Menu
Sign In Search Podcasts Charts People & Topics Add Podcast API Pricing
Podcast Image

Excess Returns

Applying Machine Learning to Value Investing with Euclidean’s John Alberg

10 Apr 2022

Description

Value investing has produced some of the greatest investors of all time. Whether it be Benjamin Graham's deep value approach or Warren Buffett's quality at a reasonable price strategy, value has a long track record of success. But what if the great value investors of the future won't be human at all? What if machines can be trained to identify the best value stocks? In this episode, we talk to John Alberg of Euclidean Technologies about applying machine learning to the process of selecting value stocks. We talk about the different types of machine learning and how these techniques can be utilized to select fundamentally sound stocks, We also discuss using machine learning techniques to avoid value traps, whether intuitive factors are more successful, areas where humans can still perform better than machines and much more. We hope you enjoy the discussion. ABOUT THE PODCAST Excess Returns is an investing podcast hosted by Jack Forehand (@practicalquant) and Justin Carbonneau (@jjcarbonneau), partners at Validea. Justin and Jack discuss a wide range of investing topics including factor investing, value investing, momentum investing, multi-factor investing, trend following, market valuation and more with the goal of helping those who watch and listen become better long term investors. SEE LATEST EPISODES https://www.validea.com/excess-returns-podcast FIND OUT MORE ABOUT VALIDEA https://www.validea.com FOLLOW OUR BLOG https://blog.validea.com FIND OUT MORE ABOUT VALIDEA CAPITAL https://www.valideacapital.com FOLLOW JACK Twitter: https://twitter.com/practicalquant LinkedIn: https://www.linkedin.com/in/jack-forehand-8015094 FOLLOW JUSTIN Twitter: https://twitter.com/jjcarbonneau LinkedIn: https://www.linkedin.com/in/jcarbonneau

Audio
Featured in this Episode

No persons identified in this episode.

Transcription

This episode hasn't been transcribed yet

Help us prioritize this episode for transcription by upvoting it.

0 upvotes
🗳️ Sign in to Upvote

Popular episodes get transcribed faster

Comments

There are no comments yet.

Please log in to write the first comment.