An adaptive metaheuristic approach for risk-budgeted portfolio optimization

Naga Sunil Kumar Gandikota, Mohd Hilmi Hasan, Jafreezal Jaafar


An investment portfolio implies the assortment of assets invested in the commodity market and equity funds across global markets. The critical issue associated with any portfolio under its optimization entails the achievement of an optimal Sharpe ratio related to risk-return. This issue turns complex when risk budgeting and other investor preferential constraints are weighed in, rendering it difficult for direct solving via conventional approaches. As such, this present study proposes a novel technique that addresses the problem of constrained risk budgeted optimization with multiple crossovers (binomial, exponential & arithmetic) together with the hall of fame via  differential evolution (DE) strategies. The proposed automated solution facilitates portfolio managers to adopt the best possible portfolio that yields the most lucrative returns. In addition, the outcome coherence is verified by monitoring the best blend of evolution strategies. As a result, imminent outcomes were selected based on the best mixture of portfolio returns and Sharpe ratio. The monthly stock prices of Nifty50 were included in this study.


Adaptive; Differential evolution; Hall of fame; Metaheuristic; Nifty50; Portfolio optimization; Risk-budget;



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