The Hidden Risks of Multi-Factor KPI Models Using Alternative Data

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Simplicity Over Complexity: The Hidden Risks of Multi-Factor KPI Models Using Alternative Data

By Qaisar Hasan

In this article, Maiden Century CEO Qaisar Hasan, discusses the pitfalls of relying on complex multi-factor models in the investment management industry. While the allure of precision and the abundance of Alternative Data can make these models seem attractive on paper, they often fail to deliver expected results in the real-world. A simpler approach, grounded in investor intuition and fundamental analysis, leads to more reliable and transparent forecast models that outperform in the long term.


Key Takeaways:


  • Complexity Trap: Complex does not always mean better. The allure of complex multi-factor models, which often look good on paper but fail in real-world applications can have serious consequences in the world of hedge funds.
  • Overfitting Issue: Alternative Data can be cut in a myriad of different ways and optimizing inputs and factor weights can lead to overfitting.
  • Importance of Simplicity: Investors are better served by models they can understand and explain to their peers as opposed to purely statistical models with superfluously high R-squared coefficients and factors that are difficult to articulate.
  • Intuition and Transparency: Maiden Century’s approach focuses on models that are intuitive and transparent, aiming to build trust with managers and provide actionable insights for investors.
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