Are traditional short-term trading strategies missing something big? In this episode, we dive into a groundbreaking approach that challenges a core assumption in finance — that all stocks have the same expected short-term return. Meet ESTER: the short-term excess return strategy powered by machine learning.

Join us as we explore how advanced algorithms analyze over 200 stock-level factors to calculate personalized expected returns — and how comparing these to actual returns can uncover mispricings caused by investor overreaction. It's buy low, sell high — but smarter.

Whether you're a quant nerd, market enthusiast, or just curious about how AI is reshaping investing, this episode is packed with insights. From gradient-boosted trees to neural networks, this is where finance meets frontier tech.

Find the full research paper here: https://community.quantopian.com/c/community-forums/mispricing-and-correction-in-short-term-returns

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.