Intraday trading strategy based on time series and machine learning for Chinese stock market

Qunwei Wang (), Y. Zhou and Jim Huangnan Shen

Papers from arXiv.org

Abstract: This article comes up with an intraday trading strategy under T+1 using Markowitz optimization and Multilayer Perceptron (MLP) with published stock data obtained from the Shenzhen Stock Exchange and Shanghai Stock Exchange. The empirical results reveal the profitability of Markowitz portfolio optimization and validate the intraday stock price prediction using MLP. The findings further combine the Markowitz optimization, an MLP with the trading strategy, to clarify this strategy's feasibility.

Date: 2021-03
New Economics Papers: this item is included in nep-big, nep-cmp, nep-cwa and nep-mst
References: Add references at CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2103.13507 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2103.13507

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().