Welcome to the Department of Statistics and Actuarial Science

The Department of Statistics and Actuarial Science is among the top academic units for statistical and actuarial science in the world and is home to more than 40 research active full-time faculty working in diverse and exciting areas. The Department is also home to over 900 undergraduate students and about 150 graduate students in programs including Actuarial Science, Biostatistics, Quantitative Finance, Statistics, and Statistics-Computing.

We are located on University of Waterloo main campus, which is located at the heart of Canada's Technology Triangle about 100 kilometers west of Toronto.

  1. Sep. 28, 2017David Sprott Distinguished Lecture by Susan A. MurphyDavid Sprott Distinguished lecture poster

  2. Aug. 10, 2017Pengfei Li is a 2017 recipient of the Faculty of Mathematics Award for Distinction in Teaching Pengfei Li

    The selection committee announced that Pengfei Li of the Department of Statistics and Actuarial Science is one of the two 2017 recipiants of the Faculty of Mathematics Award for Distinction.  Pengfei shares this honor with David Jao from the Department of Combinatorics and Optimization.

  3. July 12, 2017Samuel Eckler Medal in Actuarial ScienceAward winner Kieran Hendrickson-Gracie

    This prize was established to recognize the contribution of Samuel Eckler to the actuarial profession and is provided by Eckler Partners. The medal, which is cast in gold, is awarded each year to the outstanding graduating student of the Honours Actuarial Science Program.

    This year’s recipient is Kieran Hendrickson-Gracie who not only graduated as the top Actuarial Science major, but also has completed the five preliminary Society of Actuaries (SOA) exams, and earned three Cherry awards, in STAT 443, STAT 430, and STAT 431.

    Kieran's brother Aaron Hendrickson-Gracie, was awarded the Samuel Eckler Medal in 2013.

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  1. Oct. 26, 2017Department Seminar by Rafal Kulik, University of Ottawa

    Estimation of the expected shortfall given an extreme component under conditional extreme value model

    For two risks, $X$, and $Y$ , the Marginal Expected Shortfall (MES) is defined as $E[Y \mid  X > x]$, where $x$ is large. MES is an important factor when measuring the systemic risk of financial institutions. In this talk we will discuss consistency and asymptotic normality of an estimator of MES on assuming that $(X, Y)$ follows a Conditional Extreme Value (CEV) model. The theoretical findings are supported by simulation studies. Our procedure is applied to some financial data. This is a joint work with Kevin Tong (Bank of Montreal).

  2. Oct. 30, 2017Department seminar by Changchun Xie, University of Cincinnati

    Analysis of Clinical Trials with Multiple Outcomes

    In order to obtain better overall knowledge of a treatment effect, investigators in clinical trials often collect many medically related outcomes, which are commonly called as endpoints. It is fundamental to understand the objectives of a particular analysis before applying any adjustment for multiplicity. For example, multiplicity does not always lead to error rate inflation, or multiplicity may be introduced for purpose other than making an efficacy or safety claim such as in sensitivity assessments. Sometimes, the multiple endpoints in clinical trials can be hierarchically ordered and logically related. In this talk, we will discuss the methods to analyze multiple outcomes in clinical trials with different objectives:  all or none approach, global approach, composite endpoint, at-least-one approach.

  3. Oct. 31, 2017Department seminar by Wenqing He, Western University

    Data Adaptive Support Vector Machine with Application to Prostate Cancer Imaging Data

    Support vector machines (SVM) have been widely used as classifiers in various settings including pattern recognition, texture mining and image retrieval. However, such methods are faced with newly emerging challenges such as imbalanced observations and noise data. In this talk, I will discuss the impact of noise data and imbalanced observations on SVM classification and present a new data adaptive SVM classification method.

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Meet our people

Mary Hardy

Mary Hardy


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Mary Hardy

Research interests

Professor Hardy's research interests cover aspects of solvency and risk management for both life insurance and pension plans. The major recent focus has been in financial risk management, at the interface of actuarial science and financial engineering. She also works on the econometrics of risk management, especially for actuaries, for whom long-term horizons and deep out-of-the-money risks provide different challenges to the usual risks of banking.