Why Proprietary Quantitative Models in Active Small-Cap Equity Strategies Keep Failing

The underperformance of active small-cap equity strategies has become a persistent and well-documented phenomenon. According to a 2025 analysis, the Russell 2000 Growth Index surged 34.2% during a sharp market rebound in April 2025, while active small-cap growth funds lagged significantly. This gap was driven by managers' underweighting of high-beta stocks-those with the highest risk and reward potential-which delivered returns ranging from 89% to 236% during the rally. Over the past decade, only 31% of active small-cap growth funds outperformed the Russell 2000 Growth Index, a statistic that mirrors broader trends in active management. A 2025 SPIVA Scorecard report revealed that 94.1% of domestic funds underperformed the S&P 1500 Composite Index over the same period, underscoring structural challenges in active strategies across all market segments.

Structural Flaws in Quantitative Models

Proprietary quantitative models, often touted as a solution to the inefficiencies of discretionary management, have not fared better. A critical issue lies in their inability to adapt to shifting market dynamics. For instance, during mid-2025, long-short equity quant funds experienced sustained negative performance due to unusual correlations among factors like profitability, momentum, and liquidity. These interactions, which deviated from historical norms, exposed flaws in models that assumed linear relationships between variables. The problem was compounded by overfitting-models calibrated to historical data failed to account for real-world volatility, leading to poor out-of-sample performance.

Liquidity constraints further erode returns. Small-cap stocks, by nature, are less liquid, making it difficult for large institutional funds to execute trades without distorting prices. This is particularly problematic for high-frequency or algorithmic strategies, where timing and execution efficiency are paramount. Research highlights that over 40% of Russell 2000 constituents are unprofitable, compared to just 10% in the Russell 1000, exacerbating the challenge of identifying quality investments. Proprietary models that ignore these liquidity realities risk self-destructing, as seen in the 2025 "quant fund wobble," where forced liquidations of crowded positions amplified losses.

Market Concentration and Factor Misallocation

The dominance of large-cap stocks, particularly the "Magnificent Seven," has created a structural imbalance. By the end of 2024, the 10 largest stocks accounted for over half of the Russell 1000 Growth Index's market capitalization, leaving small-cap strategies with limited opportunities to capitalize on growth trends. Active managers using quantitative models often misallocate capital by underweighting high-beta stocks during rallies, as these stocks are perceived as too risky. Yet, as the 2025 rebound demonstrated, such stocks can drive outsized returns when market conditions shift.

Factor misallocation is another recurring flaw. For example, models that overweight profitability or momentum without considering liquidity or volatility have struggled during periods of market stress. A case in point is the underperformance of small-cap growth funds in 2021–2022, where companies with high price-to-book ratios but weak earnings dragged down returns. These models failed to adapt to a macroeconomic environment marked by rising interest rates and trade uncertainties, which disproportionately affected small, unprofitable firms.

The Path Forward

Despite these challenges, there are signs of potential recovery. Earnings growth for small-cap stocks has begun to narrow the gap with large-cap peers, and valuations are now near historic lows. However, success will require addressing the root causes of underperformance. First, quantitative models must incorporate dynamic factor interactions and liquidity metrics to avoid overfitting. Second, active managers need to focus on quality-prioritizing companies with strong balance sheets and sustainable cash flows, especially in volatile environments. Finally, as historical cycles suggest, a reversal in large-cap dominance could create opportunities for small-cap strategies that are nimble and well-constructed.

For now, the evidence is clear: proprietary quantitative models in active small-cap equity strategies are not immune to the structural flaws that plague active management broadly. Until these models evolve to account for liquidity, factor interactions, and market concentration, underperformance is likely to persist.