Active Investing Done Right: Why Most Managers Fail and What Actually Works: An Evidence-Based Perspective for Advisors and RIAs

The evidence does not suggest that active management is ineffective.
It suggests that most traditional active managers are not truly active or at least not in ways supported by empirical research.

A substantial body of academic and practitioner literature demonstrates that structured, risk-managed, systematic active investing can generate persistent alpha and superior long-term outcomes. The issue lies not with active management as a concept, but with how it is typically implemented within traditional products.

This article outlines:

• Why most traditional active managers underperform.

• What successful active strategies actually look like.

• The empirical evidence supporting effective active investing.

• What advisors should evaluate when selecting active strategies.

• How Alamut Capital applies these principles in practice.

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 norms, incentive structures, and risk controls that favor benchmark replication over genuine active risk-taking.

1.1 Benchmark Hugging and Low Active Share

Career risk, business considerations, and reputational concerns incentivize managers to remain close to 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.

For advisors, this creates a structural problem: low differentiation leads to low potential for excess return, while clients still pay active fees.

1.2 Overexposure to Idiosyncratic Risk

Traditional active management often relies on concentrated stock selection, introducing idiosyncratic risk/company-specific uncertainty for which markets do not compensate investors.

Bessembinder (2017) shows that only ~4% of individual stocks explain all net wealth creation over nearly 100 years. The majority of stocks underperform Treasury bills and are highly negatively skewed.

For advisors, this highlights a key challenge: concentrated stock selection is statistically unlikely to outperform diversified benchmarks over time, particularly on an after-fee basis.

1.3 Long-Only Constraints and Full Market Beta

Most traditional funds lack the ability to short securities or hedge exposures, leaving portfolios fully exposed to broad market beta. This structural limitation makes them particularly vulnerable during market drawdowns and significantly restricts their ability to isolate true alpha, as performance becomes largely driven by overall market movements rather than skill-based return generation.

This makes consistent performance across varying market regimes difficult, particularly when managing client expectations through market cycles.

1.4 Factor Exposure, Not Selection, Drives Most Returns

Factor models such as Fama–French and Carhart demonstrate that approximately 70–95% of portfolio return variation is driven by systematic factor exposures such as value, momentum, size, and quality rather than individual security selection. As a result, many traditional “active” managers end up implicitly loading on these common factors while charging fees for discretionary stock picking that delivers little incremental value beyond what systematic exposure already provides.

1.5 Fees Not Aligned With Delivered Active Risk

When portfolios closely track benchmarks, clients effectively pay active fees for passive exposures. From an advisory perspective, this almost guarantees underperformance after fees and creates long-term client dissatisfaction.

2. What Successful Active Strategies Actually Do

Despite widespread underperformance among traditional funds, research consistently shows that properly constructed active strategies can outperform over time. These strategies share several defining characteristics.

2.1 Emphasis on Allocation, Not Stock Picking

Seminal studies by Brinson, Hood & Beebower (1986) and Ibbotson & Kaplan (2000) demonstrate that asset allocation explains 90–100% of long-term return differences.

Successful active approaches therefore focus on multi-asset portfolio construction, deliberately balance factor exposures, and incorporate awareness of macroeconomic and market regimes. This structure allows portfolios to reduce reliance on any single return driver while adapting more effectively to changing market conditions.

For advisors, this approach reduces idiosyncratic risk while maximizing exposure to systematic return drivers.

2.2 Systematic, Rules-Based Processes

Top-performing active strategies rely on quantitative, evidence-based frameworks rather than discretionary judgment, systematically allocating capital to well-researched factors such as momentum, value, quality, low volatility, carry, and trend following, which have been validated across asset classes, geographies, and long-term market cycles.

These factors have been validated across asset classes, geographies, and decades of data. Systematic implementation enhances consistency, transparency, and repeatability, a key consideration for advisors.

2.3 Dynamic Risk Management

Research by Barroso & Santa-Clara (2015) and Moreira & Muir (2017) demonstrates that volatility-managed portfolios outperform static exposures.

Adjusting portfolio exposure as risk conditions change helps reduce drawdowns, improves the power of long-term compounding, and enhances overall risk-adjusted returns by aligning risk-taking more closely with prevailing market conditions.

In this context, risk management itself becomes a source of alpha, not merely a defensive tool.

2.4 Hedging and Long-Short Flexibility

Effective active strategies often include 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 improves resilience across market environments—an important consideration for advisors managing client capital through cycles.

2.5 Broad, Multi-Asset Diversification

Top-tier active strategies integrate exposures across equities, fixed income, commodities, alternatives, volatility strategies, and macro-driven signals. By drawing on a broader set of independent return sources, these portfolios tend to deliver more stable outcomes over time, improving the client experience and supporting stronger long-term retention.

3. Evidence That Active Investing Works When Done Properly

A substantial body of empirical research supports systematic, diversified, and risk-managed active investing:

• Asset Allocation: Brinson, Hood & Beebower (1986); Ibbotson & Kaplan (2000)

• Factor-Based Excess Returns: Fama & French (1993, 2015); Carhart (1997)

• Multi-Factor Alpha Persistence: Asness, Moskowitz & Pedersen (2013)

• Risk-Managed Outperformance: Barroso & Santa-Clara (2015); Moreira & Muir (2017)

• Selection Limitations: Bessembinder (2017); Petajisto (2010)

The evidence is clear: active investing can add value when grounded in systematic design, diversification, and risk control.

4. What Advisors Should Look For in an Active Strategy

When evaluating active strategies for client portfolios, advisors and RIAs should prioritize:

• High active share – Meaningful differentiation from benchmarks

• Systematic, quantitative framework – Transparent, research-backed methodologies

• Dynamic risk management – Adaptive exposure to volatility and regime shifts

• Multi-asset and multi-factor diversification – Broader return drivers

• Hedging or long-short capability – Reduced beta and improved alpha isolation

• Fees aligned with delivered active risk – Compensation for genuine value creation

These characteristics define active management done right.

5. How Alamut Capital Applies These Principles

At Alamut Capital, these principles form the foundation of our systematic investment philosophy. We believe effective active management begins with process discipline and rigorous risk control, not discretionary forecasting.

Systematic Quantitative Signals

Our models integrate academically validated factors, including:

• Quality

• Value momentum

• Price momentum

• Carry

• Low volatility

• Macro regime indicators

These signals guide allocation decisions consistently and transparently.

Dynamic Risk Management

Our risk framework continuously adjusts exposure based on volatility, macroeconomic conditions, cross-asset dynamics, liquidity, and trend signals—aiming to reduce drawdowns and enhance long-term compounding.

Multi-Asset Diversification

We implement diversified exposures across U.S. and global equities, fixed income, commodities, gold, alternatives, and, where appropriate, hedging instruments. This structure minimizes idiosyncratic risk while drawing on multiple structural return drivers to support more resilient portfolio outcomes.

Allocation as a Core Alpha Source

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

Continuing the Conversation

The evolution of active management requires a shift—from intuition and concentration toward evidence-based structure, diversification, and dynamic risk control.

For advisors and RIAs exploring how systematic frameworks can enhance portfolio resilience and return consistency, Alamut Capital welcomes dialogue. We invite you to engage with our team for an evidence-based discussion on modern active strategies and how these principles may complement your existing practice.