In this video, we explore cutting-edge research on statistical arbitrage using reinforcement learning, led by researchers Boming Ning and Kisiup Lee from Purdue University. Discover how AI is transforming trading by analyzing market patterns and making strategic decisions for profit. We’ll break down key concepts, from the basics of statistical arbitrage to advanced methods like the distance method, Ornstein-Uhlenbeck process, and a new concept called "empirical mean reversion time." Learn how reinforcement learning empowers AI to identify profitable market opportunities by “training” it to predict price snaps in stock pairs. Watch as we discuss real-world tests, including a study on the S&P 500, and find out how this AI-driven strategy could change the game for investors everywhere! For more quant-focused content, join us at ⁠⁠⁠⁠https://community.quantopian.com⁠⁠⁠⁠. There, you can explore a wealth of resources, connect with fellow quants, engage in insightful discussions, and enhance your skills through our extensive range of online courses. Quant Radio is an AI-generated podcast, intended to help people develop their knowledge and skills in Quant finance. This podcast is not intended to provide investment advice.