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Portfolio selection: The solver isn’t the solution.

February 4, 2026
7 MIN READ 7 MIN READ

Developing capital market assumptions (CMAs)—expected returns, volatilities, and correlations across asset classes—is an incredibly important step in constructing portfolios and developing financial plans. Used properly, CMAs can help investors to better diversify their portfolios and establish reasonable expectations around the range of likely investment outcomes they might see over various time horizons. But to harness this powerful tool, it is important to understand the appropriate application of CMAs—and the potential dangers in their misuse.

“It is difficult to make predictions, especially about the future.” While this quote has been variously attributed to figures as disparate as Niels Bohr and Yogi Berra over the years, the sentiment rings true regardless of its source; prognostication is a tough business. SEI is extremely proud of our process for developing CMAs, and we believe our estimates to be unusually good, but any forecast is subject to estimation error. We employ a variety of techniques to minimize this error, but no one can eliminate it entirely. Regardless of where investors source their CMAs, these assumptions should be viewed as just one component of a robust portfolio construction process, tempered with sound judgement and an acknowledgement of uncertainty.

Exhibit 1: What CMAs are and aren’t.

CMAs are:CMAs are not:
  • Essential inputs for portfolio construction and
    Monte Carlo simulations
  • Valuable tools in establishing reasonable asset
    class and portfolio expectations for return, risk,
    and correlation
  • Thoughtful representations of relationships
    among asset classes
  • Ranges of potential future return paths helpful
    in estimating the likelihood of achieving one’s
    financial goals
  • Perfect predictors of asset class or portfolio
    returns
  • Specific predictions of outcomes to be realized
    over any particular time horizon
  • Infallible metrics to be used as the only
    objectives in portfolio optimization
  • Point estimates to be optimized to the basis
    point (e.g., by running a “solver” to maximize
    expected portfolio return or Sharpe ratio with
    no governor/constraints)

Pure mean-variance optimization—assuming one’s CMAs are perfect and maximizing expected risk-adjusted returns based on those exact estimates—is notoriously fragile. Small changes to CMAs, particularly expected returns, can lead to extreme shifts in ostensibly optimized portfolio weights. Given the inherent imprecision of any forward-looking estimate, this vulnerability poses a significant challenge to constructing optimized portfolios based on CMAs alone; unconstrained meanvariance optimization requires a degree of precision that is unrealistic for any forward-looking assumption.

bryan_hoffman

Head of Advice and Asset Allocation, Investment Management Unit

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Important Information

This material represents an assessment of the market environment at a specific point in time and is not intended to be a forecast of future events or a guarantee of future results. Statements that are not factual in nature, including opinions, projections and estimates, assume certain economic conditions and industry developments and constitute only current opinions that are subject to change without notice. Nothing herein is intended to be a forecast of future events, or a guarantee of future results.