Optimization models play an increasingly important role in financial decisions. This course introduces the student to financial optimization models and methods. We will specifically discuss linear, integer, quadratic, and general nonlinear programming. If time permits, we will also cover dynamic and stochastic programming. The main theoretical features of these optimization methods will be studied as well as a variety of algorithms used in practice.
Course prerequisites: 
Multivariate calculus and linear algebra.
Course notes: 
Due to overlap in much of the subject matter in 625.415 and 625.416, a student may not receive credit towards the MS or Post-Master's Certificate for both 625.415 and 625.416.
Course instructor: 
Castello

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Course all programs: 
Applied and Computational Mathematics
Data Science
Financial Mathematics