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...

Our objective in this paper is to examine whether one can use option-implied information to improve the selection of mean-variance portfolios with a large number of stocks, and to document which aspects of option-implied information are most useful for improving their out-of-sample performance....

Computing the optimal portfolio policy of an investor facing capital gains tax is a challenging problem: because the tax to be paid depends on the price at which the security was purchased (the tax basis), the optimal policy is path dependent and the size of the problem grows exponentially with...

We investigate how transaction costs change the number of characteristics that are jointly significant for an investor's optimal portfolio, and hence, how they change the dimension of the cross section of stock returns. We find that transaction costs increase the number of significant...

A fundamental insight in finance is that there is a strong risk-return tradeoff. Moreira and Muir (2017) challenge this by showing that investors can increase Sharpe ratios by reducing exposure to risk factors when their volatility is high. However, Cederburg, O'Doherty, Wang, and Yan (2020)...

The growing number of institutions exploiting factor-investing strategies raises concerns that crowding may increase price-impact costs and erode profits. We identify a mechanism that alleviates crowding--trading diversification: institutions exploiting different characteristics can reduce each...

We study whether investors can exploit serial dependence in stock returns to improve out-of-sample portfolio performance. We show that a vector-autoregressive (VAR) model captures stock return serial dependence in a statistically significant manner. Analytically, we demonstrate that, unlike...

In this paper, we extend the mean-variance portfolio model where expected returns are obtained using maximum likelihood estimation to explicitly account for uncertainty about the estimated expected returns. In contrast to the Bayesian approach to estimation error, where there is only a single...