The Black-Litterman model improves on traditional mean-variance optimization primarily by:
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A
Eliminating the need for an expected return estimate
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B
Combining market equilibrium returns with investor views to reduce estimation error
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C
Requiring only historical return data without subjective inputs
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D
Optimizing only for minimum variance regardless of return expectations