When the Noise Gets Loudest: Why Fundamental Research Matters Most in Volatile Markets

The Setup

This past week reminded every market participant of a truth we tend to forget during calm stretches: prices can move violently on information that has nothing to do with the businesses underneath them.

On Tuesday, the S&P 500 surged 2.5% on news of a U.S.-Iran ceasefire. The Dow added over 1,300 points — its best single day since April 2025.² West Texas Intermediate crude plunged more than 16% to $94.41 per barrel,³ its steepest decline since the pandemic sell-off of April 2020.³ Industrials soared. Energy stocks cratered. Airlines and cruise lines jumped. And by Wednesday, the rally was already fading as questions about the Strait of Hormuz’s reopening timeline introduced fresh uncertainty.

Meanwhile, the tariff landscape continues to evolve. Following the Supreme Court’s February ruling that invalidated the IEEPA-based tariffs, a new 10% global tariff under Section 122 is set to expire in July. The effective U.S. tariff rate sits at 11.0% — the highest since 1943. Businesses absorbed roughly 80% of tariff costs last year, but analysts warn that ratio could invert as 2026 progresses, with consumers shouldering more of the burden. For companies with global supply chains, the earnings impact is real: one major consumer goods company cited tariffs as a five-point headwind to core earnings-per-share growth this fiscal year.⁸

And now, as of next week, first-quarter earnings season begins in earnest with the nation’s largest banks reporting.

The question every investor faces right now is straightforward: in an environment this noisy, how do you distinguish between signal and static?

The Analysis

The Noise Problem

Most market participants respond to volatility in one of two ways. Some chase momentum — they buy into ceasefire rallies and sell into tariff fears, attempting to surf waves of sentiment. Others freeze — they park capital in money markets and wait for “clarity” that never quite arrives.

Both approaches share a common flaw: they treat the macro environment as the primary input to investment decisions. But geopolitical events, tariff policy shifts, and oil price swings are inherently unpredictable. No one credibly forecasted the timing of the Iran ceasefire. No analyst model accurately predicted the Supreme Court’s tariff ruling. Trying to build an investment process around correctly timing these events is, to put it plainly, a losing strategy over any meaningful time horizon.

The alternative is to focus on what can be known — the fundamental characteristics of individual businesses — and to do that work with enough depth and rigor that short-term macro noise becomes largely irrelevant to the investment thesis.

Why Scuttlebutt Analysis Gains an Edge in Volatility

Philip Fisher articulated this approach decades ago in what he called “scuttlebutt” investing — the practice of going beyond financial statements to understand a business through its customers, suppliers, competitors, and employees. Fisher’s insight was that the most durable competitive advantages are qualitative in nature: management integrity, organizational culture, R&D effectiveness, customer loyalty. These things don’t show up cleanly in a 10-K, but they determine whether a business compounds value over five, ten, or twenty years. When prices dislocate from fundamentals, the investor who understands the fundamentals most deeply is best positioned to act rationally.

Consider the current environment. A ceasefire rally lifts industrials indiscriminately — but not every industrial company has the same supply chain resilience, pricing power, or management quality. A tariff headwind pressures consumer goods companies — but some have already restructured their sourcing, while others are still exposed. Earnings season will reveal these differences, but the work of understanding them should have been done long before the numbers are reported.

This is where systematic qualitative research creates its value. When an investor has already mapped a company’s competitive position through dozens of data points — employee satisfaction trends, customer retention patterns, patent activity, supplier relationships, management’s capital allocation track record — a 2.5% index move on geopolitical news doesn’t change the thesis. It may change the price, which is a different thing entirely.

The Role of Technology in Cutting Through Noise

The volume of information available to investors today is both a blessing and a curse. Earnings transcripts, SEC filings, employee reviews, patent databases, industry reports, customer sentiment data — the raw material for fundamental research has never been more abundant. The challenge is processing it with consistency and speed.

This is where artificial intelligence is beginning to transform fundamental analysis — not by replacing human judgment, but by scaling the parts of the research process that benefit from systematic coverage. Natural language processing can parse thousands of earnings transcripts to identify shifts in management tone or strategic emphasis. Machine learning models can flag anomalies in employee sentiment data that might take a human analyst weeks to surface manually.

Morgan Stanley Research estimates that nearly $3 trillion of AI-related infrastructure investment will flow through the global economy by 2028.⁹ But for investors, the more interesting question isn’t about AI as a sector — it’s about AI as a tool. The firms that are integrating AI into their research processes are finding that it enables a kind of coverage breadth that was previously impossible for concentrated, high-conviction investors. You can maintain deep fundamental knowledge of a focused portfolio while simultaneously monitoring the qualitative indicators across a much wider universe of companies.

The key distinction is that technology should amplify the quality of fundamental research, not replace it with quantitative shortcuts. A model that tells you customer sentiment for a company dropped 15% last quarter is useful. Understanding why it dropped — and whether the cause is transient or structural — still requires human judgment and domain expertise. What This Means When Earnings Season Arrives

As the big banks report next week and the broader market follows through April and May, the gap between price and value will become visible in company-specific ways. Some businesses will report results that confirm the resilience their fundamentals suggested. Others will reveal cracks that were masked by favorable macro conditions in prior quarters.

The tariff environment adds a layer of complexity. With the effective tariff rate at multi-decade highs and the cost-absorption dynamic potentially shifting from businesses to consumers, earnings calls will be unusually revealing. Listen for specifics: which management teams have concrete plans for supply chain adaptation? Which ones are vague about pricing strategy? Which companies have already invested in operational flexibility, and which are hoping the policy environment improves before they have to act?

These are scuttlebutt questions — they require qualitative judgment, not just spreadsheet analysis. And they matter far more to long-term compounding than whether the index finishes the week up or down 3%. The Implication

For investors with a multi-year time horizon, weeks like this one are clarifying rather than destabilizing. Volatility driven by geopolitical events and policy shifts doesn’t change the fundamental trajectory of well-managed businesses with durable competitive advantages. What it does is create temporary dislocations between price and intrinsic value — and those dislocations are the raw material of long-term outperformance.

The discipline required is twofold. First, do the fundamental work before you need it. The investor who scrambles to evaluate a company after a 10% price drop is already behind. Second, maintain conviction rooted in evidence rather than narrative. Markets are narrative machines — they construct stories around price moves after the fact. “Stocks rallied on ceasefire optimism” is a narrative. Whether the businesses you own are worth more or less today than they were on Monday is a question that requires actual analysis.

Concentrated portfolios — those built on deep conviction in a small number of thoroughly researched positions — are particularly well-suited to this environment. When you know a business deeply, you can assess in real time whether new information changes the thesis or merely changes the price. Diversified portfolios, by contrast, are implicitly an admission that the investor doesn’t know enough about any individual holding to maintain conviction through volatility.

The Takeaway

When the noise gets loudest, the edge belongs to the investor who has already done the quiet, unglamorous work of understanding businesses at a fundamental level — and who has the tools, process, and temperament to act on that understanding when others are reacting to headlines.