Truth Engine
Applying AI to Investing
When Renaissance Technologies Tanked Their Fund
In this excerpt, tribulations rocked the premier machine learning firm.
It was a sunny day on Wall Street, and the machine was learning. In nearby Long Island, a small group of mathematicians led by an erstwhile Stony Brook department chair implemented what would be wildly successful learning algorithms on market data. Automation removed the slow reaction times of human input. Yet in terms of broader impact, Renaissance Technologies' methods fell short. Firms like Citadel torpedoed market liquidity benefits via algorithmic front-running. When Renaissance launched their value fund, the Institutional Equities Fund, it failed to deliver on their expectation. Shortly after creation, the fund dropped 8.7% in the single month of August 2007 and worse, lagged the market by 10%.
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About the Book
An Amazon bestseller (Stock Market Investing and AI & Semantics categories). Unlock the future of finance with this definitive guide to machine learning in investing. Following the wisdom of Charlie Munger, the book equips you with multifaceted mental models to decipher the complexities of the market. Master machine learning principles that sharpen your insights, fortify your strategies with advanced tools like generative AI, and build intuition around data's nuanced role in your models. Systems design, portfolio optimization, and performance evaluation? Covered. Navigate the murky waters of cognitive biases and leverage generative AI to elevate quantitative analysis. You are equipping for the next evolution in intrinsic value investing. Prepare to redefine the boundaries of what's possible in comprehensive investing.
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About the Author
Leonidas Tam
Leo is the Co-Founder and Managing Partner of Amicus Investments, an ML research and advisory firm. He is a seasoned leader in AI, having founded and launched the NVIDIA Deep Learning Institute, the global educational and professional development organization. Previously, he was a Senior Research Scientist at NVIDIA and a research scientist at Stanford University Department of Radiology. At Stanford, he demonstrated outstanding performance in competitions, placing in the top 3% of a competition sponsored by the California Healthcare Foundation, and securing second place in a commodities trading contest. He holds multiple patents in deep learning and machine learning. Leo earned his BSc in Mathematics-Physics from Brown University and Engineering PhD from Yale University.
Episode 295
An Interview with Leonidas Tam
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