The Task of Maximising the Satisfaction from on Inwestor's Investment Portfolio
DOI:
https://doi.org/10.18559/t9a8bw39Keywords:
Optimalization, Rate of return, Investment portfolio, Portfolio analysisAbstract
The problem of selecting an investment portfolio has been widely discussed in the literature, based on both a stochastic analysis as well as a fuzzy set theory framework. The most commonly used criterion is to maximize profi t while minimizing risk. Empirical studies conducted among investors have shown that they do not always act in accordance with this principle. Individual investors assess the gains and uncertainty in the light of individual expectations, largely based on emotion and intuition. In this paper a new investment portfolio selection model will be proposed based on the measure of satisfaction. A formal description of the fuzzy environment is used based on the rate of return. Th is model assumes that an investor maximizes their level of satisfaction with an investment, understood as the similarity between the reliability of the fuzzy returns and the investor's expectations. Th e model is illustrated with mathematical examples to illustrate the optimization idea and compare it to the mean-variance model.
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References
Bachmann, K., Hens T. , 2008, Behavioral Finance for Private Banking, John Wiley and Sons, Chichester.
View in Google Scholar
Bouchon-Meunier, B., Rifqi, M., Bothorel, S., 1996, Towards General Measures of Comparison of Objects, Fuzzy Sets System, vol. 84(2), s. 143-153.
View in Google Scholar
Bygrave, W.D., Hofer, Ch.W., 1991, Th eorizing about Entrepreneurship, Entrepreneurship Th eory and Practice, vol. 16, s. 13-22.
View in Google Scholar
Cross, V.V., Sudkamp, T.A., 2002, Similarity and Compatibility in Fuzzy Set Th eory: Assessment and Applications, Physica-Verlag Heidelberg.
View in Google Scholar
Huang, X., 2006, Fuzzy Chance-constrained Portfolio Selection, Applied Mathematics and Computation, vol. 177(2), s. 500-507.
View in Google Scholar
Huang, X., 2007, Portfolio Selection with Fuzzy Returns, Journal of Intelligent and Fuzzy Systems, vol. 18(4), s. 383-390.
View in Google Scholar
Huang, X., 2008a, Mean-Entropy Models for Fuzzy Portfolio Selection, IEEE Transactions on Fuzzy Systems, vol. 16, s. 1096-1101.
View in Google Scholar
Huang, X., 2008b, Mean-semivariance Models for Fuzzy Portfolio Selection, Journal of Computational and Applied Mathematics, vol. 217(1), s. 1-8.
View in Google Scholar
Kaufmann, A., 1975, Introduction to the Th eory of Fuzzy Subsets, Academic Press.
View in Google Scholar
Kotler, P., 1967, Marketing Management: Analysis, Planning, and Control, Prentice-Hall.
View in Google Scholar
Li, X., Qin, Z., Kar, S.,2010, Mean-variance-skewness Model for Portfolio Selection with Fuzzy Returns, European Journal of Operational Research, 202(1), s. 239-247.
View in Google Scholar
Li X., Qin Z., Yang, L., 2010, A Chance-constrained Portfolio Selection Model with Risk Constraints, Applied Mathematics and Computation, 217(2), s. 949-951.
View in Google Scholar
Liu.,B., 2004, Uncertainty Th eory: an Introduction to Its Axiomatic Foundations, Springer.
View in Google Scholar
Liu, B., Liu, Y.K., 2002, Expected Value of Fuzzy Variable and Fuzzy Expected Value Models, IEEE Transactions on Fuzzy Systems, no. 10, s. 445-450.
View in Google Scholar
Nahmias, S.,1978, Fuzzy Variables, Fuzzy Sets and Systems, vol. 1(2), s. 97-110.
View in Google Scholar
Markowitz, H., 1952, Portfolio Selection, Journal of Finance, vol. 7, s. 77-91.
View in Google Scholar
Peng, J., Mok, H.M.K., Tse. W.M., 2005, Credibility Programming Approach to Fuzzy Portfolio Selection Problems, Proceedings of 2005 International Conference on Machine Learning and Cybernetics, vol. 4.
View in Google Scholar
Tversky, A., 1977, Features of Similarity, Psychological Review, vol. 84, s. 327-352.
View in Google Scholar
Zadeh, L.A., 1965, Fuzzy Sets, Information and Control, vol.8(3), s. 338-353.
View in Google Scholar
