For decades, investors have repeatedly encountered the same message: “Passive indexing outperforms active management.” Data showing that roughly 85% of active mutual fund managers underperform their benchmarks over 10-year periods reinforces this narrative, leading many investors to conclude that active investing itself is fundamentally flawed. This interpretation, however, is incomplete.

The evidence does not suggest that active management is ineffective. It suggests that most traditional active managers are not truly active, at least not in ways that research supports. A substantial body of empirical literature shows that certain forms of structured, risk-managed, systematic active investing can generate persistent alpha and superior long-term outcomes. The issue is not with the concept of active management; it is with how it is typically executed.

This article outlines why most traditional active managers underperform, what successful active strategies actually look like, the empirical evidence supporting effective active investing, what investors should seek in an active strategy, and how Thames Bridge implements these principles.

1. Why Most Traditional Active Managers Underperform

Traditional long-only active mutual funds face structural constraints that make consistent outperformance highly unlikely. These limitations stem from portfolio construction, incentive structures, and risk controls that favor benchmark replication over true active risk-taking.

1.1 Benchmark Hugging and Low Active Share

Career, business, and reputational risks encourage managers to stay close to their benchmarks. The result is low active share, where portfolios closely resemble index constituents. Petajisto (2010) demonstrates that managers with high active share outperform net of fees, while “closet indexers” systematically underperform. Low differentiation naturally leads to low potential for excess return.

1.2 Overexposure to Idiosyncratic Risk

Traditional active management relies heavily on stock selection, which introduces idiosyncratic risk, a company-specific uncertainty that markets do not compensate. Bessembinder (2017) shows that only approximately 4% of individual stocks explain all net wealth creation over nearly 100 years, the majority of stocks underperform Treasury bills, and most individual stock outcomes are negatively skewed. This means that a stock-picker concentrating capital into selected names is statistically unlikely to outperform a diversified benchmark over time.

1.3 Long-Only Constraints and Full Market Beta

Traditional funds cannot short securities or hedge exposures. As a result, portfolios remain fully exposed to broad market beta, highly vulnerable during downturns, and limited in their ability to isolate true alpha. This makes it difficult to produce consistent returns across varying market regimes.

1.4 Factor Exposure, Not Selection, Drives Most Returns

Factor models such as Fama–French and Carhart demonstrate that 70–95% of portfolio return variation can be explained by systematic exposures, including value, momentum, size, and quality. Many “active” managers unintentionally load on these factors while charging fees for stock selection that adds little value.

1.5 Fees Not Aligned With Delivered Active Risk

When portfolios mimic the benchmark, the investor pays active fees for passive exposures. After fees, this almost guarantees underperformance.

2. What Successful Active Strategies Actually Do

While traditional approaches often fail, research consistently shows that properly executed active strategies can outperform over time. These strategies share several defining characteristics.

2.1 Emphasis on Allocation, Not Stock Picking

Studies such as Brinson, Hood & Beebower (1986) and Ibbotson & Kaplan (2000) demonstrate that asset allocation explains 90–100% of long-term return differences. Successful active investors therefore emphasize multi-asset construction, balance factor exposures, and incorporate macro regime awareness. This approach minimizes idiosyncratic risk while maximizing systematic return drivers.

2.2 Systematic, Rules-Based Processes

Top-performing active strategies rely on quantitative, evidence-based decision-making rather than discretionary judgment. Common, well-researched factors include momentum, value, quality, low volatility, carry, and trend following. These factors have been validated across geographies, asset classes, and decades of market data. Systematic processes reduce emotional bias, ensure consistency, and improve repeatability.

2.3 Dynamic Risk Management

Research by Barroso & Santa-Clara (2015) and Moreira & Muir (2017) shows that volatility-managed factor portfolios meaningfully outperform static exposures. This occurs because risk is not constant. Adjusting exposure based on changing market conditions reduces drawdowns, enhances compounding, and produces higher Sharpe ratios. In this sense, risk management itself can be a source of alpha.

2.4 Use of Hedging or Long-Short Construction

Effective active strategies often incorporate the ability to hedge unwanted exposures, reduce market beta, isolate factor-driven alpha, and capture opportunities on both the long and short side. This flexibility allows portfolios to remain resilient across different macro environments.

2.5 Broad, Multi-Asset Diversification

Top-performing active approaches integrate exposures across equities, bonds, commodities, alternatives, volatility strategies, and macro indicators. More independent sources of return lead to more stable performance.

3. Evidence That Active Investing Works When Done Properly

A large base of empirical research supports the effectiveness of systematic, diversified, risk-managed active investing. This includes asset allocation research by Brinson, Hood & Beebower (1986) and Ibbotson & Kaplan (2000); factor-based excess return research by Fama & French (1993, 2015) and Carhart (1997); multi-factor alpha persistence documented by Asness, Moskowitz & Pedersen (2013); risk-managed outperformance shown by Barroso & Santa-Clara (2015) and Moreira & Muir (2017); and selection limitations identified by Bessembinder (2017) and Petajisto (2010).

Together, the evidence is clear: active investing can work when built on systematic, diversified, risk-aware foundations.

4. What Investors Should Look For in an Active Strategy

Sophisticated investors and advisors should prioritize high active share, meaning portfolios are meaningfully differentiated from benchmarks; a systematic, quantitative decision framework with transparent, rules-based methodologies supported by research; dynamic, real-time risk management that adapts to volatility and regime shifts; multi-asset and multi-factor diversification that broadens sources of risk premia and returns; hedging or long-short flexibility to reduce beta and isolate alpha; and fees aligned with delivered active risk, rewarding genuine value creation rather than benchmark replication. These characteristics define active management done right, a disciplined approach that combines evidence, structure, and transparency.

5. How We Applies These Principles

These principles form the foundation of our systematic investment philosophy. We believe successful active management begins with disciplined process design and rigorous risk control, not discretionary prediction.

Our systematic quantitative signals integrate multiple academically validated factors, including quality, value momentum, price momentum, carry, low volatility, and macro regime indicators. These signals systematically guide allocation and positioning with consistency and discipline.

Our dynamic risk management framework continuously adjusts portfolio exposure based on market volatility, macroeconomic conditions, cross-asset risk dynamics, liquidity, and trend signals. This adaptive approach aims to reduce drawdowns and strengthen long-term compounding.

We implement diversified exposures across U.S. and global equities, bonds, commodities, gold, alternatives, and hedging instruments where appropriate. This structure minimizes idiosyncratic risk and draws upon multiple structural return drivers.

Consistent with the evidence, we emphasize multi-asset and multi-factor allocation as a primary driver of long-term alpha, supported by transparent, repeatable execution.

Continuing the Conversation

The evolution of active management demands a shift from intuition and concentration toward empirical structure, diversification, and dynamic risk control. If you are an investor or advisor interested in exploring how systematic frameworks can enhance portfolio resilience and return consistency, Thames Bridge welcomes dialogue. We invite you to connect with our team for an evidence-based discussion on modern active strategies and how these principles might complement your existing approach.