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HOME > MSFinEng > Program

金融工学のプログラム

合格実績 受講生 出願条件 受験テスト
ランキング プログラムとカリキュラム 就職・転職
出願書類 オンライン出願 成績証明書 履歴書
Statement/Essay 推薦状 出願と受験  

 

プログラムとカリキュラム

 

     前述の合格校やランキングのスクールから判るように、金融工学プログラム はビジネス・スクールが開講していたり、 数学科だったり、工学スクールだったり、それぞれ特徴があります。どのスクールが具体的にどんなプログラムやカリキュラムを見てみましょう。

 

Business Schoolが開講している金融工学プログラム

Carnegie Mellon U., Tepper School of Business, MS in Computational Finance, 1.5 years icon

The Master in Computational Finance program (MSCF) at Carnegie Mellon offers a full-time computational finance graduate degree available in both Pittsburgh, PA and New York, NY. We have approximately forty, full-time students in the Pittsburgh program, and approximately thirty-five, full-time students in the New York program. The degree is a sixteen month, three-semester course of study.

Graduation Requiremens: 150 units (すべて外部リンクです)

First Year
Mini Course # Course Title Units
Mini 1 46-901 Financial Computing I 6
  46-956 Fixed Income 6
  45-785 MSCF Finance 6
  45-789 Presentations for computational Finance 6
  46-921 Probability 6
Mini 2 46-902 Financial Computing II 6
  46-980 MSCF Deutsche Trading Competition 0
  46-941 Multi-Period Asset Pricing 6
  45-885 Options 6
  46-923 Statistical Inference 6
Mini 3 45-987 Financial Products and Markets 6
  45-986 Macroeconomics for Computational Finance 6
  46-926 Statistical and Machine Learning Methods for Financial Data 6
  46-944 Stochastic Calculus I 6
Mini 4 46-929 Financial Time Series Analysis 6
  46-903 Financial Computing III 6
  46-932 Simulation Methods for Option Pricing 6
  46-945 Stochastic Calculus II 6
Second Year
Mini 1 45-988 Financial Optimization 6
  46-950 Numerical Methods 6
  46-936 Statistical Arbitrage 6
  45-886 Studies in Financial Engineering 6
Mini 2 46-915? Advanced Derivative Modeling* 6
  45-985 Credit Derivatives* 6
  46-904 Financial Computing IV* 6
  45-887 Financial Economics for Computational Finance* 6
  46-955 Topics in Quantitative Finance* 6

* Choose four of five

 

 

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数学科が開講している金融工学プログラム

Columbia U., Department of Mathmatics, MA in Mathematics of Finance, 1 year icon

 

First Semester, Fall:

1.Mathematics W4071 INTRODUCTION TO THE MATHEMATICS OF FINANCE

2.Statistics G6503 STAT INF/TIME-SERIES MODELLING

3.Statistics W6501/G6501 STOCHASTIC PROCESSES

4.Statistics W4315 LINEAR REGRESSION MODELS

Students are advised to take W4315 Linear regression models. However advanced students who are familiar with linear regression models they may request to substitute Linear Regression with a course in Mathematics, Statistics, Applied Mathematics, Engineering and Computer Science with code 4000 and higher, except research seminars. The replacement must be approved by director of the program. For Example:

Math G4073 SEMINAR IN QUANT MTHDS IN INVESTMENT MGMT

Math G4075 MATHEMATICAL METHODS IN FINANCIAL PRICE ANALYSIS

5. Elective. Can be Business School course with Business School approval, can be Economics department or SIPA course 4000 and higher, and any Math, Stat, Applied Math, Engineering course with course number 4000 and higher. Research seminars can not count as electives.

Second Semester, Spring:

6.Mathematics G6071 NUMERICAL METHODS IN FINANCE

7.Statistics G6505 STOCHASTIC METHODS IN FINANCE

8.Mathematics G8210 MATHEMATICS OF FINANCE PRACTITIONERS SEMINAR

9. Elective. Can be Business School course with Business School approval, can be Economics department or SIPA course 4000 and higher, and any Mathematics, Stat, Applied Math, Engineering course with course number 4000 and higher. Research seminars can not count as electives.

10. Elective. Same requirements.

 

 

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工学部が開講している金融工学プログラム

Cornell U., School of OR & Info. Eng., Master of Engineering, Financial Eng, 1.5 years icon

The Financial Engineering Concentration (FE) prepares students for careers that involve the quantitative analysis and management of financial instruments and risk. Such jobs frequently involve: (1) mathematical modeling and analysis of stocks, bonds, options, currency exchange rates, and other structured products, (2) developing quantitative models to help corporations understand and manage their exposure to risk, and/or (3) implementing algorithms to monitor, price, and/or trade financial instruments. Unlike other concentrations, FE is specifically designed to be a three-semester program (Fall-Spring-Fall), with the third (i.e., second fall) semester taking place at Cornell Financial Engineering Manhattan in New York City.

Any proposed deviations from the requirements listed below require written permission from the
Director of MEng Studies in the School of ORIE.
Prerequisites
・ Prob & Stat sequence (ENGRD 2700 and ORIE 5500, or equivalent)
・ Stochastic Processes (ORIE 5510 or equivalent, recommended)
・ Computers and Programming (CS 2110)
・ Basic Finance course (online course or self study)*
First Term (fall)
The following courses are required:
・ Derivatives Securities, Part I (1/2 semester course) (NBA 6730)
・ Derivatives Securities, Part II (1/2 semester course) (NBA 6740)
・ Financial Engineering with Stochastic Calculus I (ORIE 5600)
・ Fixed-Income Securities and Interest-Rate Derivatives (NBA 5550)
・ Operations Research I: Optimization I (ORIE 5300)
・ Monte Carlo Simulation (ORIE 5581)
・ Enterprise Engineering Colloquium (ORIE 9100)
Second Term (spring)
The following courses are required:
・ Financial Engineering with Stochastic Calculus II (ORIE 5610) or Credit Risk (ORIE 5620)
or Quantitative Methods of Financial Risk Mgmt. (ORIE 5650)
・ Statistics for Financial Engineering (ORIE 5640)
or Time Series Analysis (ORIE 5550)
・ Topics in Linear Optimization (ORIE 5311) or Optimization II (ORIE 5310)
or Optimization Modeling (ORIE 4300)
・ Monte Carlo Methods in Financial Engineering (ORIE 5582)
・ nvestments and Portfolio Analysis (NBA 5420)
・ Enterprise Engineering Colloquium (ORIE 9100) )
Summer Term
・ Internship
Third Term (fall) at Cornell Financial Engineering Manhattan (CFEM)
The following courses are required:
・ Applied Financial Engr ? Project Course (ORIE 5961)
・ Computational Methods in Finance (ORIE 5630)
・ Seminar in Financial Engineering (ORIE 9160)

 

プログラム の系統によって履修する科目が違うのがよく判ると思います。出願時のPrerequisitesやプログラム 終了後のCareerやカリキュラムの内容などを勘案して出願校を選定します。必要に応じで、一度、無料の出願相談を受けてみたら良いと思います。

 

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