David Ardia

I'm a quant at heart. I build methods that turn messy data — prices, news, filings, anything written down — into signals for risk, portfolios, and the economy. Financial econometrics is my home base; artificial intelligence, machine learning, and natural language processing are how I get there.

I've been shipping open-source code for twenty years. With my team I maintain a dozen R packages on CRAN — GARCH and regime-switching models, risk-based portfolios, textual sentiment, global optimization — because a method nobody can run is a method that doesn't exist. I'm also active in Sentometrics Research, bridging text mining, sentiment analysis, and econometrics, and FAME, a joint Paris Dauphine–PSL and HEC Montréal initiative on generative AI and large language models in financial markets.

Mostly, I like building things with people. Research is a team sport: with co-authors, postdocs, and students, the best ideas usually show up mid-argument in front of a whiteboard. I've supervised 4 PhDs, a dozen MSc theses, and more than 60 applied projects with industry partners, and I direct the MSc in Financial Engineering at HEC Montréal. If you're curious, rigorous, and up for having fun while doing serious work, come talk to me.

I am an elected member of the ISI, a member or researcher at CIRANO, CIREQ, CRM, Fin-ML, GERAD, and Quantact, an associate researcher at OBVIA and the Penner Institute, and an instructor at DataCamp.