Computational finance with R course: an interactive tutorial
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
As of today (Tuesday 26th of August), a new session of Professor Eric Zivot’s course on computational finance and financial econometrics starts on Coursera. Just like the previous run of the course, most R labs and R assignments will take place in DataCamp’s interactive learning environment. It’s a great course to get you started in doing finance with R.Designed by Professor Eric Zivot (University of Washington), Introduction to computational finance focuses on mathematical and statistical tools and techniques that are used in quantitative and computational finance. With the help of real-life examples, you will be introduced to the dos and don’ts of financial data analysis, estimations of statistical models, the construction of optimized portfolios, and doing finance with R. The course requires no formal background, but some basic mathematical skills will definitely come in handy.DataCamp’s interactive R exercises are developed in close collaboration with Professor Zivot himself. They therefore have the same high-quality standards as academic courses, but presented in DataCamp’s fun and learning-by-doing environment. All students that choose to enroll for the course on Coursera will be directed to DataCamp to practice their skills and to complete assignments.If you always wanted to learn more about computational finance, or if you are just interested in doing financial econometrics with R, this course is a must-do for sure. We hope to welcome you in our online classroom soon!PS. In case you prefer to only do the interactive exercises, the course is also available on DataCamp as a stand-alone version, which does require prior knowledge about finance,R or finance with R.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.