Nang explains why traditional machine-learning pitfalls are amplified in finance: limited data, regime shifts, and the temptation to over-customise models for specific assets.
View full episode →“Intuition is a subconscious aggregation of relevant data, not a mystical ability”
“Out‑of‑sample R‑squared in finance is typically 0.03‑0.04, indicating very low predictive power”
“Confirmation bias, recency bias, and gambler’s fallacy are amplified when traders over‑interpret small sample results”