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An Adaptive Financial Trading System Using Deep Reinforcement Learning

When applying artificial intelligence technology to quantitative trading, high noise and unpredictability of market environment are the first practical problems

AI Trading & Research
doi.orgPublished 2020
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Overview

When applying artificial intelligence technology to quantitative trading, high noise and unpredictability of market environment are the first practical problems

Publication information

Publication title
An Adaptive Financial Trading System Using Deep Reinforcement Learning With Candlestick Decomposing Features
Authors
Ding Fengqian, Luo Chao
Published
2020
Venue / journal
IEEE Access
DOI
10.1109/access.2020.2982662 ↗
Publication source
doi.org · 10.1109/access.2020.2982662 ↗

Source: Crossref public DOI API · observed Oct 11, 2026.

Publisher page information

Source page title
An Adaptive Financial Trading System Using Deep Reinforcement Learning With Candlestick Decomposing Features | IEEE Journals & Magazine | IEEE Xplore
Declared page language
en-US
Observed source URL
https://ieeexplore.ieee.org/document/9044812/ ↗
Publisher canonical URL
https://ieeexplore.ieee.org/document/9044812/ ↗
Source metadata observed
Oct 11, 2026

Recorded from the source page’s published HTML metadata. Publisher page language can differ from this directory’s English interface.

Source links & provenance

https://doi.org/10.1109/ACCESS.2020.2982662 ↗

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