Course Descriptions
Advanced Computational
Finance ( 2 units )
This course builds on the techniques learned in Quantitative
Methods for Derivative Pricing. The focus of the course
is a deeper analysis of numerical and computational issues
in pricing and calibration. The orientation of the course
is hands-on, with heavy use of computational techniques
applied to case projects. Classroom activity will combine
lectures with detailed discussion of case projects. The
primary objective of this course is to prepare students
to tackle the latest challenges in quantitative pricing
that they are likely to encounter in cutting edge financial
institutions. The material presented will familiarize students
with state of the art computational strategies for the calibration
of pricing frameworks, and for the pricing of complex and
multidimensional derivatives. The course will be based on
case projects, representative of real life situations as
encountered in top trading operations in equities and fixed
income. Some of the topics of emphasis will include implying
local volatility functions, understanding the role of stochastic
volatility models, pricing structures with complex embedded
options, and credit derivatives.
NOTE: A minimum grade of A- in the prerequisite course is required to enroll in this elective.
