Abstract
This paper discusses the hybrid portfolio selection problem in the situation where only some security returns can be well reflected by their past data and are suitable to be described by random variables, but the other security returns can hardly be predicted through the historical data and are suitable to be described by fuzzy variables. By using chance theory, this paper extends the risk curve to hybrid portfolio selection and develops a hybrid mean-risk model. In addition, the way for computing the expected value and the risk curve of the hybrid portfolio return is provided and a genetic algorithm is presented for finding the optimal solution. As an illustration, an example is also provided.
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Huang, X. (2011). Mean-Risk Model for Hybrid Portfolio Selection with Fuzziness and Randomness. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Lecture Notes in Computer Science, vol 6935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24082-9_27
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DOI: https://doi.org/10.1007/978-3-642-24082-9_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24081-2
Online ISBN: 978-3-642-24082-9
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