Abstract
The purpose of stock portfolio selection is how to allocate the capital to a large number of stocks in order to bring a most profitable return for investors. In most of past literature, expert considered portfolio problem only based on past data. It is very important for experts to use their experience and knowledge to predict the performance of each stock. In this paper, 2-tuple linguistic variables are used to express the opinions of experts to predict the performance of each stock with respect to each criterion. According to experts’ linguistic evaluations, we use maximizing deviation method to derive the weight of each criterion. And then, the linguistic ELECTRE method is used to derive the credibility matrix and calculate the net credibility degree of each stock. Based on the outranking index and selection threshold, we can easily obtain portfolio set and decide the investment ratio of each stock. An example is implemented to demonstrate the practicability of proposed method.
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Chen, CT., Hung, WZ. (2009). Applying ELECTRE and Maximizing Deviation Method for Stock Portfolio Selection under Fuzzy Environment. In: Chien, BC., Hong, TP. (eds) Opportunities and Challenges for Next-Generation Applied Intelligence. Studies in Computational Intelligence, vol 214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92814-0_14
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DOI: https://doi.org/10.1007/978-3-540-92814-0_14
Publisher Name: Springer, Berlin, Heidelberg
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