Mathematical Methods for Quantitative Finance Learn more

What is Quantitative Finance?
Quantitative finance has become a very hot field over the past few years. It is a discipline in which mathematical models are used to make huge investment decisions and assess their accuracy. Quantitative Finance can be related to economics in a number of ways, but in former the work is done more from an applied perspective. Past few years have seen businesses investing millions of dollars to develop these models in a bid to improve their trading record. However, the mathematical models used by different investment firms showed varied results, since none of the models have been able to use all variables. Nevertheless, the discipline seems to become even more widespread in the years to come.
Who should take this course?
People owning an investment firm or working for one such company are the prospective candidates to take this course. Even if you are not linked to any such firm but are interested in learning the new mathematical models for quantitative finance, enroll yourself for this course. However, make sure you have completed entry-level college calculus courses, since the mathematical models discussed in this course are mostly from multivariable differential calculus.
What are the benefits of this course?
Upon completion of the course the participants will have learnt the fundamental mathematical concepts required to effectively study key areas of quantitative finance, including fixed income, quantitative risk management and portfolio optimization.
Table of Contents:
- Functions and inverse functions
- Limits, derivatives, partial derivatives, and chain rule
- Integrals and multiple integrals, changing the order of differentiation and integration
- Taylor series approximations
- Newton’s method
- Lagrange multiplier method
- Vector and matrix arithmetic, determinants, eigenvalue-eigenvector decomposition, singular value decomposition
- Numerical methods for optimization
Author Bio:
This course has been prepared by Dr. Kjell Konis, Acting Assistant Professor in the Department of Applied Mathematics at the University of Washington.

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