Is it ever a stock-picker's market?

You've heard it a thousand times: "This is a stock-picker's market." When markets surge, skilled selection supposedly becomes irrelevant. When volatility strikes, the same managers insist they can finally prove their worth. The explanation changes with the weather, but the bill stays constant. Fresh evidence from Morningstar, backed by five decades of academic research, reveals the truth: the stock-picker's market is marketing fiction designed to justify fees regardless of results.

Picture 2022's bear market. Your adviser called it "exactly the environment where active management shines." Fast forward to 2024's AI-driven surge. Same adviser, different story: "Momentum markets don't reward stock-picking." Now, in 2025's choppy conditions? Back to the original pitch.

This isn't tiresome marketing. It's unfalsifiable narrative construction. Every market condition justifies the fees. The question isn't whether you've heard this before. It's whether it survives contact with evidence.

What the industry claims about the stock-picker's market

The "stock-picker's market" narrative offers fund managers a perfect hedge. Every outcome confirms their value.

The framework divides markets into two seasons. Rising markets become "momentum-driven" where skill supposedly vanishes. When volatility arrives, we enter the mythical "stock-picker's market" where selectivity suddenly matters.

The theory sounds plausible. Wider return dispersion between stocks should favour skilled selection. When some soar whilst others crater, talented managers should pick winners and dodge losers. You want to believe your fees buy this protection.

The problem runs deeper than flawed theory. This story can't be disproven in real-time. There's no environment where the industry says "just index". Bull markets justify fees for "participating in growth." Bear markets justify fees for "protecting capital." High dispersion? "Exploiting opportunities." Low dispersion? "Managing risk."

Every condition confirms the pitch. The narrative adapts whilst fees compound.

Here's what happens when you test it against data.

What 26 years of data reveals about stock-picker's markets

Morningstar's Amy Arnott examined 26 years of S&P 500 performance from 1999 through September 2025. Her conclusion: even when conditions should favour active managers, most still lose. And it's worsening.

The collapsing success rate

Active fund win rates crashed from 67% in 2000 to just 26.7% through September 2025. The 26-year average sits at 42.4%.

The trajectory is unmistakable:

Source: Morningstar Direct. Data as of Sept. 30, 2025. Data is based on actively managed equity funds that use the S&P 500 as their performance benchmark

This isn't noise. It's systematic decline. If stock-picker's markets existed, we'd see periodic spikes when conditions favour skill. Instead: steady erosion.

The timing of peak success exposes the absurdity. The year 2000 marked the tech bubble's height, when valuations detached from fundamentals entirely. If that chaotic environment represented the golden age for stock-picking, the theory collapses.

Since then, as markets have grown more efficient through technology and information flow, active managers have fared progressively worse. Whatever stock-picker's markets might theoretically be, they're becoming rarer.

Dispersion doesn't help

Arnott compared individual S&P 500 stock win rates against active fund success. Theory predicts tight correlation. More winners and losers should help skilled pickers exploit the gaps.

The relationship between stock dispersion and fund success tells the story:

Source: Morningstar Direct. Data as of Sept. 30, 2025

Reality: R-squared of 0.19. Weak relationship at best.

Translation: even when clear winners and losers emerge, most funds can't exploit it. Some years show high dispersion with decent fund performance. Others show similar dispersion with terrible results. The pattern appears random.

If managers could identify winners in high-dispersion environments, we'd see strong correlation. We see scatter.

Down markets reveal mechanics, not skill

Arnott tested whether funds perform better when index returns are lower. In 2022's bear market, slightly over half beat the benchmark.

The pattern becomes clear when plotting fund success against market returns:

Source: Morningstar Direct. Data as of Sept. 30, 2025

This looks like evidence until you examine the mechanism. Most funds hold cash for redemptions. When markets fall, cash drag becomes cash benefit. A fund holding 5% cash only needs its stocks to drop 17% to match an 18% index decline.

This isn't stock-picking. It's arithmetic. The advantage vanishes when markets rise and cash creates drag. Over full cycles, down-year benefits fail to offset up-year penalties.

The pattern across all three tests tells one story: no evidence that market conditions create opportunities justifying fees. When funds do better, it's chance or mechanical factors, not skill.

“The pattern across all three tests tells one story: no evidence that market conditions create opportunities justifying fees.”

But why does active management consistently fail regardless of conditions?

The arithmetic that guarantees failure

Active management isn't a competitive game where skill determines winners. It's a mathematical trap where costs guarantee most participants lose.

The zero-sum reality

Nobel laureate William Sharpe proved the arithmetic in 1991. Before costs, the average active investor must match the market. Mathematical certainty. For every outperformer, another must underperform by an equal amount.

After costs, active investing becomes negative-sum. Management fees, trading expenses, and research budgets get subtracted. The average active investor must trail by the amount of costs incurred.

Russ Wermers (2000) quantified this: funds underperform broad market indices by 130 basis points annually. Over 20 years, that 1.3% gap compounds brutally. A £100,000 investment growing at 8% reaches £466,096. At 6.7%? Just £367,151. Nearly £100,000 less from a seemingly modest annual difference.

The arithmetic compounds relentlessly. The industry frames 1.3% as a small premium. Compounded over decades, it's the gap between comfort and anxiety.

Skill doesn't persist

If genuine talent exists, it should persist. Talented managers should consistently outperform. Mark Carhart's 1997 study found performance persistence vanishes over longer horizons. Short-term winners revert. The only consistency? Underperformance by the worst funds continued.

Eugene Fama and Kenneth French (2010) used rigorous statistics to separate skill from luck. Finding: only a tiny fraction shows genuine skill distinguishable from chance. Even among the top 1%, the margin was slim.

Laurent Barras, Olivier Scaillet, and Russ Wermers (2010) controlled for "false discoveries." When testing thousands of funds, some appear skilled through pure chance. After correction, only a minuscule percentage delivered genuine alpha.

Think of flipping coins. If a thousand people each flip 10 times, several will get eight or nine heads through luck alone. You can't conclude they have coin-flipping skill. Same logic applies to fund performance. In a large universe, some will outperform through luck. Identifying genuine skill requires more than observing past returns.

Most stocks destroy wealth

The challenge goes deeper. Most stocks lose money. Hendrik Bessembinder's research found 51.6% of US stocks produce negative cumulative returns over their lifetimes. Globally, the top 2.4% of firms account for all net wealth creation.

Stock-picking isn't selecting winners from mostly decent options. It's finding the tiny fraction of extraordinary winners whilst avoiding the majority that destroy wealth. Missing just a few rare winners devastates long-term returns.

“Stock-picking isn’t selecting winners from mostly decent options. It’s finding the tiny fraction of extraordinary winners whilst avoiding the majority that destroy wealth.”

The arithmetic creates an impossible hurdle. Imagine a lottery where half the tickets guarantee losses and nearly all gains come from 2.4% of tickets. Even identifying "good" stocks that won't lose money, you still need the microscopic fraction that will compound dramatically. Identifying them in advance is statistically indistinguishable from luck.

This extreme skew means diversified index funds automatically capture winners. They hold everything, so they can't miss the Apples and Microsofts. Active managers must identify those winners beforehand and hold concentrated positions to outperform meaningfully.

Terrible odds before costs.

What should you do with this information?

Why simple wins

The evidence doesn't mean skill is impossible. It means you can't access it profitably, and you don't need to try.

Skill exists but doesn't help investors

Small pockets of genuine skill appear in academic literature. Malcolm Baker and colleagues (2010) found managers' purchases slightly outperform their sales over subsequent quarters, suggesting forecasting ability. Martijn Cremers and Antti Petajisto (2009) identified high-Active-Share managers who avoid closet indexing and show better results.

Three problems remain insurmountable.

First, identification. You can't distinguish skill from luck until afterwards. By the time a track record becomes statistically significant, conditions may have shifted or the edge eroded. Past performance provides no guarantee, but it's the only data you have.

Second, access. Jonathan Berk and Richard Green (2004) demonstrated that successful performance attracts inflows. As assets grow, the manager's ability to exploit opportunities diminishes. Identifying and investing with skilled managers destroys the advantage through scale. The reward flows to managers through higher fees, not to investors through returns.

Third, costs. Even where skill exists, fees often consume it. A manager generating 2% alpha before costs becomes a market performer after charging 2% in fees. You capture nothing whilst the manager profits.

The Baker research on forecasting is telling. The outperformance spans quarters, not years. By the time you identify the skilled manager, invest, and wait for compounding, transaction costs and market movements have likely eliminated any benefit.

Why the narrative persists

The "stock-picker's market" pitch is brilliant marketing precisely because it's unfalsifiable. Bull markets: "Stick with us." Bear markets: "Now's when we prove value." High volatility: "This is our moment." Low volatility: "We're protecting capital."

Every condition justifies fees. Long-term underperformance stays obscured by short-term noise. By the time the pattern becomes undeniable, fees have been extracted. Losing investors depart. New ones arrive, drawn by recent returns or compelling pitches. The cycle continues.

The industry has trained you to view simplicity with suspicion. Surely your financial future requires expertise, active management, sophisticated analysis. The truth is less flattering to professionals: sophistication is the trap.

The boring alternative

Low-cost index funds aren't sophisticated or exciting. They don't require identifying talented managers or timing conditions. They simply avoid the arithmetic trap.

You accept market returns minus minimal costs rather than market returns minus substantial costs. A global equity index fund charging 0.2% annually captures nearly all market returns. An actively managed fund charging 1.5% must beat the market by 1.3% just to match, before accounting for additional trading costs.

This isn't a bet on efficiency. It's accepting arithmetic reality. Even in inefficient markets full of opportunities, exploiting them typically costs more than the benefits. The few managers who capture excess returns charge fees that extract most of the value.

Boring defeats clever. Not sometimes. Reliably.

The freedom that comes from accepting simplicity

26 years of Morningstar data tells the same story as five decades of academic research: the stock-picker's market doesn't exist for investors paying fees. Not because markets are perfectly efficient, but because the arithmetic of costs makes profiting from skill impossibly difficult.

The real choice isn't "active versus passive in different conditions." It's "market returns minus minimal costs versus market returns minus substantial costs." Framed honestly, the decision becomes obvious.

This evidence frees you from exhausting searches for skilled managers who'll beat markets. You're not missing out by choosing simplicity. You're avoiding a trap that captures most investors. The industry spent decades convincing you that simple solutions can't work for something as complex as investing. But complexity justifies fees, not delivers returns.

The "stock-picker's market" narrative kept you paying regardless of conditions. Bull market? Pay for expertise. Bear market? Pay for protection. The explanation changed but the invoice didn't.

The data liberates you. Simple, boring, cheap indexing wins not because it's clever, but because arithmetic doesn't lie.

“The data liberates you. Simple, boring, cheap indexing wins not because it’s clever, but because arithmetic doesn’t lie.”

The costs you avoid compound just as powerfully as returns you capture. Over decades, that combination creates wealth that active management, with all its sophistication and promises, consistently fails to match.

The myth of the stock-picker's market has been exposed for what it always was: performance theatre designed to extract fees regardless of results. Stop watching the show. Start building wealth.

Resources

Baker, M., Litov, L., Wachter, J., & Wurgler, J. (2010). Can mutual fund managers pick stocks? Evidence from their trades prior to earnings announcements. Journal of Financial and Quantitative Analysis, 45(5), 1111-1132.

Barras, L., Scaillet, O., & Wermers, R. (2010). False discoveries in mutual fund performance: Measuring luck in estimated alphas. Journal of Finance, 65(1), 179-216.

Berk, J. B., & Green, R. C. (2004). Mutual fund flows and performance in rational markets. Journal of Political Economy, 112(6), 1269-1295.

Bessembinder, H. (2024). Which U.S. stocks generated the highest long-term returns? SSRN Electronic Journal.

Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.

Cremers, M., & Petajisto, A. (2009). How active is your fund manager? A new measure that predicts performance. Review of Financial Studies, 22(9), 3329-3365.

Fama, E. F., & French, K. R. (2010). Luck versus skill in the cross-section of mutual fund returns. Journal of Finance, 65(5), 1915-1947.

Sharpe, W. F. (1991). The arithmetic of active management. Financial Analysts Journal, 47(1), 7-9.

Wermers, R. (2000). Mutual fund performance: An empirical decomposition into stock-picking talent, style, transactions costs, and expenses. Journal of Finance, 55(4), 1655-1703.

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