Quantitative Finance - Master of Quantitative Finance (MQF)

Mathematics 3 Building

Mathematics 3 (M3) Building on Waterloo's Campus

Today's financial industry is rapidly evolving and complex. The Master of Quantitative Finance (MQF) program focuses on the fundamental disciplines of mathematics, statistics, econometrics, machine learning, computer science and finance to provide the analytical tools to solve practical problems in the complex world of finance.

You’ll be equipped for positions with financial institutions, corporations and government regulatory organizations.

Based in the Department of Statistics and Actuarial Science, the program is offered with the option of a research paper or a thesis. The thesis option is best if you’re interested in pursuing research or a PhD, while the research paper option allows you to complete an internship where you’ll acquire practical experience in a real-world setting to graduate career ready. 

Research areas of the program include artificial intelligence, business and industrial statistics, computational statistics, data science, machine learning, probability, statistical modeling and inference, and survey methods. Graduates come away from the program equipped for a range of positions that require advanced skills in quantitative finance, such as financial engineers in model vetting and risk compliance, analysts in portfolio credit and market risk, asset managers and portfolio managers. 

Program highlights

  • Real-world, hands-on experience with the internship option. 

  • Well respected by top firms in the financial industry.   

  • Track record for developing internship placements and career opportunities.   

 

Program overview

Department/School: Statistics and Actuarial Science
Faculty: Faculty of Mathematics
Admit term(s): Fall (September - December)
Delivery mode: On-campus
Program type: Master's, Professional
Length of program: 16 months (full-time)
Registration option(s): Full-time
Study option(s): Thesis, Master's Research Paper

Application deadlines

  • January 15 (for admission in September)

Key contacts

Supervisors

Admission requirements

  • An overall 80% average from a Canadian University (or its equivalent).
  • A four-year honour's Bachelor's degree (or equivalent) with a strong background in quantitative methods. Such a background may be in mathematics, statistics, actuarial science, computer science, economics, engineering, physics, provided there is a strong component of high level mathematics in the program. Strong communication skills are also highly desirable.
  • An interview and diagnostic test may be required.

Degree requirements

  • Review the degree requirements on the Graduate Studies Academic Calendar, including the courses that you can anticipate taking as part of completing the degree

Application materials

  • Resume
  • Supplementary information form (SIF)
    • The SIF contains questions specific to your program, typically about why you want to enrol and your experience in that field. Review the application documents web page for more information about this requirement
    • If a statement or letter is required by your program, review the writing your personal statement resources for helpful tips and tricks on completion
  • Transcript(s)
  • References
    • Three references are required, at least two academic
  • Proof of English language proficiency, if applicable
    • TOEFL 90 (writing 25, speaking 25), IELTS 7.0 (writing 6.5, speaking 6.5)

Tuition and fees