MATH 8204: Computational Methods for Asset Pricing

University of North Carolina, Charlotte

Discusses and implements pricing methods for numerous derivatives under a variety of models. It reviews common processes for modeling assets in different markets and then examines many computational approaches for pricing derivatives. These include transform techniques, such as the fast Fourier transform, the fractional fast Fourier transform, the Fourier-cosine method, and the saddle-point method; the finite difference method for solving partial differential equations (PDEs); and Monte Carlo simulation. Model calibration for real-world derivative pricing is also discussed.

Average GPA: 3.86

Grade distribution records: 28 students across 9 terms.

Grade distribution

Based on 28 student grade records across 9 terms and 1 professor.

Instructors

• Hwan-Chyang Lin 28 students, Average GPA 3.86