137
Views
9
CrossRef citations to date
0
Altmetric
Articles

Continuous-time mean variance portfolio with transaction costs: a proximal approach involving time penalization

, & ORCID Icon
Pages 91-111 | Received 23 Feb 2018, Accepted 28 Aug 2018, Published online: 26 Sep 2018

References

  • Amornwattana, S., D. Enke, and C. H. Dagli. 2007. “A Hybrid Option Pricing Model Using a Neural Network for Estimating Volatility.” International Journal of General Systems 36 (5): 558–573. doi: 10.1080/03081070701210303
  • Ang, A., and G. Bekaert. 2002. “International Asset Allocation With Regime Shifts.” The Review of Financial Studies 15 (4): 1137–1187. doi: 10.1093/rfs/15.4.1137
  • Attouch, H., and A. Soubeyran. 2011. “Local Search Proximal Algorithms as Decision Dynamics with Costs to Move.” Set-Valued and Variational Analysis 19: 157–177. doi: 10.1007/s11228-010-0139-7
  • Bao, T. Q., B. S. Mordukhovich, and A. Soubeyran. 2015. “Variational Analysis in Psychological Modeling.” Journal of Optimization Theory and Applications 164 (1): 290–315. doi: 10.1007/s10957-014-0569-8
  • Best, M. J., and J. Hlouskova. 2003. “Portfolio Selection and Transactions Costs.” Computational Optimization and Applications 24 (1): 95–116. doi: 10.1023/A:1021806200854
  • Carrillo, L., J. Escobar, J. B. Clempner, and A. S. Poznyak. 2016. “Solving Optimization Problems in Chemical Reactions Using Continuous-Time Markov Chains.” Journal of Mathematical Chemistry 54: 1233–1254. doi: 10.1007/s10910-016-0620-0
  • Chen, W.. 2015. “Artificial Bee Colony Algorithm for Constrained Possibilistic Portfolio Optimization Problem.” Physica A 429: 125–139. doi: 10.1016/j.physa.2015.02.060
  • Clempner, J. B., and A. S. Poznyak. 2014. “Simple Computing of the Customer Lifetime Value: A Fixed Local-Optimal Policy Approach.” Journal of Systems Science and Systems Engineering 23 (4): 439–459. doi: 10.1007/s11518-014-5260-y
  • Clempner, J. B., and A. S. Poznyak. 2018. “Sparse Mean-Variance Customer Markowitz Portfolio Selection For Markov Chains: A Tikhonov's Regularization Penalty Approach.” Optimization and Engineering 19 (4): 383–417. doi: 10.1007/s11081-018-9374-9
  • Costa, O. L. V., and M. V. Araujo. 2008. “A Generalized Multi-Period Portfolio Optimization with Markov Switching Parameters.” Automatica 44 (10): 2487–2497. doi: 10.1016/j.automatica.2008.02.014
  • Das, S., A. Halder, and D. D. Dey. 2016. “Regularizing Portfolio Risk Analysis: A Bayesian Approach.” Methodology and Computing in Applied Probability 19 (3): 865–889. doi: 10.1007/s11009-016-9524-5
  • Guo, X., and O. Hernández-Lerma. 2009. Continuos–Time Markov Decision Processes: Theory and Applications. Berlin: Springer.
  • Honda, T.. 2003. “Optimal Portfolio Choice for Unobservable and Regime-Switching Mean Returns.” Journal of Economic Dynamics and Control 28: 45–78. doi: 10.1016/S0165-1889(02)00106-9
  • Huang, X.. 2008. “Expected Model for Portfolio Selection with Random Fuzzy Returns.” International Journal of General Systems 37 (3): 319–328. doi: 10.1080/03081070601176422
  • Konno, H., K Akishino, and R. Yamamoto. 2005. “Optimization of a Long-Short Portfolio Under Nonconvex Transaction Cost.” Computational Optimization and Applications 32 (1–2): 115–132. doi: 10.1007/s10589-005-2056-5
  • Li, D., and W. L. Ng. 2000. “Optimal Dynamic Portfolio Selection: Multi-Period Mean-Variance Formulation.” Mathematical Finance 10: 387–406. doi: 10.1111/1467-9965.00100
  • Markowitz, H.. 1952. “Portfolio Selection.” The Journal of Finance 7: 77–98.
  • Moreno, F. G., P. R. Oliveira, and A. Soubeyran. 2011. “A Proximal Algorithm with Quasidistance. Application to Habit's Formation.” Optimization 61: 1383–1403. doi: 10.1080/02331934.2011.564623
  • Najafi, A. A., and S. Mushakhian. 2015. “Multi-Stage Stochastic Mean-Semivariance-CVaR Portfolio Optimization Under Transaction Costs.” Applied Mathematics and Computation 256: 445–458. doi: 10.1016/j.amc.2015.01.050
  • Palczewski, J., R. Poulsen, H. Schenk-Hoppe, and R. Klaus. 2015. “Dynamic Portfolio Optimization with Transaction Costs and State-Dependent Drift.” European Journal of Operational Research 243: 921–931. doi: 10.1016/j.ejor.2014.12.040
  • Pliska, S. R.. 1997. Introduction to Mathematical Finance. Malden: Basil Blackwell.
  • Poznyak, A. S., K. Najim, and E. Gomez-Ramirez. 2000. Self-learning Control of Finite Markov Chains. New York: Marcel Dekker.
  • Samuelson, P. A.. 1969. “Lifetime Portfolio Selection by Dynamic Stochastic Programming.” The Review of Economics and Statistics 51 (3): 239–246. doi: 10.2307/1926559
  • Sánchez, E. M., J. B. Clempner, and A. S. Poznyak. 2015a. “A Priori-Knowledge/actor-critic Reinforcement Learning Architecture for Computing the Mean-Variance Customer Portfolio: The Case of Bank Marketing Campaigns.” Engineering Applications of Artificial Intelligence 46 (Part A): 82–92. doi: 10.1016/j.engappai.2015.08.011
  • Sánchez, E. M., J. B. Clempner, and A. S. Poznyak. 2015b. “Solving The Mean-Variance Customer Portfolio In Markov Chains Using Iterated Quadratic/Lagrange Programming: A Credit-Card Customer-Credit Limits Approach.” Expert Systems with Applications 42 (12): 5315–5327. doi: 10.1016/j.eswa.2015.02.018
  • Sotomayor, L. R., and A. Cadenillas. 2009. “Explicit Solutions of Consumption-Investment Problems in Financial Markets with Regime-Switching.” Mathematical Finance 19 (2): 251–279. doi: 10.1111/j.1467-9965.2009.00366.x
  • Trejo, K., J. B. Clempner, and A. Poznyak. Forthcoming. “Proximal Constrained Optimization Approach with Time Penalization.” Engineering Optimization 64 (14): To be published.
  • Wu, Huiling. 2013. “Mean-Variance Portfolio Selection with a Stochastic Cash Flow in a Markov-switching Jump-Diffusion Market.” Journal of Optimization Theory and Applications 158: 918–934. doi: 10.1007/s10957-013-0292-x
  • Wu, L.. 2003. “Jumps and Dynamic Asset Allocation.” Review of Quantitative Finance and Accounting 20: 207–243. doi: 10.1023/A:1023699711805
  • Yang, Z., G. Yin, and A. Zhang. 2015. “Mean-Variance Type Controls Involving a Hidden Markov Chain: Models and Numerical Approximation.” IMA Journal of Mathematical Control and Information 32 (4): 867–888.
  • Yin, G., R. H. Liu, and Q. Zhang. 2002. “Recursive Algorithms For Stock Liquidation: A Stochastic Optimization Approach.” SIAM Journal on Optimization 13 (1): 240–263. doi: 10.1137/S1052623401392901
  • Yin, G., and Q. Zhang. 1998. Continuous-Time Markov Chains and Applications: A Singular Perturbations Approach. New York: Springer-Verlag.
  • Yin, G., and X. Y. Zhou. 2004. “Markowitz's Mean-Variance Portfolio Selection with Regime Switching: From Discrete-time Models to Their Continuous-time Limits.” IEEE Transactions on Automatic Control 49 (3): 349–360. doi: 10.1109/TAC.2004.824479
  • Yiu, K. F. C., J. Liu, T. K. Siu, and W. K. Ching. 2010. “Optimal Portfolios with Regime Switching and Value-at-risk Constraint.” Automatica 46: 979–989. doi: 10.1016/j.automatica.2010.02.027
  • Zhai, J., and M. Bai. 2017. “Mean-Variance Model for Portfolio Optimization with Background Risk Based on Uncertainty Theory.” International Journal of General Systems 47 (3): 294–312. doi: 10.1080/03081079.2017.1414210
  • Zhou, X. Y., and G. Yin. 2003. “Markowitz's Mean-Variance Portfolio Selection with Regime Switching: A Continuous-Time Model.” SIAM Journal on Control and Optimization 42: 1466–1482. doi: 10.1137/S0363012902405583

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.