Investing is about understanding risk. If you don’t understand risk, you don’t understand investing. And yet, for decades, the industry has relied on flawed tools — outdated beta models and rigid sector classifications — to measure it.

Some managers, particularly those obsessed with tracking benchmarks, force their portfolios into pre-defined sector categories designed decades ago, long before modern data and real-world market behavior could be fully understood. They do this because they are fearful of performing too differently from pre-defined, legacy benchmarks that were never constructed with investors’ interest or risk in mind. These legacy benchmarks and sector classifications, assigned by Standard & Poor’s and embedded into index construction in a bygone age of finance, no longer reflect how companies actually behave in markets today in our view.

Worse still, we believe traditional beta — the industry’s standard risk metric — wrongly assumes stocks move purely because of the market itself. That is a vast oversimplification and a fundamental mistake. Macroeconomic forces, shifting business models, and structural changes in the global economy matter a lot and are in constant flux. Beta and sector labels fail to capture this reality.

We have seen other managers who continue to rely on outdated tools, marching forward as if nothing has changed. We try not to make that mistake, and know that it is imperative to innovate and adapt.

The Flaws of Traditional Beta and Sector Labels

Imagine leading troops into battle. The maps you’ve been given were drawn decades ago. The rivers have shifted, the high ground isn’t where it used to be, and the enemy’s tactics have changed. If you rely on the old map, you could be walking straight into an ambush.

This is basically what we imagine happening if we relied only on traditional beta and outdated sector classifications. It would be dangerous and lazy to assume stocks will always behave the way they did in the past. It would be nice to believe companies fit neatly into categories designed by Standard & Poor’s or other index providers, but it would be unrealistic. We can’t fight today’s battles with old maps, based on old assumptions.

How Beta and Sector Labels Miss the Mark (Three Real-World Examples):

Example 1: A bank stock collapses — not because of a market downturn, but because interest rates spike.

• Reality – Banks make money on the spread between borrowing and lending rates. When rates rise unexpectedly, that spread shrinks, and profits fall.
• Blind spot – Traditional beta ignores interest rate risk, and sector classification lumps all financials together—even though banks, asset managers, and insurers have very different exposures.

Example 2: A global industrial giant underperforms — not because demand weakens, but because the U.S. dollar strengthens.

• Reality – A large U.S.-based industrial company sells lots of heavy machinery worldwide. When the dollar strengthens, foreign buyers pay more, demand drops, and revenue takes a hit.
• Blind spot – Yet beta would suggest the company’s stock should move with the overall market. That’s nonsense. The stock is moving with currency fluctuations. But legacy sector classifications still group it with other U.S.-focused industrials, and beta fails to capture this risk.

Example 3: A leveraged corporate borrower tanks — not because of weak earnings, but because credit spreads widen.

• Reality – Some companies rely heavily on cheap debt. When lenders demand higher interest rates on risky borrowers, these companies suddenly face higher costs and lower margins.
• Blind spot – A standard beta model won’t directly flag this risk, and sector labels won’t differentiate between a highly leveraged firm and a cash-rich one.

It’s easy to see how the conventional approach to risk creates blind spots. Companies today don’t fit neatly into the same legacy sector categories they used to in the past. A financial services company, health equipment supplier, media company, and software business may all respond similarly to environmental changes even though they are in very different sectors.  What matters is how the stocks behave, not what category a rating agency assigns them to.

Risk simply cannot be reduced to a single number.

Many managers know this but continue fighting the last war with the same old tools. That may work for them, but it makes us uncomfortable. We focus on what’s actually happening in markets today.

A Smarter Way: “Purer” Betas, “Real” Market Groupings, and a Stronger Defense

At Washington Crossing Advisors, we take a reality-based approach to risk assessment. Instead of blindly trusting beta and old-school sector classifications, we strip out macroeconomic distortions and analyze risk based on real-world stock behavior.

We want to understand where risk comes from as precisely as possible. To do this, we’ve developed the following four-step process to help us better manage portfolio risk:

Step 1: Isolate Market Risk from Macro Factors

Before measuring beta, we remove the influence of external forces like interest rates, credit spreads, and currency fluctuations. What’s left is what we call “Pure Market Beta.” In our view, this measure of risk is superior to the usual “beta” because it strips out macro distortions like interest rates, credit spreads, and currency fluctuations, giving us a clearer measure of how much a stock truly moves with the broader market — without being misled by external shocks that traditional market beta fails to separate.

Step 2: Group Companies Based on How They Actually Trade

Traditional sector labels assume companies today fit neatly into categories designed decades ago. But markets evolve. Instead of forcing companies into old definitions, we analyze how stocks actually behave—grouping them based on their real trading patterns, not just their industry labels. The results often reveal connections that Standard & Poor’s sector labels fail to capture—companies that move together in the market, even if their traditional classification suggests otherwise.

Step 3: Compare a Stock to Its Relevant Peers

Once we identify a stock’s peer group, we run our macro-adjusted beta model on the entire group. We compare the stock’s Pure Market Beta to its real peers, averaging out distortions and identifying anomalies. This produces a more stable, more accurate measure of market risk—one that we actually find useful when making portfolio decisions.

Step 4: Reinforce the Defense with Quality

One of the fastest ways to destroy wealth is through excessive exposure to high-risk companies. At Washington Crossing Advisors, we believe quality is the strongest defense against that kind of outsized risk. To this end, we analyze and grade companies from “A” (highest quality) to “F” (lowest quality).

WCA High Quality Companies Generally:

✔ Carry lower debt, making them less vulnerable to rising borrowing costs.

✔ Produce consistent profits, allowing them to weather downturns.

✔ Maintain stable operations, attracting investors when panic sets in.

We have found that higher-quality companies are fundamentally less susceptible to market stress — whether it’s an economic slowdown, stress in credit markets, or rising fear in equity markets. No strategy can eliminate risk entirely, but prioritizing quality helps manage it in a way designed to give investors a steadier hand when uncertainty rises.

While some of this defense means that gains will tend to be more tempered in strong bull markets, that portfolio yields will be below those of deep value managers, and that some types of companies with lower quality grades will not be in the portfolio, these are sacrifices generally worth making if the goal is to generate returns while minimizing unwanted risks.

So for us, quality can never be an afterthought — it is a core pillar of our process. Just as any sound military strategy requires strong defensive positions, a disciplined investment strategy requires a deliberate tilt toward quality.

The Bottom Line: A Practical Approach to Risk

We don’t slavishly adhere to arbitrary benchmarks or categories defined by third parties that are unconcerned with risk. Nor do we cling to outdated models that obscure hidden risks. We take a clear-eyed, reality-based approach that recognizes that macroeconomic forces, structural changes, and fundamental business quality are what really shape portfolio outcomes over time.

By combining macro-modeling, smarter risk grouping, and an emphasis on quality, we are building a more resilient, disciplined, and forward-thinking investment process.

Some managers will keep relying on outdated playbooks, reacting to risks only after they’ve already hit.

That’s not how we do things.

We adapt, evolve, and rethink how risk is measured — because in investing, as in war, the worst mistake is preparing for the last fight instead of the next one.

Contacts:

Kevin Caron, CFA, Senior Portfolio Manager
Chad Morganlander, Senior Portfolio Manager
Matthew Battipaglia, Portfolio Manager
Steve Lerit, CFA, Head of Portfolio Risk
Suzanne Ashley, Relationship Manager
Eric Needham, Sales Director
Jeff Battipaglia, Sales and Marketing
(973) 549-4168

www.washingtoncrossingadvisors.com

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WCA Quality Grades
The WCA Quality Grade indices are objective, quantitative measures designed to identify quality in the top 1,000 US companies. Ranked by fundamental factors, companies are graded from “A” (top quintile) to “F” (bottom quintile). Factors include debt relative to equity, asset profitability, and consistency in performance. Companies with lower debt, higher profitability, and greater consistency earn higher grades. These indices are reconstituted annually and rebalanced daily. For informational purposes only, and WCA Quality Grade indices do not reflect the performance of any WCA investment strategy.

S&P 500 — The Standard & Poor’s 500 Index is a capitalization-weighted index that is generally considered representative of the U.S. large capitalization market.

The S&P 500 High Beta Index measures the performance of 100 constituents in the S&P 500 that are most sensitive to changes in the market. Constituents are weighted relative to their level of market sensitivity, with each stock assigned a weight proportional to its beta.

The S&P 500 Low Volatility Index measures performance of the 100 least volatile stocks in the S&P 500. The index benchmarks low volatility or low variance strategies for the U.S. stock market. Constituents are weighted relative to the inverse of their corresponding volatility, with the least volatile stocks receiving the highest weights.