3.0 Hours; 3.0 Credits This course covers Monte Carlo methods, their convergence properties and variance reduction techniques, tree pricers and Greeks estimators, implied binomial trees and implied volatility trees, numerical integration techniques, and finite difference methods for pricing derivative securities, including their convergence properties. Prerequisite: MTH 9814 and MTH 9821

3.0 Hours; 3.0 Credits This course covers qualitative and quantitative aspects of the financial risk associated to managing financial portfolios and to credit default. Topics include: market risk, Var and stress testing, model risk, spot and forward risk, credit default risk and credit derivatives. Prerequisite: MTH 9814

1.5 Hours; 1.5 Credits This course will cover linear and quadratic optimization as well as other nonlinear techniques. Applications from finance will include problems in game theory and portfolio optimization. Prerequisite: MTH 9814 and MTH 9821

3.0 Hours, 3.0 Credits This course will cover probability and statistics from a Bayesian perspective, with applications to finance. Topics will include joint marginal and conditional probability; discrete and continuous random variables; Bayesian inferences for means and proportions compared with the corresponding frequentist ones; simple linear regression model analyzed in a Bayesian manner; and a [...]

3.0 Hours; 3.0 Credits Each student will be required to prepare a case study motivated by a real-world problem in finance whose solution requires the application of mathematical techniques presented in this program. The student's analysis and conclusions will be presented to faculty and students. Prerequisite: MTH 9852, MTH 9862. Corequisite: MTH 9871.

3.0 Hours; 3.0 Credits Finite difference methods are discussed and implemented for valuating derivative securities such as plain vanilla European and American options, Bermudan options and barrier options. Numerical linear algebra methods used for finite difference solvers, including LU and Cholesky decompositions and iterative (Jacobi, Gauss-Siedel, SOR, and PSOR) methods are also implemented. Prerequisite: None

3.0 Hours; 3.0 Credits This course involves the careful examination of software development techniques for solving problems in finance. Emphasis is placed on productivity and the development of software engineering skills including automation, source control, and API design. The course is aimed at students who have a basic understanding of C++ and quantitative finance. The [...]

The 2015 NSD-Baruch MFE Summer Camp successfully completed at Baruch College on August 17; twenty-six students and alumni of the National School of Development (NSD) at Peking University arrived in New York kicking off the camp in the morning of August 3rd. The students are studying in the double major program in economics in NSD [...]

Tuesday, June 16 Jim - Session 1 The volatility surface: Statistics and dynamics IPython pdf Jim - Session 2 Computationally tractable stochastic volatility models IPython pdf Andrew - Session 1 Interest Rate Options pdf Andrew - Session 2 The SABR model and its myriad flavors pdf Wednesday, June 17 Jim - Session 3 The SVI [...]

The Baruch MFE team won the Fourth Annual International Association of Financial Engineers (IAFE) Academic Student Competition. In a competition of 25 teams from 17 programs, Baruch MFE students researched and wrote a paper on developing a product which can be used to reduce the risk in defined benefit pension plans. The Baruch MFE team [...]