Mean-variance theory with imprecise accounting information

In this paper, we examine the impact of imprecise accounting information on optimal portfolio choice in the mean-variance sense. We provide a theoretical platform illustrating the exact way in which imprecise return errors affect portfolio choice and alter the optimal vector of weights. We demonstrate that the covariance between actual return and return error could partly offset the impact of low-quality information on variance-covariance matrix. This is in agreement with empirical evidence suggesting that optimal portfolio weights are highly sensitive to small estimation errors in expected returns, but they are less sensitive with respect to errors in return variance estimates.