A learning-based strategy for portfolio selection

Shun Chen and Lei Ge

International Review of Economics & Finance, 2021, vol. 71, issue C, 936-942

Abstract: Neural networks have shown exceptional performance in targeting different research areas. In this paper, we investigate a learning-based strategy for optimal investment by using neural network. First, an optimization problem for portfolio selection is proposed. Then, a neural network model is used to optimize this problem. The main contribution is that based on this proposed optimization problem and neural network model, we can easily implement the structure and obtain the final results by using deep learning software. Finally, we numerically compare the results obtained from our strategy with those of classic solutions. The comparison demonstrates the effectiveness of the learning-based strategy.

Keywords: Neural network; Portfolio selection; Strategy; Optimization (search for similar items in EconPapers)
JEL-codes: C45 C53 G11 G17 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:71:y:2021:i:c:p:936-942

DOI: 10.1016/j.iref.2020.07.010

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