Just look in a dictionary and you’ll see “optimal” described as “best” or “most favorable.” Though you’d rarely describe an investment strategy as “the best,” many advisors have no problem with describing a strategy as optimal.
In his essay, “We Need to be Better than ’Optimal,’” Mercer’s Phil Edwards provides a brief history on the terms optimal and mean variance optimization, and reasons that perhaps it is time to remove the quantitative definition of “optimal” from investment strategies and goals.
He traces the investment lexicon roots of “optimal” to just after the widespread adoption of mean variance optimization, which Harry Markowitz developed in the 1950s. But, he says, it’s time to rethink this.
“An over-reliance on simplistic quantitative tools will lead to naïve portfolio construction, wrapped in a comfort blanket of optimality.”
“Rather than aiming for some quantitative definition of optimality,” according to Edwards, “we should seek the more humble and realistic aim of robustness under a range of plausible scenarios. In its place, he recommends more straightforward and deterministic tools of stress testing, scenario analysis, and expert judgment as powerful alternatives. You might say this is just semantics, but Edwards’ position is that optimality is based on backward-looking inputs and doesn’t adequately address the complexity of the real world.
He further reasons that optimal investment strategy is an illusion and “an over-reliance on simplistic quantitative tools will lead to naïve portfolio construction.” He puts it bluntly: “It’s time we removed it from the investment lexicon.”
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