The spread between the strongest and weakest US large-cap active managers has widened considerably, highlighting how portfolio positioning has become increasingly consequential.
The gap between the strongest and weakest US large-cap active managers has widened considerably. The spread between top- and bottom-decile rolling three-year excess returns is now near the highest level in two decades. While active managers have broadly faced a difficult environment, the more striking development is the growing divergence in outcomes, suggesting that portfolio positioning has become increasingly consequential.
Source: Evestment. Average 3-year rolling excess return over the period Q2 2006 - Q2 2026.
Source: Evestment. 3 rolling year excess return calculated over the period Q3 2023 - Q2 2026.
Source: Evestment. Data for the period Q3 2023 - Q2 2026.
The growing gap between active winners and losers is the most visible feature of today's active-management landscape. The more important question, however, is what sits behind the divergence.
A closer look at the percentile distribution data suggests that the widening spread has not been driven by increasingly exceptional winners. As shown in the chart below, the current performance of both top-decile (90th percentile) and median managers remains broadly comparable to recent history. The most meaningful change has occurred at the bottom of the distribution. The latest three-year rolling excess return for bottom-decile (10th percentile) managers ending in Q2 2026 was -8.3%, compared with an average of -3.9% over the past two decades. The widening dispersion appears to reflect increasingly severe underperformance among laggards rather than a dramatic improvement among leaders.
The characteristics of those laggards become clearer when viewed across three distinct market regimes shown in Table 1. The post-GFC period (2009-2013) was characterized by relatively broad market leadership. The following period (2014-2019) saw technology emerge as the market's dominant leadership group and benchmark concentration begin to rise. The most recent period (2020-2026) has been shaped by AI-related themes, mega-cap leadership, and increasingly concentrated benchmark returns.
Across these regimes, managers generally increased exposure to technology as the sector became a larger driver of market performance. The strongest managers moved further and faster, maintaining average technology allocations above 29% in the most recent environment. The weakest managers participated in the shift but to a far lesser degree, with technology exposure remaining just above 20%.
The divergence is even more apparent when measured relative to the broader universe. During the first period, bottom-decile managers were only modestly underweight technology, lagging the universe by 1.2 percentage points. By the most recent period, that gap had widened to 5.9 percentage points. As market leadership became increasingly concentrated, the weakest managers remained meaningfully less exposed to the sector at the center of that leadership.
Table 1: Technology Sector Exposure Across Manager Groups
| Manager group | Period 1 2009-2013 | Period 2 2014-2019 | Period 3 2020-2026 | Change (Period 1 minus Period 3) |
| Top decile tech weight | 20.4% | 24.0% | 29.1% | +8.6 pp |
| Universe tech weight | 19.5% | 21.4% | 26.2% | +6.7 pp |
| Bottom decile tech weight | 18.3% | 18.0% | 20.3% | +2.0 pp |
| Bottom minus universe | -1.2 pp | -3.4 pp | -5.9 pp | -4.7 pp |
Source: Evestment. Analysis based on S&P 500-benchmarked active strategies. Figures show average technology-sector portfolio weights across manager groups for each period.
The divergence extended beyond sector exposures. Another distinguishing feature was where managers allocated capital across the market-cap spectrum. The bottom decile's weighted-average market-cap ratio relative to the universe declined from 0.95 in the first period to 0.69 in the most recent period, indicating a growing tilt toward smaller companies relative to peers. While technology exposure increasingly differentiated winners from losers, so too did exposure to the market's largest and most influential companies.
The latest three-year snapshot shown in Table 2 illustrates how different the portfolios of top- and bottom-decile managers had become. Technology remained the clearest point of separation, with top-decile managers allocating 35.6% to the sector versus 23.2% for bottom-decile managers. At the same time, bottom-decile managers maintained greater exposure to Financials and Healthcare, resulting in meaningfully different sector profiles.
The market-cap data provides an equally revealing insight. Although top-decile managers exhibited higher weighted-average market capitalizations, the median holding in bottom-decile portfolios was more than twice as large. This apparent contradiction suggests that successful managers were not simply buying larger companies across the board. Rather, they combined broad portfolios with allocations to a relatively small number of mega-cap leaders, pulling their weighted-average market capitalization sharply higher. Bottom-decile managers, by contrast, owned larger companies more consistently but had less exposure to the handful of firms that ultimately drove benchmark returns.
Perhaps most notably, bottom-decile managers were not lacking concentration. Their 10 largest holdings represented 55.0% of assets, compared with 45.6% for top-decile managers. The difference was not concentration itself, but where that concentration was directed. Top-decile managers also exhibited stronger five-year earnings growth characteristics (25% versus 19%), while valuation differences were relatively modest. The evidence suggests that exposure to growth and market leadership mattered more than simply holding concentrated portfolios or paying higher multiples.
Table 2: Portfolio characteristics: Top decile vs bottom decile managers
| Metric | Top decile | Universe | Bottom decile |
| Average excess return | 5.43% | -2.17% | -10.15% |
| Top 10 holdings concentration | 45.6% | 44.1% | 55.0% |
| Weighted avg. market cap | 1,049,172 | 1,060,288 | 794,632 |
| Median market cap | 102,179 | 156,918 | 218,824 |
| Earnings growth, past 5-year | 25% | 19% | 19% |
| Technology weight | 35.6% | 31.0% | 23.2% |
| Financials / Healthcare | 20.8% | 24.9% | 30.5% |
| P/E trailing | 30.2% | 27.2% | 27.3% |
Source: Evestment. Data reflect average portfolio characteristics for S&P 500-benchmarked active strategies over the latest three-year period ending Q2 2026. Excess returns are net of fees; market-cap figures are in USD millions.
The active-passive implications are worth considering. In a capitalization-weighted benchmark, exposure to winning companies increases automatically as those companies appreciate and occupy a larger share of the index. As AI-related leaders drove returns and their benchmark weights expanded, passive investors naturally became more exposed to the market's dominant source of performance. The same process that strengthened returns, however, also left benchmarks dependent on a relatively small group of companies.
Active managers face a more explicit choice. They can embrace the market's leadership and accept greater concentration, or they can diversify away from it and risk underperforming while leadership remains narrow. That trade-off has become increasingly important in a market where the consequences of being underexposed to the dominant winners have grown considerably larger. For institutional investors, the key decision is not active versus passive, but the trade-off between participating in concentrated leadership and managing the risks that concentration inevitably creates
Source: Evestment, State Street Investment Management. Data as of 6/30/2026 unless otherwise stated. The performance data quoted represents past performance. Past performance does not guarantee future results. Investing involves risk, including the risk of loss of principal.
Skimmed the summary? Dive deeper with the full PDF—your go-to for weekly market insights and analysis.