mfin-2012 - Educouturier

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Master in Quantitative Trading & Financial Eng Why a Master in Financial Engineering & Quantitative Finance Fostering innovative investment strategies grounded in rigorous analysis and sound theoretical framework This degree allows students to learn financial models and techniques, to recognize their reach and limitations, and to apply them to complex investment situations. This quantitative program leads to a wide range of financial careers such as trader, risk management officer, hedge funds quant analyst etc. Thanks to small class sizes and individual attention this master is able to ensure a high quality learning process. Students can develop dedicated individualized projects to suit to their ultimate career objectives. The Program at a glance ü ü ü ü Small class sizes ensuring a high quality learning process Very practical orientation to real world strategies combined with rigorous theoretical background Emphasize the development of innovative investment approaches. Students can backtest then manage their strategies on live market data Practical individualized projects allow a tailored path matching career objectives 8 a unique learning & networking experience
Dr. Gregory Gadzinski “ I often hear from prospective students: “They don’t teach you to be a successful trader in a Master program”. My answer is always the following: you could learn how to trade without knowing how to build mathematical models, but the difference between a trader that does not know mathematics and a trader that knows is like the difference between a shaman and a surgeon. Which one do you want to be Now, building financial models is very challenging: not only the mathematics are complex but trading frictions, market imperfections and human nature make sometimes your model lie far from reality. But make no mistake, financial modeling is worthwhile. If we do need models and mathematics – you cannot think about finance and economics without them-, that’s not enough though.“ ineering Program description This program is a mathematically-oriented degree intended for students who aspire to a career where they will apply theoretical finance and computer modeling skills to make pricing, hedging, trading, and portfolio management decisions. Courses and projects emphasize the practical applications of these skills while providing the rigorous theoretical framework essential to a thorough understanding of the principles of financial engineering. Students learn to combine their analytical skills with business sense to handle, analyze, and interpret data, and devise original approaches to complex problems in order to make sound investment or risk management decisions. Courses Analyzing and Trading the Yield and Credit Curves Stochastic Calculus and quantitative strategies Concepts studied Properties and behavior of the yield and credit curves and models such as the Nelson‐Siegel model The basics of asset pricing and other quantitative tools such as Stochastic calculus and the martingale approach Courses Derivative Products and Strategies Statistics & Financial Data Analysis Probability Theory and Discrete-Time Finance Stock and Bond Valuation Portfolio Theory & Management Financial Programming in Visual Basic for Applications Concepts studied The “Plain vanilla” financial derivatives such as options, futures, swaps and the trading strategies that can be implemented such as stock‐index arbitrage, fixed income arbitrage, various options strategies like strangles, and straddles... The use of ordinary least squares (OLS) simple and multiple regression to model relationships amongst financial and economic variables The probability distributions and their properties, the concept of conditional expectation of a random variable, and important limit theorems The equity valuation models (dividend discount and free cash flow models, and P/E ratio valuation), risk and risk measurement, bond prices and yields, the term structure of interest rates, interest rate risk and bond duration and convexity ... Risk Tolerance, Capital Market Line, Mean-Variance Criterion, Efficient Frontier, Single-Index Model, Capital Asset Pricing Model, Fama-French Factors, Active Bond Management Functions and subroutines using different types of variables, conditional statements, loops, and arrays; the procedure of debugging; and how to query an external database Fin. Modeling MATLAB Practitioner’s approach to the implementations of financial models in MATLAB Financial Econometrics AR, MA, and ARMA models and times series models such as the Box‐Jenkins approach www.monaco.edu 9
Page 1 and 2: Masters in Finance A unique learnin
Page 3 and 4: Be part of one of the most unique u
Page 5 and 6: The Common Core Master Specializati
Page 7: Dr. Dino Sola Professor of Finance
Page 11 and 12: Marco Casella, Managing Partner, In
Page 13 and 14: Talal Bessa, MFIN 2009-2010, Junior
Page 15 and 16: Jacek Maslak, MFIN 2008, Financial
Page 17 and 18: Joseph Michael Payte Founding board
Page 19 and 20: Admission Criteria We seek students

mfin-2012 - Educouturier

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