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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.

Cet exercice fait partie du cours

Introduction to Portfolio Analysis in R

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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.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de 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
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