FinRL-DeepSeek - new trading AI agents combining Reinforcement Learning with Large Language Models
In algorithmic trading, leveraging unstructured data, like financial news, and managing risk in bear market phases remain challenging.
Our research lab continuously explores the frontiers of quantitative trading, combining academic rigor with practical market applications
Developing advanced RL algorithms that adapt to market conditions and optimize trading strategies in real-time
Leveraging LLMs for market sentiment analysis, news processing, and natural language understanding of market dynamics.
Cutting-edge expertise in decentralized finance protocols, yield farming strategies, and cross-chain arbitrage opportunities.
At Jiang Street, we operate as a research lab with trading bots attached to it. Our team of quantitative researchers, data scientists, and engineers work together to push the boundaries of what's possible in algorithmic trading. We believe that the future of quantitative trading lies in the convergence of Artificial Intelligence and Blockchain technologies, especially reinforcement learning, large language models, and decentralized finance.
Learn more about how Jiang Street approaches problems, and about Fintech more broadly.
In algorithmic trading, leveraging unstructured data, like financial news, and managing risk in bear market phases remain challenging.
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