Smarter alpha: Get more from a portfolio’s core

Modest fees and more than a decade of strong market returns have made passive strategies that track large‑cap equity indexes simple and increasingly common building blocks for the core of a diversified investment portfolio.

But passive exposure to the broader market comes at an opportunity cost: alpha, or potential outperformance relative to the benchmark.

How can investors get more from their portfolio’s core while accounting for risk and expense budgets?

A well‑designed active-core strategy could help clients use portfolio capital more efficiently by adding the potential for consistent, risk‑adjusted alpha.

Why a little alpha from a portfolio’s core can make a big difference

The core/satellite approach to equity portfolio construction has become a common structure for investors to help balance expense and risk budgets as they pursue long‑term financial objectives.

Within this framework (Figure 1), the core typically consists of a strategic mix of passive funds that offer the prospect of a low‑cost, market‑like return. As the largest part of the portfolio, the core aims to limit fee‑related performance drag while alleviating the challenge of picking the right active manager. It also avoids the potential for subpar returns versus a benchmark. Satellite strategies orbiting this core take more active risk in the pursuit of stronger outperformance.

As passive‑core exposures have grown, so has the opportunity to use this portfolio capital more effectively. Producing even a modest excess return from a core allocation can make a significant difference to an investor’s long‑term outcome.

Our analysis, for example, suggests that an additional 25 basis points (bps) in return over 40 years of savings could result in an additional two years of retirement spending. Increasing the excess return to 50 basis points could add five additional years of spending (Figure 2).

In this instance, the frequency of outperformance is key to compounding value. When applied to such a large base of portfolio capital over longer time frames, the prospect of generating steady, if not necessarily heady, excess returns can be very compelling.

How risk-controlled alpha can add value vs. passive index trackers
Clients who want to get more from their portfolio’s core can choose from a small but growing universe of active-core strategies that seek to integrate the best attributes of active and passive investing:

1. Alpha potential: An active and repeatable investment process is built on a source of edge/insight that creates the potential for excess returns across different market environments.

2. Controlled, but active risk: Targeting 50 to 100 basis points in tracking error can help with consistency versus a benchmark and to minimize exposure to factor hot spots. It also has the potential to reduce the risk of underperforming the benchmark by a wide margin.

3. Competitive fees: An affordable expense ratio lowers the drag on potential returns.

For prospective investors, the critical question is whether the underlying investment engine can consistently generate benchmark‑plus returns with minimal active risk.

The power of an investment engine with two alpha drivers

Markets are dynamic and continually evolve. But recurring behavioral biases can lead to persistent market inefficiencies.

• Shrinking time horizons: As markets increasingly focus on short‑term outcomes, the resulting dislocations can create favorable risk/reward setups for investors who focus on what creates value over the longer term.
• Perspective skew: Markets often struggle to properly weigh inside and outside views. The inside view uses the specifics of an individual situation to understand what’s likely to happen; the outside view uses relevant historical precedents to understand the most likely outcome.

We believe an investment engine that integrates two distinct but complementary sources of insight—deep fundamental research and rigorous quantitative analysis—should be well positioned to take advantage of these inefficiencies in the pursuit of consistent, risk‑adjusted alpha.

• Fundamental research: Talented analysts with a deep understanding of individual companies’ growth prospects should be well positioned to add value when uncertainty is high or there is a wide dispersion of returns in an industry or sector. This inside view provides expert insight and forward‑looking judgment, which can be a difference‑maker in fast‑changing areas such as artificial intelligence (AI) or biotechnology.
• Quantitative analysis: Rigorous analysis of historical market and financial data related to key factors such as growth durability, business quality, capital deployment, momentum, and valuation provides an outside view. This data‑driven approach adds empirical grounding, pattern recognition, and behavioral discipline to the investment process.

With this design, performance isn’t the result of a single lens or philosophy but rather two independent investment approaches that can be even more powerful when combined.

Thoughtfully integrating fundamental and quantitative analysis helps to reduce blind spots, challenge assumptions, and improve investment decision‑making across market cycles.

Pursuing alpha while limiting tracking error

Low-tracking-error strategies seek to provide a similar risk profile to the benchmark while allowing diversified stock picking to drive relative returns.

By design, these products don’t make large, concentrated bets. Instead, smaller overweight and underweight positions are spread across a broad universe of securities. The sizes of these active bets, which are tightly controlled to limit tracking error, reflect the level of confidence in the investment thesis.

For a strategy that systematically integrates fundamental and quantitative analysis, conviction could reflect the convergence of the two approaches:

• Overweight: Stocks where both the analyst and the quantitative rating suggest a favorable risk/reward profile.
• Underweight: Companies whose fundamental and quantitative ratings appear less favorable.

When only a quantitative rating is available, the hurdle for making a meaningful active bet in a stock should be higher.

Limiting position sizes is only one way to limit tracking error. Guarding against unintended risks or style biases in the portfolio is also critical.

Managers backed by strong fundamental research and quantitative teams may be better positioned to spot and adjust to evolving risk factors where clusters of stocks start to trade in a similar manner. Some of these correlations can be related to macroeconomic developments, such as the direction of interest rates or where a company generates its earnings. In other instances, dislocations may emerge in companies with negative earnings or groups of stocks that offer exposure to popular themes, such as AI, nuclear power, or space technology.

Balancing individual alpha opportunities with top‑down risk management requires constant vigilance.

Choosing the right partner: Scale, culture, and capabilities

A strategy that has the potential to generate excess returns consistently without taking on too much tracking error can create material advantages as a core portfolio holding.

Evaluating the people and process is critical to identifying solutions with the potential to deliver above-benchmark returns with benchmark-like risk. We believe that well‑designed active-core strategies that combine human and machine insights—two distinct sources of potential alpha—should be well positioned to compound long‑term value. 

A global asset manager with demonstrated fundamental and quantitative investment capabilities should have an advantage in creating core strategies that meet clients’ needs for potential returns, risk, and cost—think of this as smarter alpha.