Can I say the major difference is Black-Litterman allowing to incorporate investor’s view?

According to Reading 18 Asset Allocation of the CFAI text (pages 230-238), resampled efficient frontier and the Black-Litterman approach are both offered as two alternatives to mean-variance optimization for the purposes of asset allocation.

Resampled efficient frontier involves running a **series of simulations** (based on **sample values of asset class means, variances, and covariances** ) and mean-variance optimization is used to obtain portfolio weights for a number of efficient portfolios. **Average weights** are then found for each asset class in the simulated efficient portfolios. This information, along with other information from the simulated efficient portfolios, is then **integrated into a single frontier known as the resampled efficient frontier**.

The Black-Litterman approach is a quantitative approach, similar to the resampled efficient frontier, but this appoach improves upon mean-variance optimization by **combining an investor’s own views on expected returns with a set of expected asset-class returns** to determine an asset allocation strategy.

Additionally, I found a linkto a prior post in this forum that has a good explanation of the difference between the two approaches. The comment by ‘janakisri’ within the post is the most helpful, in my opinion.

Hope this helps!

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