Facts Not Feelings

key points

Clarity in Chaos

In times of uncertainty — whether in sport or in markets — the ability to separate fact from feeling — or ideology — is critical. This principle applies across leadership, investing and even today’s AI-driven economy.

Recently, I had the privilege of meeting one of New Zealand’s rugby greats, former All Blacks Captain Richie McCaw — a back-to-back Rugby World Cup-winning leader with an 89% win record. At a leadership conference in our Chicago office, McCaw was asked how he stayed calm under pressure. His answer? Separate facts from feelings. Under stress, our minds create stories; focusing on facts brings calm, unlocks solutions and delivers clarity in chaos.

The greats of investing echo this wisdom. Peter Lynch spoke of “returning to fundamentals” during the 1987 crash, Charlie Munger warned how ideology could “distort cognition” and Warren Buffett advised “mastering emotions to master the market.” Those lessons feel timely amid today’s emotionally charged talk of “bubbles and bailouts.” Perhaps it’s time to refocus — on facts, not feelings.

Facts, Not Feelings

Skepticism is rarely the dominant feeling at market peaks. Euphoria — or “a mass escape from reality,” according to economist J.K. Galbraith — is more common. Yet today, deep skepticism persists even as markets hover near highs and as Warren Buffett steps in (see Berkshire Hathaway’s recent Alphabet purchase). That’s unusual.

As we noted in Beyond the Bubble, today’s market differs in many ways from the dot-com era. While some issues concern us, index quality is higher: tech companies boast stronger margins, better free cash flow and valuations that look less stretched after adjusting for profitability. Still, as bull markets mature, dispersion rises. Pullbacks — like the recent one — remind us that selectivity matters more than ever. This doesn’t mean the rally is over, but that markets are becoming more discerning. Take Oracle, recently punished over leverage concerns and counterparty risks tied to OpenAI. Credit default spreads for Oracle and CoreWeave widened sharply (+100 basis points and +600 basis points) versus their larger peers. But are these fears justified?

Residual Value

Leverage matters when collateral values fall or debt serviceability weakens. Yet the useful life of a data center extends far beyond the chips inside. High-end chips depreciate quickly (around three years), but data center buildings last 10–15 years before major upgrades are needed. Bernstein research suggests graphics processing unit (GPU) depreciation fears may also be overstated; older GPUs can still operate with cash costs below rental rates, supporting margins and financing even after 5-6 years. Nvidia has confirmed demand still outstrips supply, while Google reports seven- and eight-year-old tensor processing units (TPUs) running at full utilization.

Yes, leverage risk rises if residual values collapse — as in 2007 — but that’s not the case today, at least it isn’t yet. That and cash flow for major spenders is growing. That’s a fact worth noting.

Illiquidity Distortions

With many AI leaders still private (OpenAI, Anthropic), hedging activity can concentrate in a few public instruments. Therefore, with limited liquid credit hedges available, concentration risk can emerge (sounds familiar) and markets can distort perceptions of value, and risk. Sometimes, the hedging itself shapes the reality—a reminder that risk can be as much about structure as fundamentals. As much about perception, as reality.