R Tutorial : Intermediate Portfolio Analysis in R

Want to learn more? Take the full course at https://learn.datacamp.com/courses/intermediate-portfolio-analysis-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- Hi, I am Ross Bennett. I am an analyst on a trading desk at a proprietary trading firm in Chicago. I am the co-author of PortfolioAnalytics and contribute to several other R packages used in finance. This course will build on the fundamental concepts from the Introduction to Portfolio Analysis in R course. We will explore more advanced concepts in the portfolio optimization process such as complex constraint and objective sets, methods for estimating moments, optimization with periodic rebalancing (also referred to as backtesting), and visualizations to better understand the optimization problem. The focus of the course is to use the PortfolioAnalytics package to solve portfolio optimization problems that mirror real-world applications. Although Modern Portfolio Theory was introduced over 60 years ago, it establishes a framework for defining and evaluating objectives. In the Modern Portfolio Theory framework, the optimal portfolio for an investor to hold is the portfolio that maximizes portfolio expected return for a given level of risk. The academic approach follows the Markowitz approach using mean return as a measure of gain and standard deviation of returns as a measure of risk. However, most real-world problems consider different measures of risk as well as multiple objectives and constraints. In this course, you will explore both the standard Markowitz approach and more complex problems similar to what you will encounter in industry. Let's begin with an example to demonstrate how you can use PortfolioAnalytics to solve a portfolio problem using the Modern Portfolio Theory framework to maximize mean return and minimize standard deviation. You start with loading the PortfolioAnalytics library and a sample dataset. In the example in t