Optimization of an investment portfolio using analytical and financial monitoring tools

Purpose of the research - To examine modern methods of investment portfolio optimization with an emphasis on risk and volatility management, and to explore the integration of financial monitoring tools in ensuring regulatory compliance and operational resilience.

Methodology - The study is based on the modeling and analysis of a diversified hypothetical investment portfolio containing stocks, bonds, and ETFs. It combines classical optimization theories—such as the Markowitz model and Sharpe ratio—with advanced tools including Value-at-Risk (VaR), Conditional Valueat-Risk (CVaR), stress testing, and machine learning algorithms for volatility forecasting and asset allocation.

Originality/value - This research provides a synthesis of traditional financial models and modern datadriven techniques. A notable contribution is the applied use of financial monitoring systems—used by secondtier banks—to assess portfolio stability and regulatory risk under the frameworks of AML/CFT and Basel III.

Findings - The results show that implementing innovative risk management and optimization strategies significantly enhances portfolio performance and resilience. Empirical analysis demonstrates that financial monitoring, when combined with CVaR-based modeling and stress scenarios, contributes to better decisionmaking, reduced exposure to extreme losses, and improved compliance.

1. Baibulekova, L., Turysbekova, R., Kasymbekova, G., Shiganbaeva, N., & Kuzhukeeva, K. (2024). Riski investitsionnykh portfeley bankov Kazakhstana: problemy i puti ikh resheniya. Statistika, uchet i audit, 3(94), 128–140. https://doi.org/10.51579/1563-2415.2024.-3.10

2. Konovalova, M. E., & Abuzov, A. Yu. (2024). Matematicheskaya model' optimizatsii portfelya investitsiy s uchetom riska i finansovykh ogranicheniy v upravlenii predpriyatiem. Fundamental'nye issledovaniya, 1, 20- 24. https://fundamental-research.ru/ru/article/view?id=43551 (Data obrashcheniya: 08.05.2025). DOI: https://doi.org/10.17513/fr.43551

3. Nikulin, M. V. (2024). Povyshenie effektivnosti upravleniya portfelnymi riskami: sravnitel'noe issledovanie razlichnykh podkhodov. Promyshlennaya ekonomika, 4. https://cyberleninka.ru/article/n/povyshenie-effektivnosti-upravleniya-portfelnymi-riskami-sravnitelnoe-issledovanie-razlichnyh-podhodov (Data obrashcheniya: 15.05.2025).

4. Smaglii, N. V., Tyurin, E. E., & Dragulenko, V. V. (2024). Metody optimizatsii portfel'nykh investitsiy v usloviyakh neopredelennosti. Ekonomika i predprinimatel'stvo, 1(162), 804-808. DOI: 10.34925/ EIP.2024.162.1.154 https://elibrary.ru/item.asp?id=60033934

5. Igarashi, D. M., Matioli, L. C., & Bello, T. L. (2018). Teoriya portfelya Markovitsa i stoimost' pod riskom primenitel'no k portfelyu aktsiy BOVESPA. 50-y Brazilskiy simpozium po issledovaniyam operatsiy, Rio-de-Zhaneiro. https://proceedings.science/sbpo/sbpo-2018/trabalhos/teoria-de-portfolios-de-markowitz-evalue-at-risk-aplicados-a-um-portfolio-de-ac?lang=pt-br

6. Sergeev, A. V. (2021). Metody optimizatsii investitsionnogo portfelya i analiza aktivov. Mezhdunarodnaya konferentsiya IEEE po sistemam, cheloveku i kibernetike. DOI:10.36871/2618-9976.2021.02.009, https://slib.com/en/issues/smc_2021_02_a9/

7. Kuzhelnyi, D. S., Materova, E. S., Ruzhanskaya, N. V., & Sharafullina, R. R. (2024). Organizatsiya i optimizatsiya investitsionnogo portfelya aktsiy rossiyskikh kompaniy. Ekonomika i predprinimatel'stvo. ДОИ: 10.34925/EIP.2024.164.3.135

8. Kandaurov, D. V. (2016). Effektivnost' mezhdunarodnoy diversifikatsii s tochki zreniya upravlyayushchego paevym investitsionnym fondom. Rossiyskoe predprinimatel'stvo, 17(23), 3463–3486. DOI: 10.18334/rp.17.23.37158 https://1economic.ru/lib/37158

9. Boslovyak, S. V. (2018). Korporativnye obligatsii v sisteme investitsionnogo banking. Vestnik Polotskogo gosudarstvennogo universiteta. Seriya D. Ekonomicheskie i yuridicheskie nauki, 13. https://cyberleninka.ru/article/n/korporativnye-obligatsii-v-sisteme-investitionnogo-bankinga (Data obrashcheniya: 08.05.2025).

10. Guzhin, A. A., & Ezhkova, V. G. (2017). Risk-menedzhment i metody upravleniya riskami. Innovatsii i investitsii, 2. https://cyberleninka.ru/article/n/risk-menedzhment-i-metody-upravleniya-riskami (Data obrashcheniya: 18.05.2025).

11. Metropolis, N., & Ulam, S. (2007). The Monte Carlo Method. Journal of the American Statistical Association, 44(247), 335-341. Stable URL: http://links.jstor.org/sici?sici=0162-1459%28194909%2944%3A247%3C335%3ATMCM%3E2.0.CO%3B2-3

12. Orlova, L. N., & Sayakhetdinov, A. R. (2023). Metodiki kolichestvennoy otsenki riskov na osnove VAR: sravnitel'nyy analiz. Intellekt. Innovatsii. Investitsii, 2. https://cyberleninka.ru/article/n/metodikikolichestvennoy-otsenki-riskov-na-osnove-var-sravnitelnyy-analiz (Data obrashcheniya: 19.05.2025).

13. Bota, M. (2011). Stoimost' riska portfelya, skorrektirovannaya na likvidnost'. Yuzhnoafrikanskiy zhurnal ekonomicheskikh i upravlencheskikh nauk, 11(2), 203-216. DOI: https://doi.org/10.4102/sajems.v11i2.309

14. Eriashvili, N. D., & Tepman, L. N. (2014). Upravlenie investitsionnymi riskami. Vestnik Moskovskogo universiteta MVD Rossii, 12. https://cyberleninka.ru/article/n/upravlenie-investitsionnymi-riskami-3

15. Myasin, A. V. (2013). Stsenarnoe modelirovanie i stress-testirovanie roznichnogo kreditnogo portfelya banka. Imushchestvennye otnosheniya v RF, 6(141). https://cyberleninka.ru/article/n/stsenarnoemodelirovanie-i-stress-testirovanie-roznichnogo-kreditnogo-portfelya-banka3-2415.2024.-3.10