parameter uncertainty, an important component of model risk. Using a robust approach, we introduce a portfolio rule for … portfolio stability, variance and risk-adjusted returns. Empirically, we compare the out-of-sample performance of the robust …

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the …

-diversifiable risk. In the context of normally distributed asset returns, its estimator and finite-sample properties are explored when …

In the present work I derive the risk functions of 5 standard estimators for expected asset returns which are …-variance estimator, and the CAPM estimator. I resolve the question why it is meaningful to study the risk function in the context of … situations it is better to renounce parameter estimation altogether and pursue some trivial strategy such as the totally risk …

In the field of portfolio management, practitioners are focusing increasingly on risk-based portfolios rather than on … mean-variance portfolios. Risk-based portfolios are constructed based solely on covariance matrices, and include methods … such as minimum variance (MV), risk parity (RP), and maximum diversification (MD). It is well known that the performance of …

We investigate the impact of shrinkage estimation techniques for the moments of asset returns on risk-parity portfolios …. In contrast to mean-variance portfolios, the risk contributions of individual assets in risk-parity portfolios are fixed … a priori. This additional restriction stabilizes empirical portfolio weights in time. We show that the marginal risk …

In the present work, I derive the risk functions of 5 standard estimators for expected asset returns which are …-variance estimator, and the CAPM estimator. I resolve the question why it is meaningful to study the risk function in the context of … situations it is better to renounce parameter estimation altogether and pursue some trivial strategy such as the totally risk …

investment’s effectiveness and risk. At first, we give an overview of various methods of bootstrap confidence interval estimation …

of the MV portfolio along with its mean and risk return when the sample covariance matrix is equal to a constant matrix … distributions and examine how such error affects the risk-return tradeoff of the MV portfolios. We show that the negative effects of … error in mean returns on the joint sampling distributions increase with the decision maker's risk tolerance and the number …

investment opportunity set for risk-averse investors. We formulate a new estimation procedure for sparse second-order stochastic … invests in 10 industry sectors and cuts tail risk when compared to a sparse mean-variance portfolio. On a rolling-window basis …