Can less data actually lead to better predictions? In this deep dive, we explore groundbreaking research on mortgage default prediction that challenges everything we thought we knew about big data. Discover why using shorter time frames and fewer variables can improve accuracy, and how this insight applies beyond finance—into tech, fashion, and even social trends.

Join us as we break down the key takeaways, real-world implications, and why strategic data selection matters more than ever. Get ready to rethink the way we predict the future!

Find the full research paper here: https://community.quantopian.com/c/community-forums/time-series-feature-redundancy-paradox-an-empirical-study-based-on-mortgage-default-prediction

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.

Quant Radio: Why More Data Can Hurt Your Predictions