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Stochastic optimality in the portfolio tracking problem involving investor’s temporal preferences

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Abstract

We consider an optimal portfolio selection problem to track a riskless reference portfolio. Portfolio management strategies are compared taking into account the investor’s temporal preferences. We investigate stochastic optimality of the strategy that minimizes the expected long-run cost, deriving an asymptotical upper (almost sure) estimate for the difference between the values of the objective functional corresponding to the optimal strategy and for any admissible control.

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References

  1. Belkina, T.A. and Palamarchuk, E.S., On Stochastic Optimality for a Linear Controller with Attenuating Disturbances, Autom. Remote Control, 2013, vol. 74, no. 4, pp. 628–641.

    Article  MathSciNet  MATH  Google Scholar 

  2. Gerasimov, E.S. and Dombrovskii, V.V., Dynamic Network Model of Investment Control for Quadratic Risk Function, Autom. Remote Control, 2002, vol. 63, no. 2, pp. 280–288.

    Article  MathSciNet  MATH  Google Scholar 

  3. Cramer, H. and Leadbetter, M.R., Stationary and Related Stochastic Processes. Sample Function Properties and Their Applications, New York: Wiley, 1967.

    MATH  Google Scholar 

  4. Palamarchuk, E.S., Asymptotic Behavior of the Solution to a Linear Stochastic Differential Equation and Almost Sure Optimality for a Controlled Stochastic Process, Comput. Math. Math. Phys., 2014, vol. 54, no. 1, pp. 83–96.

    Article  MathSciNet  MATH  Google Scholar 

  5. Palamarchuk, E.S., Risk Estimation in Linear Economic Systems for Negative Time Preferences, Ekon. Mat. Metody, 2013, vol. 49, no. 3, pp. 99–116.

    Google Scholar 

  6. Ait Rami, M. et al., Solvability and Asymptotic Behavior of Generalized Riccati Equations Arising in Indefinite Stochastic LQ Controls, IEEE Trans. Automat. Control, 2001, vol. 46, no. 3, pp. 428–440.

    Article  MathSciNet  MATH  Google Scholar 

  7. Aumann, R.J. and Serrano, R., An Economic Index of Riskiness, J. Polit. Economy, 2008, vol. 116, no. 5, pp. 810–836.

    Article  MATH  Google Scholar 

  8. Dragan, V., Morozan, T., and Stoica, A.M., Mathematical Methods in Robust Control of Linear Stochastic Systems, New York: Springer, 2006.

    MATH  Google Scholar 

  9. Karatzas, I. and Shreve, S.I., Methods of Mathematical Finance, New York: Springer, 1998.

    Book  MATH  Google Scholar 

  10. Kohlmann, M. and Tang, S., Multidimensional Backward Stochastic Riccati Equations and Applications, SIAM J. Control Optimiz., 2003, vol. 41, no. 6, pp. 1696–1721.

    Article  MathSciNet  MATH  Google Scholar 

  11. Lim, A.E.B. and Wimonkittiwat, P., Dynamic Portfolio Selection with Market Impact Costs, Operat. Res. Lett., 2014, vol. 42, no. 5, pp. 299–306.

    Article  MathSciNet  Google Scholar 

  12. Pantelous, A.A., Zimbidis, A.A., and Kalogeropoulos, G.I., A Theoretic Stochastic Dynamic Control Approach for the Lending Rate Policy, Neural, Parallel Sci. Computat., 2010, vol. 18, no. 3, pp. 307–332.

    MATH  Google Scholar 

  13. Willems, J.L. and Willems, J.C., Feedback Stabilizability for Stochastic Systems with State and Control Dependent Noise, Automatica, 1976, vol. 12, no. 3, pp. 277–283.

    Article  MathSciNet  MATH  Google Scholar 

  14. Yao, D.D., Zhang, S., and Zhou, X.Y., Tracking a Financial Benchmark Using a Few Assets, Operat. Res., 2006, vol. 54, no. 2, pp. 232–246.

    Article  MathSciNet  MATH  Google Scholar 

  15. Yao, D.D., Zhang, S., and Zhou, X.Y., Stochastic Linear-Quadratic Control via Semidefinite Programming, SIAM J. Control Optimiz., 2001, vol. 40, no. 3, pp. 801–823.

    Article  MathSciNet  MATH  Google Scholar 

  16. Yong, J. and Zhou X.Y., Stochastic Controls: Hamiltonian Systems and HJB Equations, New York: Springer, 1999.

    Book  MATH  Google Scholar 

  17. Zhou, X.Y., Markowitz’s World in Continuous Time, and Beyond, in Stochastic Modeling and Optimization with Applications in Queues, Finance, and Supply Chains, New York: Springer, 2003, pp. 279–309.

    Google Scholar 

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Correspondence to E. S. Palamarchuk.

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Original Russian Text © E.S. Palamarchuk, 2015, published in Upravlenie Bol’shimi Sistemami, 2015, No. 56, pp. 123–142.

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Palamarchuk, E.S. Stochastic optimality in the portfolio tracking problem involving investor’s temporal preferences. Autom Remote Control 78, 1523–1536 (2017). https://doi.org/10.1134/S0005117917080124

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  • DOI: https://doi.org/10.1134/S0005117917080124

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