Deep Learning Models Can Pick Up on Distress Much Faster Than Humans

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When we see our models be the most active in terms of trading is when there's distress. The relationships that are traded, they don't work like when you say there's a momentum inversion. It's not that these models may not be picking up on momentum or whatever you would call it in a future language. What else do you think they can pick up faster than a super smart human or group of humans?

Julia is the co-founder of Rosetta Analytics Inc, “an alternative asset manager that is pioneering the use of advanced artificial intelligence to build and actively manage liquid investment strategies.” Prior to co-founding Rosetta, Julia served as President of Wilshire Consulting and was a member of Wilshire’s Board of Directors and Consulting Investment Committee. Julia joins the show to take a deep dive into deep reinforcement learning and Rosetta’s pioneering work using AI as the basis of its investment strategies. Important Links:

Show Notes:

Julia’s journey from Wilshire to Rosetta
Defining deep reinforcement learning
AI and non-linear thinking
Using adaptive models
Overcoming the human need for ‘why’
Pitching deep reinforcement learning models to new investors
Telling positive stories about AI; improving our discourse
“Wake up and look for the joy”; “overcoming fear is the biggest barrier to success”

Books Mentioned:

What Works on Wall Street: A Guide to the Best-Performing Investment Strategies of All Time; by Jim O’Shaughnessy
The Beginning of Infinity: Explanations That Transform the World; by David Deutsch
The Fourth Turning: An American Prophecy - What the Cycles of History Tell Us About America's Next Rendezvous with Destiny; by William Strauss and Neil Howe