Solve a simple portfolio optimization problem
This first exercise will teach you how to solve a simple portfolio optimization problem using PortfolioAnalytics. You will learn how to create a portfolio specification object, add constraints and objectives, and solve the optimization problem. The portfolio problem is to form a minimum variance portfolio subject to full investment and long only constraints. The objective is to minimize portfolio variance. There are two constraints in this problem: the full investment constraint means that the weights must sum to 1, and the long only constraint means that all weights must be greater than or equal to 0 (i.e. no short positions are allowed).
This exercise is part of the course
Intermediate Portfolio Analysis in R
Exercise instructions
- Create a portfolio specification object using asset names from the
index_returnsdataset and name the portfolio specification objectport_spec. - Add a full investment constraint such that the weights sum to 1 to the
port_specobject. - Add a long only constraint such that the weight of an asset is between 0 and 1 to the
port_specobject. - Add an objective to minimize portfolio standard deviation to the
port_specobject. - Solve the portfolio optimization problem using
optimize_method = "ROI". Assign the results of the optimization to an object namedopt.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create the portfolio specification
port_spec <- portfolio.spec(colnames(___))
# Add a full investment constraint such that the weights sum to 1
port_spec <- add.constraint(portfolio = ___, type = "___")
# Add a long only constraint such that the weight of an asset is between 0 and 1
port_spec <- add.constraint(portfolio = ___, type = "___")
# Add an objective to minimize portfolio standard deviation
port_spec <- add.objective(portfolio = ___, type = "___", name = "___")
# Solve the optimization problem
opt <- optimize.portfolio(___, portfolio = ___, optimize_method = "___")