Mathematical Finance as a discipline borrows concepts from probability theory, statistics, linear algebra, calculus and optimization, ordinary and partial differential equations, computer science and financial economics. This course reviews the essential prerequisites in mathematics, probability and statistics to prepare students for the MS in Mathematical Finance program. The course begins with a review of probability and the fundamentals of stochastic processes. Following this, statistical inference and linear algebra are reviewed. A review of comparative statics, optimization theory and dynamics, beginning with a review of integration, and continuing with first- and higher- order differential equations concludes the course.

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