Financial Data Modeling & Analysis in R (CFRM 542)

collapse

Course Details

  • Location: Online
  • Duration: 10 weeks
  • Class Times: Days
  • Cost : $3,780

Next Start Date:

January 4, 2017

This course is part of a certificate program. You can also take it without enrolling in the program.

Get Details & Apply

About this Course


This course is an in-depth hands-on introduction to the R statistical programming language for computational finance. The course will focus on R code and code writing, R packages, and R software development for statistical analysis of financial data.

Topics include:

  • The R language – syntax, data types, resources, packages and history, graphics, visualization
  • Graphics in R – plotting and visualization
  • Statistical analysis of returns – fat-tailed skewed distributions, outliers, serial correlation
  • Financial time series modeling – covariance matrices, AR, VecAR
  • Factor models – linear regression, LS and robust fits, test statistics, model selection
  • Multidimensional models – principal components, clustering, classification
  • Optimization methods – QP, LP, general nonlinear
  • Portfolio optimization – mean-variance optimization, out-of-sample back testing
  • Bootstrap methods – non-parametric, parametric, confidence intervals, tests
  • Portfolio analytics – performance and risk measures, style analysis

Prerequisites: R Programming for Quantitative Finance (CFRM 463) or prior programming experience in R, or experience in a modern programming language (C family, Java, Python).

Learning Formats

Online

Courses are offered 100 percent online. The flexible online format allows you to access course content wherever you are, on your own schedule. You simply need to complete assignments by their due dates. Video lectures, assignments and other course materials are delivered through a Web-based learning management system, such as Canvas or Moodle, which also serves as a hub for communicating with your instructors and classmates. You can stream video lectures as they are delivered live or view recordings at a later time.

Blended

Our special blended programs combine the convenience of online study with the vibrancy of in-person classes for a unique learning experience.

Not available for this course

Classroom

Attend class in person at one of our convenient locations. You’ll engage face to face with your classmates and instructors as part of a highly interactive curriculum. An online learning management system may be required to access some course materials and assignments.

Not available for this course

Start Dates

Online

Meet your instructors

Guy Yollin

Principal Consultant, www.R-Programming.org 

College Credit

This course may earn you 4.0 college credits - what's this?