Can someone kindly explain Black Litterman model? 照片

bchadwick

So in a mean-variance optimization, to create the efficient frontier you have all these assets and you input all their risk and return characteristics into the model. I think that includes standard deviation, covariances, and returns. Then you weight them differently and create the frontier.

The BL model is the opposite of this, in order to overcome the weakness of having to come up with sensitive estimates of risk and return characteristics. So you take the weights of the assets in a global index and its covariances, then solve for the return. How do you get the return from those inputs?

Thanks