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Portfolio optimization using Laplacian biogeography based optimization

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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.

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Acknowledgements

Funding was provided by Ministry of Human Resources, Govt. of India (Grant No. MHRD 02-23-200-429).

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Authors and Affiliations

  1. Department of Mathematics, School of Basic and Applied Sciences, Galgotias University, Greater Noida, India

    Vanita Garg

  2. Department of Mathematics, Indian Institute of Technology, Roorkee, Roorkee, India

    Kusum Deep

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  1. Vanita Garg
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  2. Kusum Deep
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Correspondence to Vanita Garg.

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Garg, V., Deep, K. Portfolio optimization using Laplacian biogeography based optimization. OPSEARCH 56, 1117–1141 (2019). https://doi.org/10.1007/s12597-019-00400-4

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