In this paper, we wish to evaluate the performance of simple asset-allocation strategies such as allocating 1/N to each of the N assets available. To do this, we compare the out-of-sample performance of such simple allocation rules to about ten models of optimal asset-allocation (including both...

In this paper, we evaluate the out-of-sample performance of the portfolio policy from the sample-based mean-variance portfolio model and the various extensions of this model, designed to reduce the impact of estimation error relative to the benchmark strategy of investing a fraction 1/N of...

We evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1/N portfolio. Of the 14 models we evaluate across seven empirical datasets, none is consistently better than the 1/N rule in terms of...

In this paper, we compare the out-of-sample performance of the rule allocating 1/N to each of the N available assets to several static and dynamic models of optimal asset-allocation for ten datasets. We devote particular attention to models the literature has proposed to account for estimation...

We evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1-N portfolio. Of the 14 models we evaluate across seven empirical datasets, none is consistently better than the 1-N rule in terms of...

We provide a general framework for finding portfolios that perform well out-of-sample in the presence of estimation error. This framework relies on solving the traditional minimum-variance problem but subject to the additional constraint that the norm of the portfolio-weight vector be smaller...

In this paper we develop a model of intertemporal portfolio choice where an investor accounts explicitly for the possibility of model misspecification. This work is motivated by the difficulty in estimating precisely the probability law for asset returns. Our contribution is to develop a...