看来哥们经济学没学好啊

哥们经济学好好学了，本帖用于对敲，自买自卖，之前的一个账号被禁止发言了。是账号被盗，找回密码还不让发言，只要注册新号，把论坛币倒出来。呵呵。。。
好不容易想到这招，不会又被封了吧。按照论坛的规定，我不违法的。

没钱就别买

这个价格，就这样，不讲价，讲价也不便宜

Course Descriptions
Advanced Derivative Modeling 46-915
This course considers more advanced models. We start by revisiting the Fourier transform and discuss how to use this technique to price vanilla options in different standard vol models (Heston and Stein & Stein). We then study the theory of jump processes including Ito's lemma and Girsanov's theorem. We first focus on the Poisson process and the compounded Poisson. We then explain how to create the family of Cox-processes, which plays an important role in the credit derivatives' literature. Subsequently, we apply this theory to build asset pricing models, such as Bates' model (this is basically Heston's model with jumps added). We will not follow a textbook but one useful reference is: J. Gatheral, The Volatility Surface: A Practitioner's Guide, Wiley, 2006. Prerequisites: Stochastic Calculus for Finance II 46-945, Simulation Methods for Option Pricing 46-932.

Credit Derivatives 45-985
This course is a quantitative introduction to credit derivatives and to the modeling, valuation, and hedging of credit risk. Its goals are to provide students with an advanced training in the methods and techniques of credit risk management. It is designed to help you acquire an extensive skill set for modeling and predicting correlated default arrivals and changes in credit quality that allows you to price baskets of credit-sensitive securities. Prerequisites Stochastic Calculus (46-944 and 46-945) and Simulation Methods for Options Pricing (46-932).

Deutsche MSCF Trading Competition 46-980
All first-year full and part-time students participate in a trading competition directed and underwritten by Deutsche Bank. Using equity and fixed income derivatives securities on a paper trading platform through Interactive Brokers, individuals trade and make markets during specified open market hours. Results of the competition are tallied and posted with the winners determined relative to the performance measurements specified in the trading cases. The top ten winners are recognized, with the top three winners awarded cash prizes (1st: $1,000; 2nd: $500; 3rd: $250). The winners will be honored in the company of all participants and members of the MSCF Steering Committee at a reception hosted by Deutsche Bank in New York on January 11, 2012.

Financial Computing I 46-901
This will be a "Survival Computing" course for MSCF students. We will cover the basics of C++, in the context of some elementary finance-related problems. The intent is to arm you with computing skills you can use in other MSCF courses, including Financial Computing II, III and IV. Reference texts (not required): "C++ Primer" by Lippman, et al, "Numerical Recipes in C++" by Press, et al. Prerequisite: Some experience in programming in a procedural or object-oriented language, or the Programming Prep course.

Financial Computing II 46-902
Throughout this course, we will be building a non-toy C++ application that uses genetic programming. Most of the concepts from the lectures will be used in this application. First, we look more deeply at the C++ standard library. Then some background on relational databases is given, so that the use of a database as a "back-end" to a C++ program will make sense. We look at the relational algebra, the relational calculus, and the query language SQL. Then we cover the construction of static and dynamically linked libraries. A few topics from Windows programming are briefly covered, and finally the idea of design patterns as object-oriented "building blocks" is discussed. Reference texts (not required): "C++ Primer" by Lippman, et al, "Database Modeling and Design" by Teorey, "The C++ Standard Library" by Josuttis and "Design Patterns" by Gamma, et al. (the "Gang of Four"), plus additional material available from the course Web site. Prerequisite: Financial Computing I 46-901.

Financial Computing III 46-903
This is a course in advanced O-O and C++ topics. We look at memory management, including overriding the new and delete operators, program design for other kinds of resource allocation, exception-safe code, profiling and optimizations, and other O-O topics as time permits. Also, we will consider additional ways of coupling Excel, VBA and C++, and the construction of Excel "add-ins". Several Excel/VBA/C++ projects will be assigned, as well as a "coding competition" amongst teams of students. Reference texts (not required): "Effective C++" by Meyers, "C++ Common Knowledge" by Dewhurst, and "The C++ Standard Library" by Josuttis. Prerequisite: Financial Computing I 46-901, Financial Computing II 46-902.

Financial Computing IV 46-904
The goal of this course is to refresh and expand your knowledge of several important topics of the Master Program, such as Object Oriented Programming with C++, theory of pricing and hedging of derivative securities, numerical analysis and stochastic calculus. The course is organized around a project of design and implementation of a powerful C++ library for pricing of derivative securities. You will learn important principles of implementation of financial models and master algorithms of evaluation of different types of derivative securities: European, American, standard, barrier and path dependent options on stocks and interest rates. Prerequisite: Stochastic Calculus II, Financial Computing III 46-903.

Financial Economics for Computational Finance 45-887
The first half of the course connects arbitrage-free pricing models with economic models of risk and return to evaluate proprietary portfolios (data from hedge fund returns) and the extent to which cross-sections of asset returns are consistent with arbitrage-free economics and predicted equilibrium risk/return relationships. The second half of the course looks at the role of the banks in financial intermediation, market making, securitization, and bankruptcy restructuring. The course will be focused mostly on assignments with data or case-studies. Prerequisite: Intro to MSCF Finance 45-785, Options 45-885, Macroeconomics for Computational Finance 45-905, Multi-Period Asset Pricing 46-941, Financial Time Series Analysis 46-929, Statistical Arbitrage 46-936.

Financial Optimization 45-988
This course covers quantitative techniques that are used in investment management. The essential elements of a quantitative investment management process include a model of risk and return, portfolio construction tools that find optimal trade-offs between risk and return, strategies for portfolio rebalancing and trading, and some attribution mechanism to measure performance. The course will place special emphasis on techniques for portfolio construction and trade execution. The first half of the course will deal with static models. These include conventional active management based on mean-variance optimization as well as modern techniques such as resampled efficiency, Bayesian approaches, robust optimization, and scenario optimization. The second half of the course will be devoted to dynamic models. These include optimal execution strategies, dynamic consumption and investment, and portfolio choice in the presence of taxes. Representative Texts: Grinold and Kahn, "Active Portfolio Management." Cornuejols and Tutuncu, "Optimization Methods in Finance." Campbell and Viceira, "Strategic Asset Allocation: Portfolio Choice for Long-Term Investors." Prerequisites: Intro to MSCF Finance 45-785, Stochastic Calculus II 46-945.