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Academic resources for my colleagues and students

STAT 449/649, Quantitative Financial Risk Management (QFRM)

Stat 449 & Stat 649 (Quantitative Financial Risk Management) is offered in Spring 2014, taught by Oleg Melnikov, graduate student in PhD statistics program at Rice University’s Department of Statistics.

This is an excellent course (offered each Spring semester) for students seeking to complete their requirements, having heightened interests in financial derivatives (and related mathematical concepts), and those who will be looking for job opportunities with financial firms and would like to sharpen their lingo and understanding of theoretical and real-world finance.

Note: this is a challenging and yet highly desirable course. Please make sure you are well prepared to take it and have completed the pre-requisites below. The course will demand plenty of sincere effort, and, I hope, will eventually turn into a solid asset on your CVs.

Pre-requisites for 649: STAT 431 (Math Stat) or STAT 615 (Regression & Stat Computing)

Pre-requisities for 449:

  1. MATH 211 (ODE & Linear Algebra)
  2. MATH 212 (Multivariate Calculus)
  3. One of these: 
    1. ECON 400 (Econometrics)
    2. STAT 410 (Regression & Stat Computing)
    3. Check with Econ Dept (and/or registrar) if ECON 409 (Econometrics) and ECON 400 are equivalent
  4. One of these: 
    1. STAT 310 (Probability & Statistics)
    2. ECON 307 (Prob & Stat)
    3. STAT 312 (Prob & Stat)
    4. STAT 331 (Applies Prob)
  5. Recommended:
    1. General (basic) knowledge of finance (financial markets, stocks, bonds, derivatives, indices, portfolios, risks, etc.),
    2. Programming skills (we’ll be using R)
    3. If you are eager to get started and have extra time this winter break, you can begin to review the key concepts from pre-requisite coursework and advance your R programming skills, which is one of the key tools in Finance (besides Matlab, Python, C/C++, and, of course, Excel).
      1. Depending on your skills, you can use R Studio as the IDE for R, try various financial R packages, compute/approximate integrals and gradients in R, try out option pricing models, try out portfolio risk/return models. We’ll do more of it in class, but this will give you flavor of the course and valuable skills/preparation.

There is likely a quiz and HW in the first week of the course to help students gauge their preparedness for this course. Winter break is a good time to review the pre-requisite material and start reading John C. Hull’s textbook “Options, Futures, and Other Derivatives” 8th edition (we will not be using DerivaGem software, but will be heavily utilizing R). It has 30+ chapters and we’ll be moving quickly 🙂