利用神经网络优化具有杠杆约束的投资组合：高通胀投资案例研究

IF 1.5 4区经济学 Q3 BUSINESS, FINANCE

Quantitative Finance Pub Date : 2024-06-11 DOI:10.1080/14697688.2024.2357733

Chendi Ni, Yuying Li, Peter Forsyth

引用次数: 0

摘要

在当前全球高通胀形势的激励下，我们的目标是发现一种动态的多期配置策略，以最优化地超越被动基准，同时遵守有界杠杆。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Neural network approach to portfolio optimization with leverage constraints: a case study on high inflation investment

Motivated by the current global high inflation scenario, we aim to discover a dynamic multi-period allocation strategy to optimally outperform a passive benchmark while adhering to a bounded levera...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Quantitative Finance 社会科学-数学跨学科应用

CiteScore

3.20

自引率

7.70%

发文量

102

审稿时长

4-8 weeks

期刊介绍： The frontiers of finance are shifting rapidly, driven in part by the increasing use of quantitative methods in the field. Quantitative Finance welcomes original research articles that reflect the dynamism of this area. The journal provides an interdisciplinary forum for presenting both theoretical and empirical approaches and offers rapid publication of original new work with high standards of quality. The readership is broad, embracing researchers and practitioners across a range of specialisms and within a variety of organizations. All articles should aim to be of interest to this broad readership.