Quality investing: under pressure, or misunderstood?

For Professional Investors Only

Longview Partners’ Chief Investment Officer Alexander Philipps explains why narrative-driven equity markets are challenging traditional definitions of quality and creating compelling opportunities at the same time.

Global equity markets are being shaped by powerful, fast-moving themes. The rise of artificial intelligence and dominance of momentum-driven strategies have shifted capital flows toward perceived winners and away from businesses that appear stable, predictable or exposed to disruption. The result is an unusually narrative-driven market.

This dynamic poses challenges for investors focused on durable competitive advantages, capital discipline and long-term operational performance. Quality managers have experienced a sustained period of underperformance, leading some to question whether the style remains fit for purpose in a market that appears to have moved on from its traditional virtues.

Alex Philipps, Chief Investment Officer of Longview Partners, believes the market is wrong. In this Big Interview, he explains why he believes the AI disruption narrative is being applied with the wrong conclusions and why the current environment is shaping investor perceptions for those willing to look through the noise.

 

Has quality investing changed, or has the market changed?

What has changed is the price that investors are willing to pay for stable, predictable businesses relative to the broader market. This is not because these businesses have become less valuable, but because other things have become more exciting and steady, high quality businesses that compound at high single digits have seemed like the consolation prize compared to owning something with an AI story attached to it. Markets have a habit of doing this. The pendulum swings, and businesses dismissed as boring become those investors wish they held.

Our definition of quality rests on four pillars, all of which are forward looking.

  1. The first is the sustainability of returns on capital. We believe that high historical returns are irrelevant to future investment returns. What matters is whether a company’s competitive position allows it to keep generating those returns: barriers to entry, switching costs, pricing power and incremental economics.
  2. The second is predictability. We want businesses that sit within a manageable range of outcomes and can broadly control their own destiny. This naturally excludes sectors where the outcome depends heavily on forecasting macro variables, such as commodity prices or the economic cycle. We have no competitive advantage in forecasting oil or metal prices, so we don’t go there.
  3. The third is opportunity to grow. This isn’t about chasing growth. It’s about avoiding businesses where growth is so limited that any setback quickly becomes a deleveraging story. The typical Longview portfolio holding grows revenues at a mid-to-high-single-digit revenue percentage – stable, not spectacular.
  4. And the fourth pillar is capital allocation. Even a strong business can destroy shareholder value if management deploys capital poorly, through poor M&A, empire-building or simply misallocating internally.

Our principles haven’t changed. But narrative-driven markets can cause large divergences between share prices and operational performance. Quality investing doesn’t typically outperform in rampant bull markets. It tends to keep up in normal conditions and protect strongly in difficult ones. I believe that remains true. What’s unusual about the current cycle is the duration and severity of the divergence.

 

“Understanding which situation you are dealing with – misperceived or mispriced – is where judgement comes in”

 

How does an allocator distinguish between managers who genuinely practise quality investing and those who have adopted the language?

Firstly, look at the portfolio and how it has changed over time. Does the portfolio fit with the manager’s definition of quality? Has it done so consistently over time? Are there warning flags, like buying banks in 2025 or energy in 2022, which would have boosted returns but indicated style drift?

Secondly, is the strategy a passive play on the quality index or a genuine forward-looking approach?

Our holdings are spread widely across the MSCI quality score spectrum, including some that don’t qualify for an MSCI quality rating at all. If you heard we were a quality manager and knew nothing else, you might expect all our holdings to cluster at the higher-quality end of the spectrum. The reason they don’t is because the index uses a backward-looking, three-factor definition – debt to equity, return on equity and standard deviation of earnings over the last five years – with no forward-looking indicators. That approach can miss businesses most likely to compound over the next decade and include some that may have already peaked. We focus entirely on the forward picture and what will allow businesses to continue earning returns above their cost of capital.

We find opportunities in two ways. The first is what we call misperceived quality – businesses the market doesn’t recognise as high quality but which, on a forward-looking analysis, genuinely are. HCA Healthcare is a good example: highly leveraged, capital-intensive, not an obvious quality candidate on any screen. But it has compounded earnings per share faster than Apple over the last 10years, benefiting from local monopoly positions in a market where roughly 80 per cent of competitors are not-for-profit. Finding opportunities like this requires fundamental analysis, not a factor screen.

The second is mispriced quality – businesses the market acknowledges as strong which have been temporarily discounted because of narrative or sentiment. Moody’s, which rates more than 90 percent of US corporate bonds, is a case in point. After the surge in debt issuance in 2020 and 2021, the market assumed volumes would fall off a cliff. We thought they would decline near term but recover over the long run.

Understanding which situation you are dealing with – misperceived or mispriced – is where judgement comes in. Both are fertile ground. And both are missed by approaches that rely on backward-looking screens.

 

What has the firm learned through this period of underperformance, and what have you changed?

Longview is celebrating its twenty fifth anniversary this year. It is inevitable that managers will go through periods where performance is challenged and we are no exception. In these times, it is important to learn lessons but not drift away from your strengths.

There are three areas I would like to touch on.

The first is a genuine market headwind. We are not alone in this. The market has been driven upwards by banks, European infrastructure and, more recently, energy and heavy asset businesses. For the most part, these are not typically fertile hunting grounds for quality investors. AI has also played a part, with many beneficiaries failing either our predictability or valuation criteria. Whilst we continue to ask whether we have got any calls wrong – perhaps aerospace, for example – and how we can avoid these in the future, it is important we don’t come to the wrong conclusion and change our definition of quality to suit today’s narrative.

The second is valuation discipline. Oracle is the clearest example: we held it for over 20 years and sold on valuation grounds when it hit our price target in the middle of last year. A few months later, we believe the market overreacted to information we felt should have been well-known and the share price rose sharply. This felt like a painful miss at the time, but today the shares are significantly below the level at which we sold. This confirmed our belief in the importance of value discipline and not trying to squeeze the last drop out of an investment.

The third is risk management, working in harmony with bottom-up stock selection. Our primary approach to risk management is reducing the risk of widespread portfolio value destruction. Last year, we capped the portfolio’s exposure to areas like software and information services and deprioritised work on a wide range of names that looked attractive in a historical context but looked at risk from AI disruption.

With hindsight, we could have been even more restrictive and cut existing exposure as well. This year, we have taken a more proactive approach to AI disruption risk, reducing portfolio exposure and setting thoughtful but slightly more restrictive guardrails, whilst staying true to our principles.

Your sell rule triggers when quality, fundamentals or valuations fail. Looking at underperforming current holdings – a governance or execution reset like Fiserv, or a company perceived at risk from AI – why hasn’t that rule triggered?

Our sell discipline asks the same questions as the initial buy: does this holding pass or fail on each of our quality, fundamentals or valuation criteria? When something has gone wrong, valuation is almost never the trigger; the market typically overreacts to actual value destruction we can identify, so the business ends up looking optically cheap against our assessment. The real question is always about quality and fundamentals.

On quality, we assess whether the business has deteriorated to the point where it fails across our four pillars. For a company threatened by AI, that might mean we feel its opportunity to grow has been materially impaired. We are not selling because the stock is down, or because a narrative has attached itself to the sector.

On fundamentals, the question is about direction of travel. Not ‘is this business worse than it was?’ but ‘is it going to continue deteriorating?’ If we believe the answer is yes, it triggers a sell regardless of where quality sits.

On Fiserv, the reset was real and something we got wrong. However, EPS growth going from 14-15 per cent to zero is a reset, not a terminal decline. The business continues to have recurring revenues and new management came in with a sensible plan. The key question for us was whether management fully understood the scale of the problems and implemented the right changes. Our view is based on hours of analysis, conversations with industry participants and discussions within the team.

On companies perceived to be threatened by AI, the difficulty is that there is almost no hard evidence yet of actual disruption. We are dealing with perceived disruption. Many of these businesses have continued performing metronomically. Our process is designed to prevent us selling purely based on sentiment or market narrative.

What would trigger a sell? Evidence. This can be hard or soft but we look for evidence that there a deterioration in competitive position, for example, signs that technology is likely to genuinely alter the economic model of the business for the worse. This might come from gathering evidence into what the company is doing defensively and offensively to protect and grow its business and what peers and competitors are doing. We are watching for these things constantly.

 

Where is the market wrong on AI disruption?

I believe the market has taken a single broad narrative and applied it with extraordinary bluntness to an enormously diverse set of businesses, but the argument doesn’t always stand up to scrutiny.

American Express sold off on concerns that AI will displace white-collar workers and reduce consumer spending. If you follow that logic, every consumer-facing business should be under pressure. And yet some names, like Walmart, are currently trading close to all-time highs. Insurance brokers sold off on concerns about a new AI car insurance comparison app. Yet the institutional broker market, serving multinationals with complex, global policy requirements that only a handful of companies in the world can underwrite, bears no resemblance to that model. This does not mean the market has been wrong in all cases. But there are inconsistencies.

The deeper error is conflating what could happen in a tail scenario with what is likely in the base case. Some might suggest the range of possible outcomes has widened. I push back on this.

What has changed is that the tail has fattened – the probability attached to certain adverse outcomes has increased. two things have legitimately shifted: the capital being spent on AI has grown significantly, and the quality of what these tools can do has improved materially. But we believe that neither of them, on their own, justifies treating every business that sells data, software or information as if the tail scenario is the base case. We have also seen multiple feted AI products discontinued within a year or so of launch. Not every new AI tool will be a success.

There is also a fundamental question about adoption pace. If you are the chief financial officer or chief technology officer of a large company and someone said you could replace your enterprise resource planning system with an AI model, you would not do it overnight. Changing a core enterprise system takes years, with significant disruption risks.

The question we believe the market is not asking clearly enough is: where will the value accrue in an AI-enabled world? Will it accrue to AI model providers, or will the underlying models become commoditised? Will it accrue to businesses with decades of proprietary data, deep client relationships and switching costs that allow them to deploy AI for their own benefit and charge for the result?

 

“Not every new AI tool will be a success”

 

You have a rules-based, equal-weight on entry approach to portfolio construction. In a market dominated by momentum and concentration, is that approach at a structural disadvantage?

It is a headwind in the current environment, but you have to look over a longer time horizon than the here and now.

Our equal-weighting approach on entry to the portfolio is deliberate and serves three specific purposes. Firstly, we believe that if you don’t have high conviction, you shouldn’t own something. Our approach leaves no room for low conviction tail positions to pollute the portfolio. Secondly, it removes the temptation to let winners run to the point where position concentration reflects price momentum rather than investment conviction. This means we are not implicitly running a momentum book under the cover of a quality framework. Thirdly, it focuses the investment team’s time and efforts into making a binary decision on whether a company passes the process. This reduces hidden costs of distraction and decision fatigue.

An equal-weighted portfolio is going to lag an index where a handful of stocks can account for a disproportionate share of total returns. That is a structural reality. The corollary is that when that concentration reverses – as it has historically – the equal-weighted approach has often tended to benefit.

The portfolio has significant US concentration at a time when investors want regional diversification. Are you comfortable with that?

When people see a portfolio with significant US exposure, the natural inference is that its returns are linked primarily to US conditions.

Many of our holdings are listed in the US but derive most of their revenues from other markets. Booking Holdings is a good example: it is a Dutch business listed in New York whose dominant market is Europe. The domicile of a company’s listing and the geographic exposure of its economic activity are different things and conflating them can be misleading.

That said, there is a question about whether the pipeline of businesses meeting our quality criteria is more concentrated in the US than elsewhere. The honest answer is that it has been. The combination of deep capital markets, strong intellectual property protection, competitive product markets and an entrepreneurial culture has produced more businesses meeting our quality threshold in the US. We have never been benchmark-aware in setting geographic exposure – we go where we believe the quality is. But we are conscious this can create the appearance of a portfolio with too much exposure to one geography.

 

Last word

Investors fall in love with new narratives. Sometimes those narratives are justified; often they prove more simplistic than the reality they claim to describe.

For example, to Philipps the current environment reflects a familiar pattern in which technological and market structure changes have amplified themes to the point where large groups of businesses are assessed through the same lens. The result, in his view, is substantial mispricing and an opportunity for investors.

“Ultimately, our job is to identify companies that can compound their operational value over time and not overpay for this,” he says. “If we can do that consistently, the market should eventually recognise it.”

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