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Dynamic model of BSF portfolio management

https://doi.org/10.32362/2500-316X-2025-13-2-93-110

EDN: JCRKUO

Abstract

Objectives. The work compares studies on BSF portfolios consisting of a risk-free Bond (B) asset, a Stock (S), and a cash Flow (F) that represents risky asset prices in the form of a tree structure. On the basis of existing models for managing dynamic investment portfolios, the work develops a dynamic model for managing a BSF portfolio that combines risk-free and risky assets with a deposit. Random changes in the prices of a risky asset are reflected in the developed model according to a tree structure. Two approaches to portfolio formation are proposed for the study: (1) initial capital is invested in a risk-free asset, while management is conducted at the expense of a risky asset; (2) the initial capital is invested in a risky asset, but management is carried out at the expense of a risk-free asset.

Methods. A binomial model was used to predict the prices of risky assets. Changes in risky asset prices in the model are dynamically managed via a branching tree structure. A comparative analysis of modeling results reveals the optimal control method.

Results. A dynamic model for unrestricted management of a BSF portfolio has been developed. By presenting risky asset prices according to a tree structure, the model can be used to increase the accuracy of evaluating investments by from 2.4 to 2.7 times for the first approach and from 1.7 to 2.7 times for the second. The increased accuracy of evaluating investments as compared with previously proposed models is achieved by averaging prices at various vertices of the tree.

Conclusions. The results of the research suggest that the use of a dynamic management model based on a tree-like price structure can significantly increase the accuracy of evaluating investments in an investment portfolio.

About the Authors

Artur A. Mitsel
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Artur A. Mitsel, Dr. Sci. (Eng.), Professor, Department of Automated Control Systems

40, Lenina pr., Tomsk, 634050

Scopus Author ID 6603150769;

ResearcherID G-8307-2014


Competing Interests:

The authors declare no conflicts of interest.



Elena V. Viktorenko
Tomsk State University of Control Systems and Radioelectronics
Russian Federation

Elena V. Viktorenko, Senior Lecturer, Postgraduate Student, Department of Economics

40, Lenina pr., Tomsk, 634050 

ResearcherID AEJ-4949-2022


Competing Interests:

The authors declare no conflicts of interest.



References

1. Dombrovskii V.V., Lyashenko E.A. A Linear Quadratic Control for Discrete Systems with Random Parameters and Multiplicative Noise and Its Application to Investment Portfolio Optimization. Autom. Remote Control. 2003;64(10): 1558–1570. https://doi.org/10.1023/A:1026057305653 [Original Russian Text: Dombrovskii V.V., Lyashenko E.A. A Linear Quadratic Control for Discrete Systems with Random Parameters and Multiplicative Noise and Its Application to Investment Portfolio Optimization. Avtomatika i telemekhanika. 2003;10:50–65 (in Russ.).]

2. Dombrovskii V.V., Lyashenko E.A. Dynamic model of investment portfolio management in the financial market with stochastic volatility with regard transaction costs and restrictions. Vestnik Tomskogo gosudarstvennogo universiteta = Tomsk State University J. 2006;S16:217–225. (in Russ.).

3. Dombrovskii V.V., Dombrovskii D.V., Lyashenko E.A. Predictive control of random-parameter systems with multiplicative noise. Application to investment portfolio optimization. Autom. Remote Control. 2005;66(4):583–595. https://doi.org/10.1007/s10513-005-0102-5 [Original Russian Text: Dombrovskii V.V., Dombrovskii D.V., Lyashenko E.A. Predictive control of random-parameter systems with multiplicative noise. Application to investment portfolio optimization. Avtomatika i telemekhanika. 2005;4: 84–97 (in Russ.).]

4. Gerasimov E.S., Dombrovskii V.V. Dynamic network model of investment management control for quadratic risk function. Autom. Remote Control. 2002;63(2):280–288. https://doi.org/10.1023/A:1014251725737 [Original Russian Text: Gerasimov E.S., Dombrovskii V.V. Dynamic network model of investment management control for quadratic risk function. Avtomatika i telemekhanika. 2002;2:119–128 (in Russ.).]

5. Dombrovskii V.I., Galperin V.A. Dynamic model of investments portfolio selection by quadratic risk function. Vestnik Tomskogo gosudarstvennogo universiteta = Tomsk State University J. 2000;269:73–75 (in Russ.).

6. Galperin V.A., Dombrovskii V.I. Dynamic management of a self-financing investment portfolio with a quadratic risk function in discrete time. Vestnik Tomskogo gosudarstvennogo universiteta = Tomsk State University J. 2002;(S1-1):141–146 (in Russ.).

7. Dombrovskii V.I., Galperin V.A. Investment portfolio management in continuous time with a quadratic risk function. In: Proceedings of the 10th Anniversary Symposium on Nonparametric and Robust Statistical Methods in Cybernetics. Tomsk: TSU; 2004. P. 185–192 (in Russ.). https://elibrary.ru/xwjkax

8. Galperin V.A., Dombrovskii V.I. Dynamic management of an investment portfolio taking into account abrupt changes in prices of financial assets. Vestnik Tomskogo gosudarstvennogo universiteta = Tomsk State University J. 2003;280:112–117 (in Russ.).

9. Dombrovskii V.V., Dombrovskii D.V., Lyashenko E.A. Dynamic optimization of the investment portfolio under restrictions on the volume of investments in financial assets. Vestnik Tomskogo gosudarstvennogo universiteta = Tomsk State University J. 2008;1:13–17 (in Russ.).

10. Dombrovskii V.V., Pashinskaya T.Yu. Predictive control strategies for investment portfolio in the financial market with hidden regime switching. Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie vychislitelnaja tehnika i informatika = Tomsk State University Journal of Control and Computer Science. 2020;50:4–13 (in Russ.).

11. Grineva N.V. Dynamic optimization of the investment portfolio management trajectory. Problemy ekonomiki i yuridicheskoi praktiki = Economic Problems and Legal Practice. 2021;17(3):73–77. https://doi.org/10.33693/2541-8025-2021-17-3-73-77

12. Ivanyuk V. Proposed Model of a Dynamic Investment Portfolio with an Adaptive Strategy. Mathematics. 2022;10(23):4394. https://doi.org/10.3390/math10234394

13. Mitsel A.A., Krasnenko N.P. Dynamic model of investment portfolio management with linear criterion of quality. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki (Doklady TUSUR) = Proceedings of TUSUR University. 2014;34:176–182 (in Russ.).

14. Kolyasnikova E.R. Hedging strategy in the (B, S, F)-market model. Obozrenie prikladnoi i promyshlennoi matematiki = OP&PM Surveys of Applied and Industrial Mathematics. 2009;16(3):467–468 (in Russ.).

15. Bronshtein E.M., Kolyasnikova E.R. The (B, S, F)-market Model and hedging strategies. Upravlenie riskom = Management of Risk. 2010;2:55–64 (in Russ.).

16. Bronshtein E.M., Kolyasnikova E.R. Approximate hedging strategy in the (B, S, F)-market model. Matematicheskoe modelirovanie = Math. Model. 2010;22(11):29–38 (in Russ.).

17. Davnis V.V., Bogdanova S.Yu., Suyunova G.B. Models of (B, S)-market and risk-neutral price of options. Vestnik OrelGIET = OrelSIET Bulletin. 2010;1:134–140 (in Russ.).

18. Davnis V.V., Fedoseev A.M. Adaptive model-bulding of (B, S)-market. Sovremennaya ekonomika: problemy i resheniya = Modern Economics: Problems and Solutions. 2011;6(18):202–213 (in Russ.).

19. Fedoseev A.M., Korotkikh V.V. Features valuation of options on complete and incomplete markets. Sovremennaya ekonomika: problemy i resheniya = Modern Economics: Problems and Solutions. 2011;4(16):137–144 (in Russ.).

20. Almeida C., Freire G. Pricing of index options in incomplete markets. J. Fin. Economic. 2022;144(1):174–205. https://doi.org/10.1016/j.jfineco.2021.05.041

21. Davnis V.V., Davnis V.V. Econometric options for the (B, S, I)-market models. Sovremennaya ekonomika: problemy i resheniya = Modern Economics: Problems and Solutions. 2013;10(46):154–165 (in Russ.). Available from URL: https://journals.vsu.ru/meps/article/view/7987

22. Krotov V.F., Lagosha B.A., Lobanov S.M., Danilov N.I., Sergeev S.I. Osnovy teorii optimal’nogo upravleniya (Fundamentals of Optimal Control Theory). Moscow: Vysshaya shkola; 1990. 430 p. (in Russ.).

23. Athans M. The Matrix Minimum Principle. Information and Control. 1967;11(5–6):592–606. https://doi.org/10.1016/S0019-9958(67)90803-0


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1. Risky asset prices
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Type Исследовательские инструменты
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  • A dynamic model for unrestricted management of a BSF portfolio was developed.
  • By presenting risky asset prices according to a tree structure, the model can be used to increase the accuracy of evaluating investments by from 2.4 to 2.7 times for the first approach and from 1.7 to 2.7 times for the second.
  • The increased accuracy of evaluating investments as compared with previously proposed models is achieved by averaging prices at various vertices of the tree.

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Mitsel A.A., Viktorenko E.V. Dynamic model of BSF portfolio management. Russian Technological Journal. 2025;13(2):93-110. https://doi.org/10.32362/2500-316X-2025-13-2-93-110. EDN: JCRKUO

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ISSN 2782-3210 (Print)
ISSN 2500-316X (Online)