A GA-simheuristic for the stochastic and multi-period portfolio optimisation problem with liabilities

References

• Alvarez Fernandez, S., Ferone, D., Juan, A. A., & Tarchi, D. (2021). A simheuristic algorithm for video streaming flows optimisation with QoS threshold modelled as a stochastic single-allocation p-hub median problem. Journal of Simulation , 1–14. pages. https://doi.org/10.1080/17477778.2020.1863754
   Web of Science ®Google Scholar
• Arrow, K. J. (1974). The limits of organization. WW Norton & Company.
   Google Scholar
• Berkelaar, A., & Kouwenberg, R. (2010). A liability-relative drawdown approach to pension asset liability management. Journal of Asset Management, 11(2–3), 194–217. https://doi.org/10.1057/jam.2010.13
   Google Scholar
• Bertsekas, D. P. (2014). Constrained optimization and Lagrange multiplier methods. Academic press.
   Google Scholar
• Boender, G., Dert, C., Heemskerk, F., & Hoek, H. (2008). Chapter 18 - A scenario approach of ALM. Handbook of Asset and Liability Management, North-Holland. (pp. 829–860).
   Google Scholar
• Bogentoft, E., Romeijn, H. E., & Uryasev, S. (2001). Asset/liability management for pension funds using cvar constraints. Journal of Risk Finance, 3(1), 57–71. https://doi.org/10.1108/eb043483
   Google Scholar
• Brailsford, S. C., Eldabi, T., Kunc, M., Mustafee, N., & Osorio, A. F. (2019). Hybrid simulation modelling in operational research: A state-of-the-art review. European Journal of Operational Research, 278(3), 721–737. https://doi.org/10.1016/j.ejor.2018.10.025
   Web of Science ®Google Scholar
• Carsey, T. M., & Harden, J. J. (2013). Monte Carlo simulation and resampling methods for social science. Sage Publications.
   Google Scholar
• Chica, M., Juan, A. A., Bayliss, C., Cordón, O., & Kelton, W. D. (2020). Why simheuristics? benefits, limitations, and best practices when combining metaheuristics with simulation. In SORT-Statistics and Operations Research Transactions (SSRN Electronic Journal) (pp. 311–334). pages.
   Google Scholar
• Consiglio, A., Cocco, F., & Zenios, S. A. (2008). Asset and liability modelling for participating policies with guarantees. European Journal of Operational Research, 186(1), 380–404. https://doi.org/10.1016/j.ejor.2007.01.037
   Web of Science ®Google Scholar
• Consiglio, A., Saunders, D., & Zenios, S. A. (2006). Asset and liability management for insurance products with minimum guarantees: The uk case. Journal of Banking and Finance, 30(2), 645–667. https://doi.org/10.1016/j.jbankfin.2005.04.009
   Web of Science ®Google Scholar
• Corsaro, S., De Angelis, P., Marino, Z., Perla, F., & Zanetti, P. (2010). On parallel asset-liability management in life insurance: A forward risk-neutral approach. Parallel Computing, 36(7), 390–402. Parallel and Distributed Computing in Finance. https://doi.org/10.1016/j.parco.2009.10.002
   Web of Science ®Google Scholar
• Dash, G. H., Jr., & Kajiji, N. (2005). A nonlinear goal programming model for efficient asset-liability management of property-liability insurers. INFOR, 43(2), 135–156. doi:10.1080/03155986.2005.11732722.
   Web of Science ®Google Scholar
• Doering, J., Kizys, R., Juan, A. A., Fito, A., & Polat, O. (2019). Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends. Operations Research Perspectives, 6 , 100121. https://doi.org/10.1016/j.orp.2019.100121
   Web of Science ®Google Scholar
• Dutta, G., Rao, H. V., Basu, S., & Tiwari, M. K. (2019). Asset liability management model with decision support system for life insurance companies: Computational results. Computers & Industrial Engineering, 128, 985–998. https://doi.org/10.1016/j.cie.2018.06.033
   Web of Science ®Google Scholar
• Escudero, L. F., Garín, A., Merino, M., & Pérez, G. (2009). On multistage stochastic integer programming for incorporating logical constraints in asset and liability management under uncertainty. Computational Management Science, 6(3), 307–327. https://doi.org/10.1007/s10287-006-0035-7
   Google Scholar
• Fernández, J. L., Ferreiro-Ferreiro, A. M., Garca-Rodrguez, J. A., & Vázquez, C. (2018). GPU parallel implementation for asset-liability management in insurance companies. Journal of Computational Science, 24, 232–254. https://doi.org/10.1016/j.jocs.2017.05.010
   Web of Science ®Google Scholar
• Ferone, D., Gruler, A., Festa, P., & Juan, A. A. (2019). Enhancing and extending the classical GRASP framework with biased randomisation and simulation. Journal of the Operational Research Society, 70(8), 1362–1375. https://doi.org/10.1080/01605682.2018.1494527
   Web of Science ®Google Scholar
• Ferstl, R., & Weissensteiner, A. (2011). Asset-liability management under time-varying investment opportunities. Journal of Banking and Finance, 35(1), 182–192. https://doi.org/10.1016/j.jbankfin.2010.07.028
   Web of Science ®Google Scholar
• Fleten, S., Høyland, K., & Wallace, S. W. (2002). The performance of stochastic dynamic and fixed mix portfolio models. European Journal of Operational Research, 140(1), 37–49. https://doi.org/10.1016/S0377-2217(01)00195-3
   Web of Science ®Google Scholar
• Gondzio, J., & Grothey, A. (2006). Solving nonlinear financial planning problems with 10 9 decision variables on massively parallel architectures. WIT Transactions on Modelling and Simulation, 43(pages), 95–105. doi:10.2495/CF060101.
   Google Scholar
• Gondzio, J., & Kouwenberg, R. (2001). High-performance computing for asset-liability management. Operations Research, 49(6), 879–891. https://doi.org/10.1287/opre.49.6.879.10015
   Web of Science ®Google Scholar
• Gonzalez-Martin, S., Juan, A. A., Riera, D., Elizondo, M. G., & Ramos, J. J. (2018). A simheuristic algorithm for solving the arc routing problem with stochastic demands. Journal of Simulation, 12(1), 53–66. https://doi.org/10.1057/jos.2016.11
   Web of Science ®Google Scholar
• Grasas, A., Juan, A. A., & Lourenço, H. R. (2016). SimILS: A simulation-based extension of the iterated local search metaheuristic for stochastic combinatorial optimization. Journal of Simulation, 10(1), 69–77. https://doi.org/10.1057/jos.2014.25
   Web of Science ®Google Scholar
• Gruler, A., Panadero, J., de Armas, J., Moreno, J. A., & Juan, A. A. (2018). Combining variable neighborhood search with simulation for the inventory routing problem with stochastic demands and stock-outs. Computers & Industrial Engineering, 123, 278–288. https://doi.org/10.1016/j.cie.2018.06.036
   Web of Science ®Google Scholar
• Gruler, A., Quintero-Araujo, C. L., Calvet, L., & Juan, A. A. (2017). Waste collection under uncertainty: A simheuristic based on variable neighbourhood search. European Journal of Industrial Engineering, 11(2), 228–255. https://doi.org/10.1504/EJIE.2017.083257
   Web of Science ®Google Scholar
• Guimarans, D., Dominguez, O., Panadero, J., & Juan, A. A. (2018). A simheuristic approach for the two-dimensional vehicle routing problem with stochastic travel times. Simulation Modelling Practice and Theory, 89, 1–14. https://doi.org/10.1016/j.simpat.2018.09.004
   Web of Science ®Google Scholar
• Gülpinar, N., & Pachamanova, D. (2013). A robust optimization approach to asset-liability management under time-varying investment opportunities. Journal of Banking and Finance, 37(6), 2031–2041. https://doi.org/10.1016/j.jbankfin.2013.01.025
   Web of Science ®Google Scholar
• Gülpınar, N., Pachamanova, D., & Çanakoğlu, E. (2016). A robust asset–liability management framework for investment products with guarantees. OR Spectrum, 38(4), 1007–1041. https://doi.org/10.1007/s00291-016-0437-z
   Web of Science ®Google Scholar
• Harper, A., Mustafee, N., & Yearworth, M. (2021). Facets of trust in simulation studies. European Journal of Operational Research, 289(1), 197–213. https://doi.org/10.1016/j.ejor.2020.06.043
   Web of Science ®Google Scholar
• Hatami, S., Calvet, L., Fernández-Viagas, V., Framinan, J. M., & Juan, A. A. (2018). A simheuristic algorithm to set up starting times in the stochastic parallel flowshop problem. Simulation Modelling Practice and Theory, 86, 55–71. https://doi.org/10.1016/j.simpat.2018.04.005
   Web of Science ®Google Scholar
• Hibiki, N. (2006). Multi-period stochastic optimization models for dynamic asset allocation. Journal of Banking and Finance, 30(2), 365–390. https://doi.org/10.1016/j.jbankfin.2005.04.027
   Web of Science ®Google Scholar
• Huang, H., & Willemain, T. (2006). Input modelling for financial simulations using the bootstrap. Journal of Simulation, 1(1), 39–52. https://doi.org/10.1057/palgrave.jos.4250007
   Web of Science ®Google Scholar
• Juan, A. A., Faulin, J., Grasman, S. E., Rabe, M., & Figueira, G. (2015). A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems. Operations Research Perspectives, 2, 62–72. https://doi.org/10.1016/j.orp.2015.03.001
   Web of Science ®Google Scholar
• Khabibullin, R., Ponomarenko, A., & Seleznev, S. (2020). Forecasting the implications of foreign exchange reserve a ccumulation with a microsimulation model. Journal of Simulation, 1–14. pages. https://doi.org/10.1080/17477778.2020.1813641
   Web of Science ®Google Scholar
• Kizys, R., Juan, A. A., Sawik, B., & Calvet, L. (2019). A biased-randomized iterated local search algorithm for rich portfolio optimization. Applied Sciences, 9(17), 3509. https://doi.org/10.3390/app9173509
   Google Scholar
• Klaassen, P. (1997). Discretized reality and spurious profits in stochastic programming models for asset/liability management. European Journal of Operational Research, 101(2), 374–392. https://doi.org/10.1016/S0377-2217(96)00404-3
   Web of Science ®Google Scholar
• Kopa, M., & Rusý, T. (2020). A decision-dependent randomness stochastic program for asset–liability management model with a pricing decision. In Annals of Operations Research, 299, 241–271. https://doi.org/10.1007/s10479-020-03583-y.
   Google Scholar
• Kouwenberg, R., & Zenios, S. A. (2008). Stochastic Programming Models for Asset Liability Management, volume 1 of. In Handbook of Asset and Liability Management - Set, North-Holland. (pp. 253–303). pages.
   Google Scholar
• Kramer, O. (2017). Genetic algorithms. Genetic algorithm essentials, 679, Studies in Computational Intelligence. Springer International Publishing. ISBN: 978-3-319-52155-8. https://doi.org/10.1007/978-3-319-52156-5.
   Google Scholar
• Li, D., Shen, Y., & Zeng, Y. (2018). Dynamic derivative-based investment strategy for mean–variance asset–liability management with stochastic volatility. Insurance, Mathematics & Economics, 78, 72–86. https://doi.org/10.1016/j.insmatheco.2017.11.006.
   Web of Science ®Google Scholar
• Li, X., Wu, X., & Yao, H. (2019). Multi-period asset-liability management with cash flows and probability constraints: A mean-field formulation approach. Journal of the Operational Research Society, 1–18. doi:10.1080/01605682.2019.1610207.
   Web of Science ®Google Scholar
• Macaulay, F. R. (1938). Some Theoretical Problems Suggested by the Movements of Interest Rates, Bond Yields and Stock Prices in the United States since 1856. National Bureau of Economic Research, Inc.
   Google Scholar
• Mankiw, N. G., Kneebone, R. D., McKenzie, K. J., & Rowe, N. (2020). Principles of macroeconomics. (Nelson Education). ISBN: 9780176872830 0176872833.
   Google Scholar
• Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91 https://doi.org/10.1111/j.1540-6261.1952.tb01525.x.
   Web of Science ®Google Scholar
• Movahed, S. B., & Fanian, S. (2019). Optimum portfolio construction considering value at risk using genetic algorithms and monte carlo simulation (Segal Graduate School of Business).
   Google Scholar
• Mulvey, J. M., Rosenbaum, D. P., & Shetty, B. (1997). Strategic financial risk management and operations research. European Journal of Operational Research, 97(1), 1–16. https://doi.org/10.1016/S0377-2217(96)00222-6
   Web of Science ®Google Scholar
• Onggo, B. S., Panadero, J., Corlu, C. G., & Juan, A. A. (2019). Agri-food supply chains with stochastic demands: A multi-period inventory routing problem with perishable products. Simulation Modelling Practice and Theory, 97, 101970. https://doi.org/10.1016/j.simpat.2019.101970
   Web of Science ®Google Scholar
• Orlova, E. V. (2019). Model for operational optimal control of financial recourses distribution in a company. Computer Research and Modeling. ISBN: 11 2 343–358, https://doi.org/10.20537/2076-7633-2019-11-2-343-358 .
   Google Scholar
• Pagès-Bernaus, A., Ramalhinho, H., Juan, A. A., & Calvet, L. (2019). Designing e-commerce supply chains: A stochastic facility–location approach. International Transactions in Operational Research, 26(2), 507–528. https://doi.org/10.1111/itor.12433
   Web of Science ®Google Scholar
• Panadero, J., Doering, J., Kizys, R., Juan, A. A., & Fito, A. (2020). A variable neighborhood search simheuristic for project portfolio selection under uncertainty. Journal of Heuristics, 26(3), 353–375. https://doi.org/10.1007/s10732-018-9367-z
   Web of Science ®Google Scholar
• Papi, M., & Sbaraglia, S. (2006). Optimal asset-liability management with constraints: A dynamic programming approach. Applied Mathematics and Computation, 173(1), 306–349. https://doi.org/10.1016/j.amc.2005.04.078
   Web of Science ®Google Scholar
• Pflug, G. C., & Pichler, A. (2014). Multistage stochastic optimization: Vol. 1104. [volume]. Springer.
   Google Scholar
• Pratt, J. W. (1978). Risk aversion in the small and in the large. Uncertainty in economics, pages 59–79. Elsevier .
   Google Scholar
• Quintero-Araujo, C. L., Guimarans, D., & Juan, A. A. (2021). A simheuristic algorithm for the capacitated location routing problem with stochastic demands. Journal of Simulation, 15(3), 217–234. https://doi.org/10.1080/17477778.2019.1680262
   Web of Science ®Google Scholar
• Rosmarin, J. (2008). An evolutionary approach to multistage portfolio optimization (PhD thesis, Imperial College London).
   Google Scholar
• Solares, E., Coello Coello, C. A., Fernandez, E., & Navarro, J. (2019). Handling uncertainty through confidence intervals in portfolio optimization. Swarm and Evolutionary Computation, 44, 774–787. https://doi.org/10.1016/j.swevo.2018.08.010
   Web of Science ®Google Scholar
• Soler-Dominguez, A., Juan, A. A., & Kizys, R. (2017). A survey on financial applications of metaheuristics. ACM Computing Surveys (CSUR), 50(1), 1–23. https://doi.org/10.1145/3054133
   Web of Science ®Google Scholar
• Tobin, J. (1958). Liquidity preference as behavior towards risk. The Review of Economic Studies, 25(2), 65–86. https://doi.org/10.2307/2296205
   Google Scholar
• Tolk, A., Harper, A., & Mustafee, N. (2021). Hybrid models as transdisciplinary research enablers. European Journal of Operational Research, 291(3), 1075–1090. https://doi.org/10.1016/j.ejor.2020.10.010
   Web of Science ®Google Scholar
• Wei, J., & Wang, T. (2017). Time-consistent mean-variance asset-liability management with random coefficients. Insurance, Mathematics & Economics, 77(C), 84–96. doi:10.1016/j.insmatheco.2017.08.011.
   Google Scholar
• Zhang, M., & Chen, P. (2016). Mean-variance asset-liability management under constant elasticity of variance process. Insurance, Mathematics & Economics, 70(C), 11–18. doi:10.1016/j.insmatheco.2016.05.019.
   Google Scholar
• Zhang, X., & Zhang, K. (2009). Using genetic algorithm to solve a new multi-period stochastic optimization model. Journal of Computational and Applied Mathematics, 231(1), 114–123. https://doi.org/10.1016/j.cam.2009.02.055
   Web of Science ®Google Scholar
• Zhou, Z., Zeng, X., Xiao, H., Ren, T., & Liu, W. (2019). Multiperiod portfolio optimization for asset-liability management with quadratic transaction costs. Journal of Industrial and Management Optimization, 15(3), 1493–1515. doi:10.3934/jimo.2018106.
   Web of Science ®Google Scholar