Deep Stock Representation Learning: From Candlestick Charts to Investment Decisions

Guosheng Hu, Yuxin Hu, Kai Yang, Zehao Yu, Flood Sung, Zhihong Zhang, Fei Xie, Jianguo Liu, Neil Robertson, Timothy Hospedales, Qiangwei Miemie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We propose a novel investment decision strategy (IDS) based on deep learning. The performance of many IDSs is affected by stock similarity. Most existing stock similarity measurements have the problems: (a) The linear nature of many measurements cannot capture nonlinear stock dynamics; (b) The estimation of many similarity metrics (e.g. covariance) needs very long period historic data (e.g. 3K days) which cannot represent current market effectively; (c) They cannot capture translation-invariance. To solve these problems, we apply convolutional AutoEncoder to learn a stock representation, based on which we propose a novel portfolio construction strategy by: (i) using the deeply learned representation and modularity optimisation to cluster stocks and identify diverse sectors, (ii) picking stocks within each cluster according to their Sharpe ratio (Sharpe 1994). Overall this strategy provides low-risk high-return portfolios. We use the Financial Times Stock Exchange 100 Index (FTSE 100) data for evaluation. Results show our portfolio outperforms FTSE 100 index and many well known funds in terms of total return in 2000 trading days.
Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech and Signal Processing
Place of PublicationCalgary, AB, Canada
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2706-2710
Number of pages5
ISBN (Electronic)978-1-5386-4658-8
ISBN (Print)978-1-5386-4659-5
DOIs
Publication statusPublished - 13 Sept 2018
Event2018 IEEE International Conference on Acoustics, Speech and Signal Processing - Calgary, Canada
Duration: 15 Apr 201820 Apr 2018
https://2018.ieeeicassp.org/
https://2018.ieeeicassp.org/default.asp

Publication series

Name
PublisherIEEE
ISSN (Electronic)2379-190X

Conference

Conference2018 IEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated titleICASSP 2018
Country/TerritoryCanada
CityCalgary
Period15/04/1820/04/18
Internet address

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