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A constrained consensus based optimization algorithm and its application to finance
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DOI：10.1016/j.amc.2021.126726.png)
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摘要
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In this paper, we propose a predictor-corrector type Consensus Based Optimization(CBO) algorithm on a convex feasible set. Our proposed algorithm generalizes the CBO algorithm in [11] to tackle a constrained optimization problem for the global minima of the nonconvex function defined on a convex domain. As a practical application of the proposed algorithm, we study the portfolio optimization problem in finance. In this application, we introduce an objective function to choose the optimal weight on each asset in an assetbundle, which yields the maximal expected returns given a certain level of risks. Simulation results show that our proposed predictor-corrector type model is successful in finding the optimal value. (C) 2021 Elsevier Inc. All rights reserved.
Keyword:
Consensus based optimization
Portfolio selection
Mean-variance model
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3.4
论文数:
2.3W
被引数:
3.3W
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