Compute benchmark returns
In this exercise, we will create a benchmark to evaluate the performance of the optimization models in later exercises. An equal weight benchmark is a simple weighting scheme to construct the benchmark portfolio. The intuition of an equal weight approach is that there is no preference for any given asset. We are setting this up to answer the question, "Can optimization outperform a simple weighting scheme to construct a portfolio?"
Este ejercicio forma parte del curso
Intermediate Portfolio Analysis in R
Instrucciones del ejercicio
- Load the
PortfolioAnalyticspackage. - Load the edhec dataset.
- Assign the edhec dataset to a variable named
asset_returns. - Create a vector of equal weights assigned to a variable named
equal_weights. - Compute an equal weight benchmark, rebalanced quarterly, of
asset_returns. - Plot the benchmark returns.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# Load the package
# Load the data
# Assign the data to a variable
# Create a vector of equal weights
equal_weights <- rep(1 / ncol(___), ncol(___))
# Compute the benchmark returns
r_benchmark <- Return.portfolio(R = ___, weights = ___, rebalance_on = ___)
colnames(r_benchmark) <- "benchmark"
# Plot the benchmark returns