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 about 50 research active full-time faculty working in diverse and exciting areas. The Department is also home to around 1000 undergraduate students and about 175 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 kilometres west of Toronto.


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The first Waterloo Conference in Statistics, Actuarial Science, and Finance

April 25 & 26, 2019 in Waterloo, ON. 

  1. May 31, 2019Master of Actuarial Science (MACTSC) 10th AnniversaryMACTSC 10th Anniversary Banner

    In 2019, the Master of Actuarial Science (MActSc) professional degree program will be celebrating 10 wonderful years at the University of Waterloo. 

    MActSc is an internationally renowned program in actuarial science and risk management, and is located within the Department of Statistics and Actuarial Science. This fast track professional program is only offered to the best and brightest students from around the world. Once accepted these students receive one-on-one interpersonal training from prominent faculty in the field of actuarial science. After 10 rigorous and demanding years, staying on the cutting edge of the industry and training the most elite in this field, the MActSc program will be celebrating by hosting a banquet dinner on May 31, 2019. 

    This event will be great opportunity for past and current students, faculty, and industry supporters to celebrate their hard work over the past decade.     

  2. Apr. 30, 2019April Is Mathematics and Statistics Awareness Month!Image of a Globe

    Every April, math and statistics associations across the country celebrate Mathematics and Statistics Awareness Month, a full month of programs and initiatives dedicated to promoting better public understanding of mathematics and statistics. ASA programs include a virtual science fair, weekly challenge questions, and video Q&As with working professionals! We hope you enjoy these fun opportunities to participate and share them with your friends and colleagues.

    Learn More at AM STAT News.

    View more about ASA Member News online.

  3. Apr. 4, 2019Waterloo helps Indonesian university launch co-op programRepresentatives from the University of Waterloo, Indonesian universities and government officially launch a co-op office.

    Waterloo helps Indonesian university launch co-op program

    On March 12, Bill Duggan, the University of Waterloo’s READI Project Field Director, joined with Dr. Totok Prasetyo, Director of Institutional Development of Higher Education (Kemenristekdikti), Abdullah Mojadeddi, First Secretary of the Embassy of Canada and Prof. Djisman Simandjuntak, Rector, Prasetiya Mulya University, to open Indonesia’s first Co-operative Education Office at Prasetiya Mulya University.

    As one of the READI Project’s first Indonesian university stakeholders, Prasetiya Mulya University embraced the co-operative education model immediately. They have devoted significant time and resources over the past two years to adapting their educational structure as they pioneered the development of this very effective type of work-integrated learning.

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  1. Apr. 25 to 26, 2019Waterloo Conference in Statistics, Actuarial Science and FinanceGeneric Pink Graph

    The first Waterloo Conference in Statistics, Actuarial Science, and Finance (WATSAF1). 

  2. Apr. 25, 2019David Sprott Distinguished Lecture by Damir Filipovic, EPFL and Swiss Finance Institute Senior ChairDamir Filipovic

    A Machine Learning Approach to Portfolio Risk Management


    Risk measurement, valuation and hedging form an integral task in portfolio risk management for insurance companies and other financial institutions. Portfolio risk arises because the values of constituent assets and liabilities change over time in response to changes in the underlying risk factors. The quantification of this risk requires modeling the dynamic portfolio value process. This boils down to compute conditional expectations of future cash flows over long time horizons, e.g., up to 40 years and beyond, which is computationally challenging. 

    This lecture presents a framework for dynamic portfolio risk management in discrete time building on machine learning theory. We learn the replicating martingale of the portfolio from a finite sample of its terminal cumulative cash flow. The learned replicating martingale is in closed form thanks to a suitable choice of the reproducing kernel Hilbert space. We develop an asymptotic theory and prove
    convergence and a central limit theorem. We also derive finite sample error bounds and concentration inequalities. As application we compute the value at risk and expected shortfall of the one-year loss of some stylized portfolios.

  3. May 3, 2019Department seminar by Vali Asimit, Cass Business School

    To be announced (TBA)

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Meet our people

Mu Zhu

Mu Zhu

Professor

Contact Information:
Mu Zhu

Mu Zhu personal website

Research interests

Mu's main research interests are machine learning, multivariate analysis, and network data analysis, with their applications to bioinformatics, health informatics, and data mining. He is currently working with colleagues and students on generative neural networks, statistical dependence, and large covariance matrices.