Founder and Scientific Director
and Risk Management Labs
Ruslan Goyenko is an Associate Professor of Finance at Desautels Faculty of Management, McGill University. He received PhD in Finance from Indiana University, Kelley School of Business. He also held faculty appointments at the University of Toronto and Notre Dame University. While his primary area of expertise is liquidity and liquidity risk among different asset classes, his most recent research is focused on the application of machine learning in asset pricing, such as return predictability, optimal portfolio construction and optimization, and the risk management. He published in top finance journals such as the Review of Financial Studies, Journal of Financial Economics, and Journal of Financial and Quantitative Analysis. Ruslan co-organizes and continues organizing prestigious academic and industry conferences on Asset Management. He is a recipient of numerous research grants from The Social Sciences and Humanities Research Council of Canada, and more recently from Autorité des Marchés Financiers (Québec).
Senior Advisor & Research Associate
Dr. Jonathan Brogaard is a Professor of Finance at the University of Utah’s David Eccles School of Business. His research interests focus on market microstructure and empirical asset pricing to examine the impact of automated and high-speed trading on equity and commodity markets, both in the United States as well as internationally. This work has been published extensively across the top finance journals, including, the Journal of Finance, the Journal of Financial Economics, and the Review of Financial Studies. It has also been cited in major media publications, including Businessweek, Bloomberg, The Economist, Financial Times, Newsweek, The New Yorker, New York Times, and Wall Street Journal, contributing to debates on such topics as the role of passive index investing, commodity markets pricing, high-frequency trading, and exchange design in securities markets.
Core Faculty Associates
Zhenzhen Fan is an assistant professor at the Asper School of Business, University of Manitoba (Winnipeg, Canada). Zhenzhen obtains her Ph.D. from the University of Amsterdam (Amsterdam, the Netherlands). Her major research area is empirical asset pricing, including topics on climate risk, cryptocurrencies, financial derivatives, foreign exchange rates, etc. Zhenzhen has published in top finance journals, such as Journal of Financial and Quantitative Analysis and Journal of Financial Economics.
Fred Liu is an assistant professor in finance at the University of Guelph. He earned his PhD in Economics from Western University in 2021. He received an MA in Economics from Western University in 2015, a BA in Economics from the University of Waterloo in 2014, and a BBA in Finance from Wilfrid Laurier University in 2012. His research focuses on applying machine learning in asset pricing, risk management, and high-frequency financial markets.
Chengyu Zhang is a Ph.D. student in finance at McGill University. His research interests include applications of machine learning in asset pricing and optimal portfolio construction. He received an honors bachelor’s degree in statistics from the University of Toronto, and a master’s degree in finance from McGill University.
Philippe conducts cutting edge research in applied machine learning and is specialized in time series modelling. Prior to joining Firm Labs, Philippe completed a Phd/MSc/BSc in computer science at the University of Sherbrooke where his research program focused on developping time series models with adaptive computation. He also worked in collaboration with Laplace Insights as the lead machine learning researcher developping time series model for Dynamic Global Macro and low-volatility ESG porfollio strategies.
WenJing Cai is a Ph.D. candidate in Economics at McGill University under the supervision Jean-Marie Dufour. She is a research associate at FIRM Labs and a quantitative researcher at CIRANO. Her primary research interest is Financial Econometrics and Finite Sample Inference.
Qiwei Shao is a master’s student of Computer Science at University of Montreal. His main research focus is the application of machine learning in finance and text. He has done several research projects in portfolio construction, natural language processing and information retrieval.
Jeffrey Yang is a finance Ph.D. student at the University of Utah's David Eccles School of Business. His research interests include empirical asset pricing and market microstructure. Jeffrey holds a B.S. in Economics and Mathematics from the University of Oregon.