Abstract
A new interactive model for constructing a tactical global assets allocation through integrating fuzzy scenarios clustering- based approaches (FSCA) with mean-variance (MV) is proposed. This serves as an alternative forecasting rebalance quantitative model to the popular global assets allocation, in which the portfolio is first being observed in contrast with major asset and sub-assets classes which possess upward and downward positive co-movement phenomenon while considering the linkage of cross-market between different time-zones. In addition, fuzzy scenarios clustering would be induced into the MV model so as to adjust the weighting of the risk-return structural matrices. It could further enhance the efficient frontier of a portfolio as well as obtaining opportunity of excess return. By means of global major market indices as the empirical evidences, it shows that the new approach can provide a more efficient frontier for a portfolio and there would be less computational cost to solve MV model.
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References
Samuelson, P.A.: Lifetime Portfolio Selection by Dynamic Stochastic Programming. Review of Economic Studies 51(3), 239–246 (1969)
Arrow, K.J.: Essays in the Theory of Risk Bearing. North-Holland, Amsterdam (1970)
Hakansson, N.H.: Optimal Investment and Consumption Strategies under Risk for a Class of Utility Functions. Econometrica 38(5), 587–607 (1970)
Merton, R.C.: Continuous Time Finance. Blackwell, Oxford (1990)
Markowitz, H.M.: Portfolio Selection: Efficient Diversification of Investments. Wiley, New York (1959)
Markowitz, H.M.: Mean Variance Analysis in Portfolio Choice and Capital Markets. Basil Blackwell, Oxford (1988)
Sharpe, W.F.: Portfolio Theory and Capital Markets. McGraw-Hill, New York (1970)
Rudd, A., Rosenberg, B.: Realistic Portfolio Optimization, TIMS Studies in Management Science: Portfolio Theory, pp. 21–46. North Holland Press, Amsterdam (1979)
Zenios, S., Kang, P.: Mean Absolute deviation portfolio optimization for mortgage-backed securities. Annals of Operations Research 45, 433–450 (1993)
Sharpe, W.: Integrated Asset Allocation, Financial Analysis (1987)
Konno, H., Kobayashi, K.: An Integrated Stock-Bond Portfolio Optimization Model. Journal of Economic Dynamics and Control, 1427–1444 (1997)
Zhang, L.H.: Global Asset Allocation with Multirisk Considerations. The Journal of Investing 7(3), 7–14 (1998)
Makhoul, J.S., Gish, R.H.: Vector Quantization in Speech Coding. Proc. IEEE 73(11), 1551–1588 (1985)
Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1987)
Schirripa, Tecotzky: Schirripa, Felix, Tecotzky, Nan, An Optimal Frontier. The Journal of Portfolio Management 26(4), 29–40 (2000)
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Wang, HW. (2006). Fuzzy Scenarios Clustering-Based Approach with MV Model in Optimizing Tactical Allocation. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_116
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DOI: https://doi.org/10.1007/11903697_116
Publisher Name: Springer, Berlin, Heidelberg
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