Portfolio optimization using Laplacian biogeography based optimization

Vanita Garg () and Kusum Deep ()
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Vanita Garg: Galgotias University
Kusum Deep: Indian Institute of Technology, Roorkee

OPSEARCH, 2019, vol. 56, issue 4, No 3, 1117-1141

Abstract: Abstract Portfolio optimization is defined as the most appropriate allocation of assets so as to maximize returns subject to minimum risk. This constrained nonlinear optimization problem is highly complex due to the presence of a number of local optimas. The objective of this paper is to illustrate the effectiveness of a well-tested and effective Laplacian biogeography based optimization and another variant called blended biogeography based optimization. As an illustration the model and solution methodology is implemented on data taken from Indian National Stock Exchange, Mumbai from 1st April, 2015 to 31st March, 2016. From the analysis of results, it is concluded that as compared to blended BBO, the recently proposed LX-BBO algorithm is an effective tool to solve this complex problem of portfolio optimization with better accuracy and reliability.

Keywords: Portfolio optimization; Mean variance model; LX-BBO (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12597-019-00400-4

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