We propose an averaging rule that combines established minimum-variance strategies to minimize the expected out-of-sample variance. Our rule overcomes the problem of selecting the “best” strategy ex-ante and diversifies remaining estimation errors of the single strategies included in the...

Markowitz (1959) mean-variance (MV) portfolio optimization has been the practical standard for asset allocation and equity portfolio management for almost fifty years. However, it is known to be overly sensitive to estimation error in risk-return estimates and have poor out-of-sample performance...

We study implications of unpriced "granular measurement errors" -- idiosyncratic shocks to large firms that aren't well-diversified in market indices -- for asset pricing tests and propose alternative tests insensitive to them. We find stronger evidence of an intertemporal relation between the...

This paper aims to develop a feasible estimator of the Sharpe ratio that the investor would expect from estimated efficient portfolios. Based on the analytical expression of the expected Sharpe ratio, we construct an estimator that captures all the errors involved in the estimated efficient...

The optimized portfolio that is calculated by a covariance matrix has large sensitivities to small eigen values of the covariance matrix. Estimation of sampling errors for small eigen values is quite important for fund managers who construct their portfolios from estimated covariance matrixes....

This study is based on investors' viewpoint and adopts the accruals quality model [1] as proxy variable of earning quality. By applying the process capability concept in engineering application, we establish capability index of basis accrual quality and transform it into the investment risk...