A Practitioner's Guide to Asset Allocation

CHAPTER 7 1/N

FALLACY: EQUALLY WEIGHTED PORTFOLIOS ARE SUPERIOR TO OPTIMIZED PORTFOLIOS

Optimized portfolios are designed to maximize expected return for a chosen level of risk by accounting for differences in expected returns, standard deviations, and correlations. Yet it has been argued that equally weighted portfolios outperform optimized portfolios out of sample. The “1/N” approach to investing assigns asset weights based purely on the number of asset classes, N, and ignores all other information. Those who favor this naïve allocation method believe that estimation error is so insurmountable that incorporating any views about expected return and risk damages portfolios more than it helps them.

Should we really conclude that expectations about return, risk, and correlation, derived from some combination of theory and data, are useless for portfolio construction? We argue not. The notion that 1/N is superior to optimization is based on tests that blindly extrapolate small‐sample historical means as estimates of expected return. It is this naïve approach to estimating expected return, and not the process of optimization, that is flawed. Thoughtful practitioners know not to rely on recent return outcomes as expected returns. Successful portfolio optimization does not require perfect estimates of return and risk—merely estimates that are plausible. If we use reasonable intuition along with long samples of historical data to estimate optimization inputs, optimization regularly ...