Beyond Volatility: Why We Updated the ALTS Portfolio Modeling Risk Methodology

For decades, investment risk has largely been summarized by one statistic: volatility.

Volatility is useful. It tells us how much an investment has moved around its average return. It gives advisors a common language for comparing assets, building efficient frontiers, and explaining why a portfolio may feel smoother or bumpier over time.

But volatility is not the same thing as pain. A portfolio that rises sharply and falls gently can look volatile. A portfolio that behaves quietly most of the time but suffers badly in a severe downturn can look deceptively calm. For advisors trying to build resilient portfolios, that distinction matters.

Why the Left Tail Matters

Larry Swedroe recently discussed Hyland and Schmitz's April 2026 paper, Pricing the Left Tail: Consumption Skewness and Expected Returns. The central idea is straightforward: investors care deeply about how assets behave when the economic environment is genuinely stressed.

In plain English, the paper focuses on the left tail, or the difficult part of the range of outcomes where growth slows, incomes are pressured, financing becomes harder, and confidence weakens. Assets that tend to hold up better in those environments can be more valuable to a portfolio than a simple volatility number would suggest. Assets that appear stable in normal conditions but become fragile when conditions deteriorate deserve closer scrutiny.

That framing resonated with our work on private markets because many private assets are not priced every minute. Their reported volatility may be lower simply because they are valued less frequently. That does not automatically mean they are less risky. It means the risk has to be studied differently.

How ALTS Applied the Concept

Based on this thinking, ALTS updated the risk methodology in the ALTS Portfolio Modeling tool. The goal is not to make the model more complicated for advisors. The goal is to make the output more useful.

Instead of relying primarily on average volatility, the updated framework places more emphasis on downside environments, resilience, and the quality of an asset's role inside a portfolio. It asks whether an allocation may help during difficult periods, whether it may create hidden concentration risk, and whether its return profile is supported by durable fundamentals.

For private-market modeling, that means looking beyond smoothed valuations. It means evaluating cash-flow behavior, financing exposure, liquidity terms, sector sensitivity, and the conditions under which a strategy may face stress. These factors are often more relevant to real client outcomes than a single historical standard deviation.

What This Means for Advisors

Advisors need tools that support better conversations. Clients rarely ask whether their portfolio's annualized volatility was efficient. They ask whether they are prepared for a downturn, whether their income plan can withstand stress, and whether their alternatives are doing the job they were selected to do.

The updated ALTS Portfolio Modeling framework is designed to help advisors explain those issues more clearly. It can support discussions about portfolio resilience, downside-risk assessment, diversification quality, and the tradeoffs that come with adding private assets to a traditional allocation.

This is especially important when comparing public and private investments. Public assets may show every bump in the road. Private assets may report a smoother path. A thoughtful framework should not reward smooth reporting by itself. It should ask whether the asset can contribute to the portfolio when the environment is unfavorable.

Industrial Real Estate as an Example

Industrial real estate illustrates the point. A warehouse, manufacturing facility, or logistics property may look stable in a spreadsheet, but the real question is how it behaves under stress. Tenant quality, lease duration, replacement cost, location, property use, financing structure, and industry demand can all influence downside resilience.

Two industrial properties may have similar expected returns and similar reported volatility, yet very different risk profiles. One may be backed by a durable tenant, essential operations, and conservative leverage. Another may depend on a more cyclical user, shorter lease terms, or a market with weaker replacement demand. Average volatility alone will not capture that difference.

By incorporating downside-oriented thinking into the modeling process, advisors can better evaluate whether an industrial real estate allocation is simply different from public markets or genuinely additive to portfolio resilience.

A More Thoughtful Framework

The ALTS Portfolio Modeling tool is not intended to predict the future with precision. No model can do that. Its purpose is to help advisors evaluate private-market allocations with a richer set of questions before capital is committed.

Moving beyond volatility does not mean abandoning discipline. It means using the right discipline for the asset class. For private markets, a stronger risk framework should consider downside scenarios, liquidity constraints, valuation practices, economic sensitivity, and the role each allocation is expected to play in the total portfolio.

That is the spirit behind the methodology update. A portfolio should not be judged only by how smooth it looks in average conditions. It should be evaluated by how thoughtfully it is built for the environments clients worry about most.

This article is for educational purposes only and should not be considered investment, tax, legal, or accounting advice. Portfolio modeling is based on assumptions and scenarios that may differ materially from actual results.