AQR Capital Management

Cliff gave his thoughts on the choice between leverage risk and concentration risk in a recent interview with Ted Seides on the Capital Allocators podcast – listen to the clip below. Cliff covers regime changes in factors, machine learning, pod shops, private equity, serving on investment committees and more in the full episode linked below: - Apple: https://lnkd.in/eMteiaAp - Spotify: https://lnkd.in/eK5WJMtp

ICYMI: In a recent webinar, Cliff described AQR’s latest wave of innovations. Listen to it here: https://bit.ly/3Kel6qS To learn more about our Bayesian approach to incorporating new signals, read our paper on long/short equity design choices: https://bit.ly/3UVNumL

We recently held our inaugural London Forum, a full-day event that brought together a range of industry leaders for a series of presentations and discussions on the latest challenges and opportunities for the investment industry. Speakers included: - Elroy Dimson, Ph.D., Professor of Finance, Cambridge Judge Business School - John Greaves, Director of Fiduciary Management, Railpen - Matt Richardson, CEO, Income Analytics - Padmesh Shukla, Chief Investment Officer, Transport for London Pension Fund - James Barty, Managing Director of Investment Strategy, Church Commissioners for England - Matthew Yeates, Deputy Chief Investment Officer, 7IM - David Bateman, Head of Private Pensions DC Policy, Department for Work and Pensions - Thomas Maloney, Managing Director and European Head of the Portfolio Solutions Group, AQR - Lasse Pedersen, Ph.D., Principal, AQR - Bryan Kelly, Ph.D., Principal and Head of Machine Learning, AQR Thank you to all of our speakers and attendees for making it an enjoyable and insightful day! If you are a professional investor interested in attending our future events, please email teamuk&i@aqr.com.

Listen as Cliff talks about the market environment, value investing and a range of other topics on the Phil Bak Podcast. Apple: https://lnkd.in/eEQiacQi Spotify: https://lnkd.in/eY4GfQvA

Conventional wisdom suggests small, simple models are best suited for market timing applications, given finance’s “small data” constraint and naturally low predictability. However, in our latest, we show that complex models better identify true nonlinear relationships and therefore produce better market timing strategy performance. We validate this "virtue of complexity" result in three practical market timing applications: https://bit.ly/3WvF3AM

ICYMI: During a recent webinar, Cliff shared why investors should look for diversifying alternatives in the current environment. Listen here: https://bit.ly/4d9uycs

In a recent webinar, Cliff shares why investors may not be as diversified as they think and how alternatives can help. Listen to it below: https://bit.ly/3xQOcJU And to learn why a good time to diversity is when equities are riding high, be sure to read our paper, "Time to Diversify – But into What?": https://bit.ly/4aFu3oZ

Much of the existing academic finance literature predicts market returns with “simple” models that use only a few parameters. In this article, AQR’s Bryan Kelly and co-authors theoretically prove that, contrary to conventional wisdom, simple models severely understate return predictability compared to “complex” models in which the number of parameters exceeds the number of observations. They empirically document the virtue of complexity in U.S. equity market return prediction, and their findings establish the rationale for modeling expected returns through machine learning. Read the paper: https://bit.ly/49AsZRO

ICYMI: In a recent webinar, Cliff summed up our enthusiasm for multi-strats. Listen why: https://bit.ly/4aZbHPz And to learn more, be sure to read our paper "A Fresh Look at Multistrategy Alternatives": https://bit.ly/49BWkLI

AQR’s Cliff Asness was the guest on a recent episode of The Meb Faber Show. In the episode's wide-ranging discussion, Cliff provides insights on diversifying by both asset class and geography, the challenge of managing short-term expectations while keeping a long-term perspective, how AQR is implementing AI and machine learning, and more. Listen to the episode: Apple: https://apple.co/3vDJtLf Spotify: https://spoti.fi/3VVFu7k YouTube: https://bit.ly/3VUGYyF