We could account for this by treating mean return and standard deviation as distributions rather than point estimates, and calculating utility-maximizing leverage across the distribution instead of at a single point. This raises a further concern that we don’t even know what distribution the mean and standard deviation have, but at least this gets us closer to an accurate model.
Why not just take the actual mean and standard deviation, averaging across the whole distribution of models?
What exactly is the “mean” you are quoting, if it’s not your subjective expectation of returns?
(Also, I think the costs of choosing leverage wrong are pretty symmetric.)
Why not just take the actual mean and standard deviation, averaging across the whole distribution of models?
What exactly is the “mean” you are quoting, if it’s not your subjective expectation of returns?
(Also, I think the costs of choosing leverage wrong are pretty symmetric.)