Credibilistic multi-period portfolio optimization based on scenario tree

Negin Mohebbi and Amir Abbas Najafi

Physica A: Statistical Mechanics and its Applications, 2018, vol. 492, issue C, 1302-1316

Abstract: In this paper, we consider a multi-period fuzzy portfolio optimization model with considering transaction costs and the possibility of risk-free investment. We formulate a bi-objective mean-VaR portfolio selection model based on the integration of fuzzy credibility theory and scenario tree in order to dealing with the markets uncertainty. The scenario tree is also a proper method for modeling multi-period portfolio problems since the length and continuity of their horizon. We take the return and risk as well cardinality, threshold, class, and liquidity constraints into consideration for further compliance of the model with reality. Then, an interactive dynamic programming method, which is based on a two-phase fuzzy interactive approach, is employed to solve the proposed model. In order to verify the proposed model, we present an empirical application in NYSE under different circumstances. The results show that the consideration of data uncertainty and other real-world assumptions lead to more practical and efficient solutions.

Keywords: Multi-period portfolio; Uncertainty; Fuzzy credibility theory; Scenario tree; Interactive dynamic programming (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:492:y:2018:i:c:p:1302-1316

DOI: 10.1016/j.physa.2017.11.058

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