A financial portfolio is almost always modeled as the sum of correlated random variables. The Great Recession and many other financial mishaps can be attributed to poor risk modeling. In this course, you'll explore the many capabilities of the R programming language in relation to risk modeling, factor analysis, numerical optimization, linear regression, and logistic regression. By course's end, you'll have a firm understanding of how to use R to create more accurate models and make smarter financial decisions.
- Access 138 lectures & 15.5 hours of content 24/7
- Model risk using covariance matrices & historical returns
- Understand factor analysis & its link to linear regression
- Discuss principal components, Eigenvalues & Eigen vectors
- Apply PCA to explain the returns of a technology stock like Apple
- Explore the classic linear programming problem setup & the primal and dual problems
- Implement simple & multiple regression in Excel, R, and Python
- Discover applications of logistic regression
Loonycorn is comprised of two individuals—Janani Ravi and Vitthal Srinivasan—who have honed their respective tech expertise at Google and Flipkart. The duo graduated from Stanford University and believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.