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Quant trading is a science in implementation but an art in algorithm design
  • Nang uses the autopilot analogy: once the algorithm is designed, it runs autonomously.
  • The scientific part is writing, testing, and executing code; the artistic part is deciding which signals, parameters, and objective functions to embed.
  • This duality explains why many quant managers still need human intuition for model design.
  • The art‑science split also clarifies why purely mechanical systems can still fail if the design is flawed.
Rishi NangTitans Of Tomorrow00:02:16

Supporting quotes

The science part is in the implementation and the art part is in designing the machine that is doing the implementation. Rishi Nang
And then, we're good at letting it run. What we're bad at is doing those things repeatedly. So the art is in designing the algorithm but once it's designed, it's actually best to mostly just let it run. Rishi Nang

From this concept

Quant vs. Discretionary: The Art-Science Spectrum

Nang frames quant trading as a blend of scientific implementation and artistic design. He highlights the key blind spots that discretionary traders overlook and the rigor that quant traders must embed.

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