Baruch College’s Masters of Financial Engineering (MFE) team won the sixth annual International Association for Quantitative Finance (IAQF) competition, in a three-way tie at the top. The competition featured 25 teams from 19 MFE programs. This victory marks the third consecutive year the Baruch MFE Program has won the IAQF and adds to what has [...]
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The Baruch College’s Master of Financial Engineering Program won First Place (out of 52 teams) at the 14th Rotman International Trading Competition held in February 2017 in Toronto. This is our second win in a row after the record-breaking win from 2016, and the third win all-time, after winning RITC 2012. The performance of the [...]
The Baruch MFE team won the 5th IAQF Student Competition, the second year in a row our students win the competition. In a competition of 27 teams from 17 programs, our students worked on estimating industry sensitivities to oil prices and the effectiveness of hedges of oil price risks. Teams from UC Berkeley and University [...]
The Baruch College’s Master of Financial Engineering (MFE) program won 1th place (out of 52 teams) at 13th Rotman International Trading Competition held in February 2016 in Toronto. This was a record-breaking year and a unique win in the history of the competition: - we won three of the six events (commodities trading, credit risk, [...]
Our Baruch MFE student Song Wang (Baruch MFE December'16) won the Solve-a-thon at MIT trading competition organized by WorldQuant and a cash prize of $10,000 for achieving a score of over 100,000 (calculated based on alpha generation) in less than two months. Out of over 700 participants, the next highest score was 55,000, and only [...]
1.5 Hours; 1.5 Credits This course covers various filtering techniques such as Kalman filter, particle filtering,and chaos based filtering. Applications include estimation of stochastic volatility parameters from timeseries of underlying asset prices and the use of stochastic volatility in derivative pricing. It also compares the cross-sectional and time-series based estimated parameters and applies the results [...]
3.0 Hours; 3.0 Credits This course covers the basic stochastic processes and probabilistic techniques used in finance, for example: random walks, Markov chains, martingales, Brownian Motion, stochastic integration, and Ito's formula. The Black-Scoles formula is presented from the standpoint of expectation in an appropriate probability space. Prerequisite: MTH 9814 and MTH 9831
3.0 Hours; 3.0 Credits The course introduces the quantitative techniques and models commonly used in the asset management industry. The emphasis is on practical aspects of modeling, and specific techniques for portfolio construction and risk management. Topics include classic subjects such as Markowitz’s mean-variance optimization, CAPM and APT models, the Black- Litterman model, as well [...]
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