Active managers are struggling against the S&P 500 not just from bad picks, but because the market is dominated by a few AI stocks they can't fully concentrate in. Many also became too defensive during April's volatility, causing them to miss the subsequent sharp market rebound.
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Today's market is more fragile than during the dot-com bubble because value is even more concentrated in a few tech giants. Ten companies now represent 40% of the S&P 500. This hyper-concentration means the failure of a single company or trend (like AI) doesn't just impact a sector; it threatens the entire global economy, removing all robustness from the system.
The dominance of low-cost index funds means active managers cannot compete in liquid, efficient markets. Survival depends on creating strategies in areas Vanguard can't easily replicate, such as illiquid micro-caps, niche geographies, or complex sectors that require specialized data and analysis.
The underperformance of active managers in the last decade wasn't just due to the rise of indexing. The historic run of a few mega-cap tech stocks created a market-cap-weighted index that was statistically almost impossible to beat without owning those specific names, leading to lower active share and alpha dispersion.
Professional fund managers are often constrained by the need to hug their benchmark index to avoid short-term underperformance and retain clients. Individuals, free from this 'career risk,' can make truly long-term, contrarian bets, which is a significant structural advantage for outperformance.
Contrary to classic theory, markets may be growing less efficient. This is driven not only by passive indexing but also by a structural shift in active management towards short-term, quantitative strategies that prioritize immediate price movements over long-term fundamental value.
The current market is not a simple large-cap story. Since 2015, the S&P 100 has massively outperformed the S&P 500. Within that, the Magnificent 7 have doubled the performance of the other 93 stocks, indicating extreme market concentration rather than a broad-based rally in large companies.
Contrary to the belief that indexing creates market inefficiencies, Michael Mauboussin argues the opposite. Indexing removes the weakest, 'closet indexing' players from the active pool, increasing the average skill level of the remaining competition and making it harder to find an edge.
Massive AI capital expenditures by firms like Google and Meta are driven by a game-theoretic need to not fall behind. While rational for any single company to protect its turf, this dynamic forces all to invest, eroding collective profitability for shareholders across the sector.
The increased volatility and shorter defensibility windows in the AI era challenge traditional VC portfolio construction. The logical response to this heightened risk is greater diversification. This implies that early-stage funds may need to be larger to support more investments or write smaller checks into more companies.
Timing is more critical than talent. An investor who beat the market by 5% annually from 1960-1980 made less than an investor who underperformed by 5% from 1980-2000. This illustrates how the macro environment and the starting point of an investment journey can have a far greater impact on absolute returns than individual stock-picking skill.
