This week, Ethan Kho sits down with Dr. Ernest P. Chan — former quant at Millennium and Morgan Stanley, and now founder of PredictNow.ai and QTS Capital Management. Ernie is one of the best-known voices in quant finance, author of Quantitative Trading, and a pioneer in systematic trading strategies.
We cover:- When machine learning trading models work in markets — and when they fail- Why financial markets suffer from data sparsity, and how regime shifts and black swan events in finance break models- How quants use AI in trading for risk management and portfolio optimization- The promise of LLMs for financial markets and how generative AI can overcome data scarcity- Semi-supervised learning explained, with real examples from analyst reports and Fed speeches- Where quants can still find alpha generation when new technologies become widely available- How PredictNow helps banks and hedge funds apply AI risk management at scale- Lessons from launching QTS Capital and running independent quant trading strategies such as crisis alpha- The role of alternative data in hedge funds and what actually drives performance post-2008- What it was like working alongside quants at Millennium, Morgan Stanley, Credit Suisse — and how Renaissance Technologies influenced Ernie’s career- The traits that make a great quant, and why creativity still matters in quantitative trading strategies= Advice for students and professionals entering quant finance in the age of financial big data and generative AI- How to spot overfitting in backtests and apply the scientific method in systematic trading strategies- Why risk awareness separates long-term success from blow-ups in post-2008 quant strategies