An Adaptive Heuristic Approach to Optimize Equity Market Neutral Portfolio


  • Naga Sunil Kumar Gandikota Centre for Research in Data Science, Computer & Information Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia
  • Mohd Hilmi Hasan Centre for Research in Data Science, Computer & Information Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia
  • Jafreezal Jaafar Centre for Research in Data Science, Computer & Information Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia



Adaptive, Neutral, Heuristic, Hall of fame, Crossovers, Optimization


An Equity Market Neutral Portfolio (EMNP) safeguards a safe portfolio concerning exposure to pertinent market benchmarks. Although it is possible to efficiently solve the problem of EMNP optimization through linear programming techniques, combining the risk budget constraint of risky assets with other constraints of EMNP where there is no market exposure, leveraging, or portfolio beta makes it challenging to resolve this problem via conventional approaches directly. This study aims to propose a novel technique to solve the problem of constrained optimization of EMNP via differential evolution strategies involving multiple crossovers (Exponential as well as binomial together with the Hall of Fame). The suggested automated technique enables portfolio managers to select the portfolio with the highest potential return. Monitoring the optimal combination of evolutionary techniques also confirms the results’ consistency. Therefore, impending outcomes were chosen depending on the optimal balance of portfolio returns and risk. This analysis includes Nifty50’s monthly stock prices.


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How to Cite

Gandikota, N. S. K., Hasan, M. H., & Jaafar, J. (2023). An Adaptive Heuristic Approach to Optimize Equity Market Neutral Portfolio. Communications in Mathematics and Applications, 14(3), 1127–1142.



Research Article