Contrary to conventional wisdom, the massive flow of capital into passive indexes and short-term systematic strategies has reduced the number of actors focused on long-term fundamentals. This creates price dislocations and volatility, offering alpha for patient investors.

Daniel Gladys argues that as passive investing grows, fewer participants focus on fundamentals. This widens the gap between a stock's price and its intrinsic value, creating a favorable environment for disciplined value investors who can identify these overlooked opportunities.

Many investments labeled "value traps" aren't bad picks but are simply taking longer than expected to mature. During this latency, the business's fundamentals and earnings potential can actually improve, making it a better investment.

Contrary to popular belief, the market may be getting less efficient. The dominance of indexing, quant funds, and multi-manager pods—all with short time horizons—creates dislocations. This leaves opportunities for long-term investors to buy valuable assets that are neglected because their path to value creation is uncertain.

The central task for capital allocators is to identify investment managers with a proven, durable edge—be it in sourcing, operations, or strategy—that allows them to consistently capture alpha in markets that are otherwise becoming more efficient.

The UK market is characterized by cheap valuations, poor corporate governance, and low insider ownership. These factors often trap value investors, with private equity takeovers being the primary catalyst for realizing returns, as organic market mechanisms fail to correct undervaluation.

Today's markets are less efficient because the dominant players—passive funds, retail traders, and short-term quants—do not invest based on long-term fundamentals. This creates a significant arbitrage opportunity for investors who are willing to focus on a company's intrinsic value over a one- to three-year horizon, a timeframe now largely ignored.

David Kaiser of Methodical Investments posits a contrarian view on AI's market impact. Instead of creating perfect efficiency, he argues AI and the data it processes might actually create more mispricings and inefficiencies. This provides opportunities for disciplined, rules-based strategies that don't constantly adapt to short-term noise.

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.