Research paper / RESOURCE PROFILE

Financial Trading as a Game: A Deep Reinforcement Learning Approach

Huang, Chien Yi. arXiv preprint arXiv:1807.02787 (2018)

arxiv.orgPublished Jul 8, 2018
Visit source website ↗
Screenshot unavailableResource information and source links remain available. Financial Trading as a Game: A Deep Reinforcement Learning Approach — reviewed source website screenshot
Reviewed source screenshot · recorded Oct 11, 2026 View source ↗

Overview

Huang, Chien Yi. arXiv preprint arXiv:1807.02787 (2018)

Topics & capabilities

reinforcement-learningstrategiespaper

Publication information

Publication title
Financial Trading as a Game: A Deep Reinforcement Learning Approach
Authors
Chien Yi Huang
Published
Jul 8, 2018
Last publication revision
Jul 8, 2018
Subject areas
q-fin.TR, cs.LG, stat.ML
Publication source
arxiv.org · abs/1807.02787v1 ↗

Source: arXiv API · observed Oct 11, 2026.

Source links & provenance

https://arxiv.org/abs/1807.02787 ↗

Discovery references

References explain how this resource entered the collection. They do not represent an endorsement.

Explore related resources

Screenshot unavailableResource information and source links remain available. DeepIntoStreams/TSFM_Finance — reviewed source website screenshot
RepositoryChecked capture

DeepIntoStreams/TSFM_Finance

github.com

the official implementation of the paper “Re(visiting) Time Series Foundation Models in Finance”.

GitHub stars
31
Language
Jupyter Notebook
Code license
Apache-2.0
foundation-modeltime-seriesresearch-lab
96 Authority 96 / 100 Cited by 2 resources in this directory 2 discovery sources Directory record updated: 2026-10-11 How scoring works →

Sign In

Register

Reset Password

Please enter your username or email address, you will receive a link to create a new password via email.