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Modelling and Data Analysis
2023. Vol. 13, no. 4, 140–152
https://doi.org/10.17759/mda.2023130408
ISSN: 2219-3758 / 2311-9454 (online)

Bond Portfolio Selection in the Cox-Ingersoll-Ross Framework by the Probabilistic Criterion

 
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Abstract

The problem of bond portfolio selection is considered in Cox-Ingersoll-Ross framework. The probability function is chosen as an optimality criterion, which leads to a stochastic optimization problem, The problem is solved using a smooth approximation of the probability function and its derivatives via gradient projection method. An example is provided.

General Information

Keywords: bond stochastic programming, probability function, bond portfolio, Cox-Ingersoll-Ross model

Journal rubric: Software

OpenAlex citations: 0

OpenAlex topics: Stochastic processes and financial applications, Risk and Portfolio Optimization, Financial Markets and Investment Strategies

Information about the work in OpenAlex

Number of citations: 0

Topics

Stochastic processes and financial applications

This cluster of papers focuses on the theory and applications of option pricing models, including topics such as stochastic calculus, jump diffusion, volatility modeling, mean field games, term structure models, risk premia, Monte Carlo simulation, and market microstructure noise in the context of financial economics.

Number of works: 113503  |  Total number of citations: 1609064

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Risk and Portfolio Optimization

This cluster of papers focuses on robust optimization techniques for risk management and finance, including topics such as conditional value-at-risk, stochastic programming, portfolio optimization, uncertain data, coherent risk measures, and the Wasserstein metric. The papers explore methodologies and applications of robust optimization in addressing uncertainty and risk in financial decision-making.

Number of works: 33529  |  Total number of citations: 405468

Topic detailsв OpenAlex

Financial Markets and Investment Strategies

This cluster of papers explores asset pricing models, stock returns, market efficiency, investor sentiment, liquidity risk, behavioral finance, momentum investing, market microstructure, hedge funds, and the information content of various factors affecting asset prices.

Number of works: 138504  |  Total number of citations: 3379345

Topic detailsв OpenAlex

Work details in OpenAlex

Article type: research article

DOI: https://doi.org/10.17759/mda.2023130408

Funding. The reported study was funded by Russian Science Foundation (RSF), project number 22-21-00213

Received 09.09.2023

Accepted

Published

For citation: Sobol, V.R., Torishniy, R.O. (2023). Bond Portfolio Selection in the Cox-Ingersoll-Ross Framework by the Probabilistic Criterion. Modelling and Data Analysis, 13(4), 140–152. (In Russ.). https://doi.org/10.17759/mda.2023130408

© Sobol V.R., Torishniy R.O., 2023

License: CC BY-NC 4.0

References

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  4. Ignatov A.N., Kibzun A.I. Dvuhshagovaya zadacha formirovaniya portfelya cennyh bumag iz dvuh riskovyh aktivov po veroyatnostnomu kriteriyu // Avtomatika i telemekhanika. 2015. №7. P. 78–100.
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  6. Barysheva A.E., Markov A.S., Micel' A.A. Ocenka VaR pri negaussovom raspredelenii dohodnostej aktivov // Rossijskij tekhnologicheskij zhurnal. 2020. №8(2). pp.67-84.
  7. Vasicek O. An equilibrium characterization of the term structure // J. Financial Economics. 1977. V. 5. pp. 177-188.
  8. Cox J., Ingersoll J., Ross S. A Theory of the term structure of interest rate // Econometrica. 1985. V. 53. pp. 385-407.
  9. Kan Yu.S., Sysuev A.V. O priblizhennom reshenii zadachi formirovaniya portfelya cennyh bumag s fiksirovannym dohodom // Avtomatika i telemekhanika. 2010. № 6. pp. 130–141.
  10. Sobol' V.R., Torishnyj R.O. O gladkoj approksimacii veroyatnostnyh kriteriev v zadachah stohasticheskogo programmirovaniya // Tr. SPIIRAN. V. 19. № 1. 2020. pp. 180—217
  11. Sobol V., Torishnyi R. Smooth approximation of probability and quantile functions: vector generalization and its applications // Journal of Physics: Conference Series. 1925 012034. 2021. pp. 1–10.
  12. Torishnyj R.O. Programmnyj kompleks dlya analiza zadach stohasticheskogo programmirovaniya s veroyatnostnym kriteriem // VKiT. 2022. V. 19. No 5(215). pp. 3–12.

Information About the Authors

Vitalyi R. Sobol, Candidate of Science (Physics and Matematics), Associate Professor, Department 804 "Probability Theory and Computer Modeling", Moscow Aviation Institute (National Research University) (MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-1275-0445, e-mail: vitsobol@mail.ru

Roman O. Torishniy, Engineer of Department, 804 "Probability Theory and Computer Modeling", Moscow Aviation Institute (National Research University) (MAI), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-9732-6247, e-mail: arenas-26@yandex.ru

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