Welcome to Statistics and Actuarial Science

The Department of Statistics and Actuarial Science is a top-tier academic unit among statistical and actuarial science globally. Our community is engaged in topics such as actuarial science, biostatistics, data science, quantitative finance, statistics, & statistics-computing. Our department is home to more than 60 full-time faculty researching diverse and exciting areas, over 1000 undergraduate students from around the world, and more than 175 graduate students in master, doctoral, and professional programs.


More than 150 students participated last week in the second annual Scotiabank Data Science Discovery Days.

The event, which took place both online and on campus from January 26 to February 2, invited Waterloo students to analyze large volumes of data in projects that would emulate the real work data scientists di every day. This year, the event focused on “Using AI to derive business insights from customer feedback.”

Read the full article on the Faculty of Math site.

The fourth annual Student Conference in Statistics, Actuarial Science, and Finance took place on October 27 & 28, 2023. This two-day event was entirely organized by and for students.

The conference featured keynote presentations by prominent researchers, including Agostino Capponi (Columbia University) and Grace Yi (Western University). Additionally, 30+ student researchers from various universities presented their research findings.

Highlighting excellence, the conference acknowledged outstanding talks at the conference by issuing 6 Presentation Awards to the following participants:

The winners in alphabetic order are:

  • Luke Hagar, University of Waterloo  
  • Dingding Hu, University of Waterloo  
  • Yifan Li, University of Western Ontario  
  • Dante Mata Lopez, UQAM  
  • Zachary Van Oosten, University of Waterloo  
  • Augustine Wigle, University of Waterloo 

 Honourable mentions go out to: 

  • Yuling (Max) Chen, University of Waterloo 
  • Hwanwoo Kim, University of Chicago

The Institute for Operations Research and the Management Sciences (INFORMS) has awarded department members Alexander Schied and Ruodu Wang, along with co-author Paul Embrechts (ETH Zurich) the Best Paper Award on Financial Engineering in the journal "Operations Research".

The paper aims to understand the consequences of risk optimization in finance when the model being used is uncertain or wrong. The conclusion is that some classic methods of risk assessment, called risk measures in the scientific field, are problematic, and some new methods in financial regulation are much better.

For this purpose, the authors study issues of robustness in the context of Quantitative Risk Management and Optimization. They develop a general methodology for determining whether a given risk-measurement-related optimization problem is robust, called “robustness against optimization.” The new notion is studied for various classes of risk measures and expected utility and loss functions. Motivated by practical issues from financial regulation, special attention is given to the two most widely used risk measures in the industry, Value-at-Risk (VaR) and Expected Shortfall (ES). The authors establish that for a class of general optimization problems, VaR leads to nonrobust optimizers, whereas convex risk measures generally lead to robust ones. The results offer extra insight on the ongoing discussion about the comparative advantages of VaR and ES in banking and insurance regulation. The new notion of robustness is conceptually different from the field of robust optimization, to which some interesting links are derived.