Out of sample performance evaluation

This example will illustrate how your returns can change based on the weighting created by an optimized portfolio. You will use the estimation portfolio (pf_estim) to evaluate the performance of your portfolio on the estimation sample of returns (returns_eval).

How severe is the optimality loss? Let's compare, for the portfolio weights in pf_estim, the performance you expected using the evaluation sample (returns_estim) with the actual return on the out-of-sample period (returns_eval).

pf_estim, returns_estim, and returns_eval are pre-loaded in your workspace.

This exercise is part of the course

Introduction to Portfolio Analysis in R

View Course

Exercise instructions

Calculate the returns of the portfolio with monthly rebalance weights pf_estim$pw on the estimation sample returns_estim. Call this returns_pf_estim.
Calculate the returns of the portfolio with monthly rebalance weights pf_estim$pw on the evaluation sample returns_eval. Call this returns_pf_eval.
Use the function table.AnnualizedReturns() on returns_pf_estim.
Use the function table.AnnualizedReturns() on returns_pf_eval. Compare the return, risk, and Sharpe ratio of these portfolios. The results from the pf_eval are what you may expect in a real performance.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Create returns_pf_estim
returns_pf_estim <- Return.portfolio(___, pf_estim$pw, rebalance_on = "months")


# Create returns_pf_eval


# Print a table for your estimation portfolio


# Print a table for your evaluation portfolio

Edit and Run Code