MATH 6204: Modern Computational Methods for Finance
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: 3.76
Grade distribution records: 77 students across 10 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 57 | 74.0% |
| B | 18 | 23.4% |
| W | 1 | 1.3% |
Based on 77 student grade records across 10 terms and 1 professor.
Instructors
- Hwan-Chyang Lin 77 students, Average GPA 3.76