The educational aim of this program is to provide well-rounded training for careers in research, teaching or industrial work in which advanced mathematics, or large scale computation is used in an essential way. For more information, please see the university calendar.
The Mathematics of Finance concentration studies the foundations of financial theory, including asset pricing and financial institutions.
Although actuaries normally only need a bachelor's degree, they do need to take a range of courses to prepare for the career, including classes in programming, statistics, risk management, and economics--all of which are usually included in a mathematical finance PhD program. MATH 601 Measure and Integration The concentration also provides a strong background for candidates who eventually want to pursue a PhD in economics or finance. In this course, you will likely study such areas as numerical linear algebra programming and differential equations.
CANADA, Introduction to Levy Processes with Applications in Finance, Monte Carlo Methods in Finance-Existing Course, Stochastic Optimal Control & Applications in Finance, Energy, Commodity and Environmental Finance, School of Architecture, Planning and Landscape, Certificate in Data Science and Analytics, Undergraduate Science Centre and Student Success Centre, Faculty of Graduate Studies and MyGradSkills, Algebraic Geometry, Number Theory and Cryptography, Combinatorics, Discrete Mathematics, Geometry and Logic, Pure and Applied Analysis, and Mathematical Physics, Statistics, Big Data Analysis, and Applications to Biology, Medicine, and the Oil and Gas Industry, Giving to the Department of Mathematics and Statistics, Courses in rigorous mathematics (advanced linear algebra, advanced calculus, differential equations, analysis), A course in theoretical or applied probability, and/or mathematical statistics at the graduate level, Courses in real analysis, and possibly measure theory, advanced probability (limit theorems, sigma fields), stochastic processes (e.g., Wiener, Poisson processes), A broad range of courses in statistical methods (statistical computing, Bayesian statistics, generalized linear models, time series, multivariate statistics), Undergraduate or graduate computer science courses, Research or work experience relevant to mathematical finance or stochastic processes/probability/statistics, Solid programming experience (e.g., C, C++, Fortran, Python, R, SAS, Matlab), At least one additional course from List B (see below), At least two additional courses from List B or List C (see below). What are Ways to Finance a College Education? MATH 693.05 Advanced Topics in Mathematical Finance, Haskayne Courses: Actuaries, mathematicians, and economists can often benefit from programs of this type. This course could cover a range of numerical methods, models, and solutions.
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