A risk tolerance model for portfolio adjusting problem with transaction costs based on possibilistic moments

Insurance: Mathematics and Economics

Volumn 46, Issue 3, 2010, Pages 493-499

  Zhang, Wei Guo ^a   Zhang, Xi Li ^a   Xu, Wei Jun ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Portfolio adjusting; Possibilistic moment; SMO type decomposition method; Transaction costs

Indexed keywords

EID: 77952671316     PISSN: 01676687     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.insmatheco.2010.01.007     Document Type: Article

References (30)

1. Arnott R.D., Wanger W.H. The measurement and control of trading costs. Journal of Financial Analysts 1990, 4(6):73-80.
2. Best M.J., Grauer R.R. The efficient set mathematics when mean-variance problems are subject to general linear constraints. Journal of Economics and Business 1990, 42:105-120.
3. Best M.J., Jaroslava H. The efficient frontier for bounded assets. Mathematical Methods of Operations Research 2000, 52(2):195-212.
4. Carlsson C., Fullér R. On possibilistic mean value and variance of fuzzy numbers. Fuzzy Sets and Systems 2001, 122(2):315-326.
5. Carlsson C., Fullér R., Majlender P. A possibilistic approach to selecting portfolios with highest utility score. Fuzzy Sets and Systems 2002, 131(1):13-21.
6. Chen P.H., Fan R.G., Lin C.J. A study on SMO-type decomposition methods for support vector machines. IEEE Transactions on Neural Networks 2006, 17(4):893-908.
7. Fan R.G., Chen P.H., Lin C.J. Working set selection using second order information for training support vector machines. Journal of Machine Learning Research 2005, 6:1889-1918.
8. Giove S., Funari S., Nardelli C. An interval portfolio selection problems based on regret function. European Journal of Operational Research 2006, 170(1):253-264.
9. Inuiguchi M., Tanino T. Portfolio selection under independent possibilistic information. Fuzzy Sets and Systems 2000, 115(1):83-92.
10. Keerthi S.S., Shevade S.K., Bhattacharyya C., Murthy K.R.K. Improvements to Platt's SMO algorithm for SVM classier design. Neural Computation 2001, 13:637-649.
11. Konno H., Wijayanayake A. Portfolio optimization under D.C. transaction costs and minimal transaction unit constraints. Journal of Global Optimization 2002, 22:137-154.
12. Lai K.K., et al. A class of linear interval programming problems and its application to portfolio selection. IEEE Transactions on Fuzzy Systems 2002, 10(6):698-704.
13. León T., Liem V., Vercher E. Viability of infeasible portfolio selection problems: A fuzzy approach. European Journal of Operational Research 2002, 139(1):178-189.
14. Liu L.P. A new foundation for the mean-variance analysis. European Journal of Operational Research 2004, 158(1):229-242.
15. Liu L., Shenoy C., Shenoy P.P. Knowledge representation and integration for portfolio evaluation using linear belief functions. IEEE Transactions on Systems, Man, and Cybernetics, Part A 2006, 36(4):774-785.
16. Li J., Xu J.P. A novel portfolio selection model in a hybrid uncertain environment. Omega 2007, 35:75-88.
17. Markowitz H. Portfolio Selection: Efficient Diversification of Investments 1959, Wiley, New York.
18. Markowitz H. Analysis in Portfolio Choice and Capital Markets 1987, Oxford, Basil Blackwell.
19. Platt J.C. Fast training of support vector machines using sequential minimal optimization. Advances in Kernel Methods: Support Vector Machines 1998, MIT Press, Cambridge, MA. B. Schlkopf, C. Burgers, A. Smola (Eds.).
20. Saeidifar A., Pasha E. The possibilistic moments of fuzzy numbers and their applications. Journal of Computational and Applied Mathematics 2009, 223:1028-1042.
21. Samuelson P.A. The fundamental approximation theorem of portfolio analysis in terms of means, variances and higher moments. Reviews Economocs Studies 1970, 37(4):537-542.
22. Watada J. Fuzzy portfolio selection and its applications to decision making. Tatra Mountains Mathematical Publications 1997, 13(2):219-248.
23. Yoshimoto A. The mean variance approach to portfolio optimization subject to transaction costs. Journal of the Operational Research Society of Japan 1996, 39:99-117.
24. Zhang W.G., Liu W.A., Wang Y.L. On admissible efficient portfolio selection: Models and Algorithms. Applied Mathematics and Computation 2006, 176(1):208-218.
25. Zhang W.G., Nie Z.K. On admissible efficient portfolio selection problem. Applied Mathematics and Computation 2004, 159(2):357-371.
26. Zhang W.G., Wang Y.L. An analytic derivation of admissible efficient frontier with borrowing. European Journal of Operational Research 2008, 184:229-243.
27. Zhang W.G., Wang Y.L., Chen Z.P., Nie Z.K. Possibilistic mean-variance models and efficient frontiers for portfolio selection problem. Information Sciences 2007, 177(13):2787-2801.
28. Zhang W.G., Xiao W.L. On weighted lower and upper possibilistic means and variances of fuzzy numbers and its application in decision. Knowledge and Information Systems 2009, 18:311-330.
29. Zhang W.G., Xiao W.L., Wang Y.L. A fuzzy portfolio selection method based on possibilistic mean and variance. Soft Computing 2009, 13:627-633.
30. Zhang W.G., Zhang X.L., Xiao W.L. Portfolio selection under possibilistic mean-variance utility and a SMO algorithm. European Journal of Operational Research 2009, 197(2):693-700.