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In this episode I chat with Mads Ingwar and Martin Oberhuber, co-founders of Kvasir Technologies, a systematic hedge fund powered by a full-stack application of machine learning.
By full-stack I mean every layer of the process, including data ingestion, signal generation, portfolio construction, and execution, which gives us a lot to talk about.
Our conversation covers topics ranging from the limitations of machine learning and hard lessons learned to how to keep up in a rapidly evolving field and thoughts about managing model risk.
Given the niche knowledge in a field like machine learning, some of my favorite answers came when I asked how they might perform due diligence upon themselves or where they think other adopters of machine learning go wrong. For allocators, I think these answers are priceless.
I hope you enjoy my conversation with Mads and Martin.
By Corey Hoffstein4.9
228228 ratings
In this episode I chat with Mads Ingwar and Martin Oberhuber, co-founders of Kvasir Technologies, a systematic hedge fund powered by a full-stack application of machine learning.
By full-stack I mean every layer of the process, including data ingestion, signal generation, portfolio construction, and execution, which gives us a lot to talk about.
Our conversation covers topics ranging from the limitations of machine learning and hard lessons learned to how to keep up in a rapidly evolving field and thoughts about managing model risk.
Given the niche knowledge in a field like machine learning, some of my favorite answers came when I asked how they might perform due diligence upon themselves or where they think other adopters of machine learning go wrong. For allocators, I think these answers are priceless.
I hope you enjoy my conversation with Mads and Martin.

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