Everyone wants an edge in the market, and machine learning models claim to predict the next big stock. But how reliable are these AI-driven forecasts? In this episode, we dive into the uncertainty hidden behind machine learning predictions and explore cutting-edge research on forecast confidence intervals (FCIs).We break down two powerful methods—mathematical approximations and K-step bootstrapping—that help investors measure uncertainty and make smarter portfolio decisions. Whether you're a casual investor or a finance pro, understanding these concepts could transform how you allocate assets.Are you accounting for uncertainty in your investment strategy? Tune in to find out!Find the full research paper here: https://community.quantopian.com/c/community-forums/the-uncertainty-of-machine-learning-predictions-in-asset-pricingFor 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.

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