A novel PSO for multi-stage portfolio planning

2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009

Volumn 4, Issue , 2009, Pages 71-77

  Wu, Zhangjun ^a,b   Ni, Zhiwei ^a,b   Zhang, Chang ^a,b   Gu, Lichuan ^a,b  

^a HEFEI UNIVERSITY OF TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Portfolio planning; QCLPSO; Stochastic financial optimization

Indexed keywords

DECISION MAKING PROCESS; EFFICIENT FRONTIER; FINANCIAL MARKET; INVESTMENT STRATEGY; MULTI-PERIOD; MULTI-STAGE; OBJECTIVE FUNCTIONS; PARTICLE SWARM OPTIMIZERS; PORTFOLIO PLANNING; REBALANCING; RISK MINIMIZATION; SAVINGS STRATEGY; VARIANCE FUNCTION;

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL EFFICIENCY; DECISION MAKING; INVESTMENTS; STOCHASTIC SYSTEMS; STRATEGIC PLANNING;

OPTIMIZATION;

EID: 77949298988     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AICI.2009.426     Document Type: Conference Paper

References (24)

1. H. Konno, "Piecewise linear risk function and portfolio optimization", J. Oper. Re.s. Soc. Japan 33, no. 2, 1990.
2. A. Perold, "Large-scale portfolio optimization, Manag". Sci. 30, 1984, pp.1143.
3. W.F. Sharpe, "Capital asset prices: A theory of market equilibrium under condition of risk", J.Finance 19, 1964, pp.425-442.
4. H. Markowitz, "Portfolio Selection: Efficient Diversification of Investments", Wiley, New York, 1959.
5. J.M. Mulvey, "Nonlinear network models in finance", Adv. Math. Progr. Fin. Planning 1, 1987, pp.253.
6. J.M. Mulvey and H. Vladimirou, "Stochastic network optimization models for investment planning", Ann. Oper. Res. 20, 1989, pp.187-217.
7. J.M. Mulvey and H. Vladimirou, "Applying the progressive hedging algorithm to stochastic generalized networks", Ann. Oper. Res. 31, 1991, pp.399-424.
8. Berger, A.J., Glover, F., Mulvey, J.M.: "Solving Global Optimization Problems in Long-Term Financial Planning". Statistics and Operations Research Technical Report. Princeton University, 1995.
9. Chan, M.-C., Wong, C.-C., Cheung, B.K.-S.: "Genetic Algorithms in Multi-Stage Asset Allocation System". Proc. 2002 IEEE International Conference on Systems, Man and Cybernetics, Vol. 3. Piscataway, NJ, 2002, pp.316-321
10. J. Kennedy and R.C. Eberhart, "Particle swarm optimization," in Proc.IEEE Int. Conf. Neural Networks, vol. 4, 1995, pp. 1942-1948.
11. Ming JIANG, Yupin LUO, Shiyuan YANG, "Stagnation Analysis in Particle Swarm Optimization", in Proc.IEEE SIS 2007.
12. C.Zhang, Z.W Ni, Z.J Wu, L.C Gu, "A Novel Swarm Model With Quasi-Oppositional Particle" ,in Proc. IFITA 2009
13. George B. Dantzig, Gerd Infanger, "Multi-stage stochastic linear programs for portfolio optimization", Annals of Operations Research, 45, 1993, pp.59-76.
14. Mulvey, J.M., Rosenbaum, D.P., Shetty, B., "Parameter Estimation in Stochastic Scenario Generation System". European Journal of Operations Research, Vol. 118, No.3. Elsevier Science, Amsterdam, 1999, pp.563-577
15. R.C. Eberhart and Y. Shi. "Particle swarm optimization: developments, applications and resources", Proc. 2001 Congress on Evolutionary Computation, Seoul, South Korea, 2001, pp.81-86.
16. R. Eberhart and J. Kennedy, "A New Optimizer using Particle Swarm Theory". Proceedings of the Sixth International Symposium on Micro Machine and Human Science (Nagoya, Japan): IEEE Service Center, Piscataway, NJ, 1995, pp 39-43.
17. P. N. Suganthan, "Particle swarm optimizer with neighborhood operator," in Proc. Congr. Evol. Comput., Washington, DC, 1999, pp. 1958-1962.
18. T. Peram, K. Veeramachaneni, and C. K. Mohan, "Fitness-distance- ratio-based particle swarm optimization," in Proc. Swarm Intelligence Symp.,2003, pp. 174-181.
19. Y. Shi and R. C. Eberhart, "A modified particle swarm optimizer," in Proc. IEEE Congr. Evol. Comput., 1998, pp. 69-73.
20. Clerc, M., "The swarm and the queen: towards a deterministic and adaptive particle swarm optimization". Proceedings, 1999 ICEC, Washington, DC, pp 1951-1957.
21. Liang, J.J., Qin, A.K., Suganthan, P.N., Baskar, S., "Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions", Evolutionary Computation, IEEE Transactions on Volume 10, Issue 3, June 2006 Page(s):281 - 295
22. H. R. Tizhoosh, "Opposition-based learning: A new scheme for machine intelligence," in Proc. Int. Conf. Comput. Intell. Modeling Control and Autom., Vienna, Austria, 2005, vol. I, pp. 695-701.
23. Z.J Wu, Z.W Ni, C.Zhang, L.C Gu, "Opposition Based Comprehensive Learning Particle Swarm Optimization" ,in Proc. ISKE 2008
24. H. R. Tizhoosh, "Quasi-Oppositional Differential Evolution", in Proc. CEC2007