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.
238 stars. No commits in the last 6 months.
Use this if you are a quantitative trader, market maker, or financial analyst looking to develop or evaluate automated strategies for setting bid and ask prices in financial markets.
Not ideal if you need a simple, off-the-shelf trading bot for personal investing or if you are not involved in continuous, high-volume market making activities.
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Last pushed
Jun 29, 2023
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