deep-RL-trading and Reinforcement-Learning-for-Market-Making

deep-RL-trading
50
Established
Reinforcement-Learning-for-Market-Making
40
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 22/25
Stars: 360
Forks: 123
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 238
Forks: 58
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: —
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

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

About Reinforcement-Learning-for-Market-Making

KodAgge/Reinforcement-Learning-for-Market-Making

Using tabular and deep reinforcement learning methods to infer optimal market making strategies

This project helps quantitative traders and financial institutions to automatically set optimal bid and ask prices for financial assets. By analyzing market data and simulated trades, it provides strategies that balance profit from spreads with inventory risk. The output is an optimized market-making strategy, enabling more efficient and profitable liquidity provision.

Market Making Algorithmic Trading Quantitative Finance Liquidity Provision Financial Strategy

Related comparisons

deep-RL-trading and deep-trading-agent deep-RL-trading and QLearning_Trading deep-RL-trading and Deep-RL-Stocks deep-RL-trading and trade-rl

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