Course Sequence Advice for Part-Time Students


The following table is intended to help each student plan a course sequence that is consistent with all prerequisites.  First, we list the Mathematics in Finance courses, indicating their dependencies.  Then we offer two examples of feasile course sequences.

Required Courses (Total 6 Courses + Project & Presentation)

 

Courses Offered Fall Semester

Coursed Offered Spring Semester

Core Level 1

  1. Derivative Securities
  2. Risk and Portfolio Mgmt with Econometrics
  3. Stochastic Calculus
  4.  Computing in Finance
  1. Derivative Securities
  2. Risk and Portfolio Mgmt with Econometrics
  3. Stochastic Calculus

Core Level 2

  1. Scientific Computing (4)
  2. Continuous Time Finance (1,3)
  3. Project & Presentation
  1. Scientific Computing for Finance (4)
  2. Continuous Time Finance (1,3)
  3. Project & Presentation

 

Electives (Choose 5 Courses)

Courses Offered Fall Semester

Courses Offered Spring Semester

  1. Time Series Analysis & Statistical Arbitrage (1, 3, 4, 5)
  2. Advance Econometrics Modeling and Big Data (1, 2, 4)
  3. Nonlinear Problems in Finance: Models and Computational Methods (6)
  4. Data Science in Quantitative Finance (2, 4, 5)
  5. Regulation and Regulatory Risk Models(1, 2)
  6. Fixed Income Derivatives: Models & Strategies in Practice (1, 4)
  7. Credit Anayltics: Bonds, Loans, and Derviatves (1, 4)
  1. Active Protfolio Management (4)
  2. Interest Rate & Fx Models (1, 3, 4)
  3. Advanced Risk Management (1, 4)
  4. Algorithmic Trading & Quantitative Strategies (2, 4)
  5. (1, 3, 4)
  6. Market Microstructure (2, 4)
  7. Secruritized Products & Structured Finance (1,3)
  8. Engergy Markets & Derivatives (1, 3)

 

SAMPLE COURSE SEQUENCES (ASSUMING A FALL START)

The sequence omits Computing in Finance

 

The sequence omits Risk & Portfolio Management w/ Econometrics

(Fall) Derivative Securities & Stochastic Calculus

 

(Fall) Derivative Securities & Computing in Finance

(Spring) Risk & Portfolio Management w/ Econometrics & Scientific Computing in Finance

 

(Spring) Scientific Computing in Finance & Stochastic Calculus

(Fall) Continuous Time Finance & Credit Markets & Models

 

(Fall) Continuous Time Finance & Time Series Analysis & Statistical Arbitrage

(Spring) Advanced Risk Management & Interest Rate & Fx Models

 

(Spring) Interest Rate & Fx Models & Advanced Risk Management

(Fall) Computational Methods for Finance & Times Series Analysis & Statistical Arbitrage

 

(Fall) Regulation & Regulatory Risk Models & Advanced Econometrics Modeling & Big Data

(Spring) Advance Risk Management & Project & Presentation

 

(Spring) Algorithmic Trading & Quantitative Strategies & Project & Presentation