QLearning_Trading and deep-RL-trading

QLearning_Trading
51
Established
deep-RL-trading
50
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Stars: 517
Forks: 181
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 360
Forks: 123
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About QLearning_Trading

ucaiado/QLearning_Trading

Learning to trade under the reinforcement learning framework

This project helps financial traders develop an adaptive strategy for trading a single stock. By inputting historical stock data, it trains an agent through a reward/punishment system to learn and maximize profits. The output is a trading strategy that has learned from experience. This tool is for individual traders or quantitative analysts looking to automate and optimize their trading decisions.

algorithmic-trading quantitative-finance stock-market trading-strategy financial-modeling

About deep-RL-trading

golsun/deep-RL-trading

playing idealized trading games with deep reinforcement learning

This project helps quantitative traders develop and test automated trading strategies. It takes historical market data as input and provides an optimized trading strategy for momentum or arbitrage opportunities as output. Traders and quantitative analysts seeking to apply machine learning to financial markets would use this.

quantitative-trading algorithmic-trading financial-modeling market-arbitrage momentum-strategies

Related comparisons

QLearning_Trading and trade-rl QLearning_Trading and deep-trading-agent QLearning_Trading and Deep-RL-Stocks QLearning_Trading and Reinforcement-Learning-for-Market-Making QLearning_Trading and trade-rl

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