for helpful comments. We thank the editor, Richard Green, and two anonymous referees, for a number of suggestions that have helped us sharpen the focus of the article. We are responsible for any errors or omissions. The views expressed herein are those of the authors and not necessarily those of the National Bureau of Economic Research.

Green and Holli¢eld (1992) argue that the presence of a dominant factor would result in extreme negative weights in mean-variance e⁄cient portfolios even in the absence of estimation errors. In that case, imposing no-short-sale constraints should hurt, whereas empirical evidence is often to the contrary. We reconcile this apparent contradiction. We explain why constraining portfolio weights to be nonnegative can reduce the risk in estimated optimal portfolios even when the constraints are wrong. Surprisingly, with no-short-sale constraints in place, the sample covariance matrix performs as well as covariance matrix estimates based on factor models, shrinkage estimators, and daily data. MARKOWITZ'S (1952MARKOWITZ'S ( , 1959 PORTFOLIO THEORY is one of the most important theoretical developments in ¢nance. Mean-variance e⁄cient portfolios play an important role in this theory. Such portfolios constructed using sample moments often involve large negative weights in a number of assets. Since negative portfolio weights (short positions) are di⁄cult to implement in practice, most investors impose the constraint that portfolio weights should be nonnegative when constructing mean-variance e⁄cient portfolios. Green and Holli¢eld (1992) argue that because a single factor dominates the covariance structure, it would be di⁄cult to dismiss the observed extreme negative and positive weights as being entirely due to the imprecise estimation of the inputs.They consider the global minimum variance portfolio to avoid the e¡ect of estimation error in the mean on portfolio weights. They note that when returns are generated by a single factor model, minimum variance portfolios can be constructed in two steps. First, naively diversify over the set of high beta stocks and

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Unlike the NYSE, the Toronto Stock Exchange (TSX) does not adjust prices in the outstanding limit orders on ex‐dividend days. We find that TSX ex‐day stock price behavior differs from that on the NYSE in several key aspects. In each case, the TSX ex‐day behavior is consistent with the lack of a limit order adjustment mechanism. Our findings confirm that market microstructure is an important factor that contributes to the observed Canadian ex‐day price behavior. Our findings also resolve the puzzle of the relatively small ex‐day price drop in Canada.