - An Empirical Study // Asia-Pacific Journal of Management Research and Innovation, Vol. 6, Iss.4. https://doi.org/10.1177/097324701000600406 14. Haan, M.A., Hauck, D. (2023) Games with possibly naive present-biased players // Theory Decis. https://doi.org/10.1007/s11238-023-09924-0 15. Kantorovich L.V. (1959) Economic calculation of the best use of resources. M.: USSR Academy of Sciences. (In Russ.). 16. Maiti, M. (2021). Efficient Frontier and Portfolio Optimization. In: Applied Financial Econometrics. Singapore: Palgrave Macmillan. https://doi.org/10.1007/978-981-16-4063-6_4 17. Makbule Kandakoglu, Grit Walther, & Sarah Ben Amor (2022) A robust multicriteria clustering methodology for portfolio decision analysis // Computers & Industrial Engineering, Vol. 174, 108803 https://doi.org/10.1016/j.cie.2022.108803 18. Markowitz, H.M. (1952) Portfolio selection // Journal of Finance, Vol. 7, No 1, P. 77-91. 19. Meunier, L. & Ohadi, S. (2023) When are two portfolios better than one? A prospect theory approach // Theory Decis, Vol. 94, P. 503-538. https://doi.org/10.1007/s11238-022-09901-z 20. Narayan, S., & Rehman M.U. (2020) International portfolio strategies and opportunities: the case of the U.S., Japan and Asia // Financ Res Lett, Vol. 37, 101358. https://doi.org/10.1016/j.frl.2019.101358 21. Nagler, M.G. (2023) Thoughts matter: a theory of motivated preference // Theory Decis, Vol. 94, P. 211–247. https://doi.org/10.1007/s11238-022-09891-y 22. Pilipenko A.I., Dikhtiar V.I. & Baranova N.M. (2019) ‘Financial stability’ safeguarding: modelling the Russian budgetary policy // Int. J. Economic Policy in Emerging Economies, Vol. 12, No.1, P. 85-99 23. Ramzi Nekhili, Elie Bouri (2023) Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management // Energy Economics, Vol. 119, 106596 https://doi.org/10.1016/j.eneco.2023.106596 24. Reilly, Frank K. (2000) Investment analysis and portfolio management / Frank K. Reilly, Keith C. Brown, 6th ed. Singapore [etc.]: South-Western/Thomson learning. ISBN 0-03-025809-X 25. Samuel R. Kaplan (2015) Portfolio Analysis for Vector Calculus // PRIMUS, Vol. 25, Iss. 1, P. 31-40. https://doi.org/10.1080/10511970.2014.899533 26. Scott Musman and Andrew Turner (2017) A game theoretic approach to cyber security risk management // The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, Vol. 15, Iss. 2. https://doi.org/10.1177/1548512917699724 27. Takuya Okabe, Jin Yoshimura (2022) A new long-term measure of sustainable growth under uncertainty // PNAS Nexus, Vol. 1, Iss. 5, pgac228. https://doi.org/10.1093/pnasnexus/pgac228 28. Taras Bodnar, Nestor Parolya & Wolfgang Schmid (2021) Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty // Quantitative Finance, Vol. 21, Iss. 2, P. 221-242 https://doi.org/10.1080/14697688.2020.1748214 29. Tsay R., Chen R. (2019). Nonlinear Time Series Analysis. Hoboken, NJ: John Wiley & Sons |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/119334 |