Beyond Spurious Correlations: Understanding Portfolio Risk with Causal AI

Our CEO, Dr. Darko Matovski delivered a webinar on the benefits of Causal AI for understanding risk and optimizing portfolios.

In this webinar, we:

  • Introduce the current state of machine learning in finance, highlighting its successes and failures.
    – While machine learning excels in static closed-looped systems, such as board games, most financial systems are dynamic, continuously changing in nature. This leads to many issues, including overfitting and spurious correlations
    – Current ML requires a trade off between explainable models (such as linear) or high performing models (like DNNs). It is hard to get both.
  • Introduce Causal AI and explain how it can overcome many of the limitations of current ML and share case studies of how it is currently proving that in production.
  • Give a product demo to show how Causal AI can be used to explain the relationships driving portfolio performance, simulate different scenarios that can affect performance and optimize portfolios.

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