Use HFTFramework to create algorithms that make markets more efficiently.
Automations like optimizing market-making performance for your high-frequency trading system.
HFTFramework improves market making performance with research-backed strategies, making it a valuable tool for founders in high-frequency trading.
"A founder wants to improve the performance of their high-frequency trading system. They use HFTFramework to implement a reinforcement learning approach to the Avellaneda-Stoikov market-making algorithm. Within a few hours, they've optimized their system to execute trades more efficiently."
You should pick this up if you're new to high-frequency trading and want to learn from the research.
A senior engineer/professional would use this for its research-backed strategies and high-frequency trading expertise.
HFTFramework is primarily designed for high-frequency trading, making it not suitable for general machine learning tasks.
HFTFramework utilized for research on " A reinforcement learning approach to improve the performance of the Avellaneda-Stoikov market-making algorithm "
Read the entire source before you build โ unlike paid marketplaces that hide it behind a buy button.
Are you the creator of this tool? Claim your listing โ and earn 85% of every sale.
More ai-agent tools founders pair with this one.