A sit-down with Raffaele Ghigliazza, a quant with a PhD background in mechanical engineering and deep work across applied math, dynamical systems, and neuroscience. He has spent about 20 years in finance, split between risk and asset management, and currently works as a macro-systematic researcher.

We discuss quant research after LLMs: what LLMs really changed, how to think about backtesting, and why robustness matters more than ever. Topics include business cycles, data limitations, overfitting, CPCV and cross-validation, ensembling, and why mixing market regimes can break a model.

*DISCLAIMER*

The information shared on this podcast is for educational and informational purposes only and reflects the personal opinions of the hosts and guests at the time of recording. Nothing in this podcast constitutes financial, investment, legal, tax, or trading advice, and nothing should be interpreted as a recommendation to buy, sell, or hold any security, cryptocurrency, derivative, or financial product.

Trading and investing involve substantial risk, including the possible loss of all or part of your capital. You are solely responsible for your own decisions, and you should consult a qualified professional before making financial decisions. By listening to this podcast, you agree that the hosts, guests, and producers are not liable for any losses or damages arising from the use of any information discussed.