December 1st, 2020

Navigating the Quant Shock: How Machine Learning Can Help Portfolios Through Regime Shifts

Machine learning can be useful for a lot of things – picking out movies to suggest, performing live translation, even (one day) fully self-driving cars. In investment and finance, the application of machine learning is still relatively new, but it offers exciting results, especially in the age of uncertainty we find ourselves in, here in

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November 20th, 2020

Boosted.ai Featured in TabbForum on the Three Top Downfalls of Quant Investors

Why do some quant strategies fail? It has to do with all of the human decisions that go into setting up the machine.

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August 26th, 2020

Boosted.ai Featured in Waters Technology on Navigating COVID-19 Risks

How can you measure and predict the effects of something that hasn’t happened in a century?

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August 26th, 2020

Understanding the Machine: The Importance of Relative Valuation

The rise of the machines: not just the lukewarm third installment of the Terminator series, but also, the ominous headline nearly every publication uses when writing about machine learning.

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August 26th, 2020

Boosted.ai Raises $8 Million to Bring Artificial Intelligence To Investment Management

We are thrilled to announce that we recently closed an $8 million USD Series A financing round, led by Portag3 Ventures.

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August 26th, 2020

Portfolio Construction and the COVID Cluster

· While we do not have a crystal ball and cannot know which stocks will become most impacted by some future event, we offer a solution of how to mitigate this problem by using the example of the COVID cluster of stocks. · Using advanced machine learning techniques, we can create portfolios with increased resilience

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August 26th, 2020

Modelling The Coronavirus Risk Factor & Neutralizing It

Nobody can tell the future. Six months ago, I would have never guessed (even for April Fool’s Day) that we would find ourselves here, in a real-life version of the film Contagion. Modelling a black swan event like COVID-19 with traditional quantitative techniques is extremely difficult, due precisely to any black swan event’s inherent unpredictability.

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