AllianceBernstein sees demand for steadier alpha as concentrated markets challenge traditional active management
As global equity markets become more concentrated, investors are questioning whether traditional active management can still deliver consistent excess return. For AllianceBernstein, the answer is not to abandon fundamental research, but to combine it more deliberately with systematic portfolio construction.
Aditya Monappa, global head of multi-asset & hedge fund solutions business development at AllianceBernstein (AB), says interest in lower tracking error strategies and quantitative approaches has risen over the past 12 to 18 months, particularly among institutional investors. The appeal is being driven by a market environment in which beta may be less reliable and active managers are under pressure to show that returns are coming from genuine stock selection, rather than unintended exposure to factors, sectors or mega-cap stocks.
“There is a lot more focus on quantitative or systematic approaches to investing,” Monappa tells Asia Asset Management, adding that the volume of conversations around this type of approach has “increased dramatically”.
A key driver is market concentration. While the US is often cited as the clearest example, Monappa notes that concentration is also evident in markets such as Taiwan and Korea, where the artificial intelligence rally has driven momentum in a relatively narrow group of companies. Investors may be uncomfortable with that concentration, but they are also reluctant to miss out on returns from dominant AI-linked names.
Monappa argues that the next three to five years may be more challenging for equity beta than the period since the global financial crisis. Risk assets have delivered strong long-term returns, despite interruptions such as Covid-19 and the 2022 rate shock. Looking ahead, he believes investors may need to work harder to achieve their return objectives.
“If you’re an institutional investor or even a retail investor and you have a target return in mind, the beta is maybe not going to get you your target return,” he says. “What’s going to matter more is how you find that alpha.”
That is the context for AB’s lower-tracking-error solutions that use AB’s fundamental research as an input but applies a quantitative overlay to portfolio construction.
AB says the strategies use fundamental research alongside quantitative optimisation tools to build a diversified portfolio seeking attractive and consistent returns while managing active risk.
Monappa says this matters because traditional active managers have found it harder to outperform in developed equity markets. He cites AB research showing that, in the five years ending 2010, around 82% of active managers in a large-cap core equity universe outperformed their benchmark. In the five years ending 2025, that figure had fallen to around 36%.
The problem, he argues, is not necessarily poor stock picking. Rather, many active portfolios carry structural biases towards particular sectors, styles or factors. When factor leadership rotates sharply, those embedded biases can overwhelm stock-level insight.
Lower-tracking-error strategies are designed to address that problem. “The inputs are still the very strong fundamental research done by our research teams,” Monappa says. “But there is a quantitative overlay, or systematic overlay, to building the portfolio.”
Monappa does not present quantitative investing as a replacement for fundamental research. During Covid-19, he says, purely systematic strategies struggled because they relied heavily on historical data that did not contain a comparable modern pandemic episode. In 2022, when interest rates rose sharply, systematic strategies adapted more effectively because they had fewer embedded biases.
For Monappa, this supports a hybrid process. Fundamental research can assess business models, earnings durability and company-level change, while systematic tools can help control unintended exposures and construct portfolios more consistently.
Looking ahead, he identifies artificial intelligence and geopolitics as two dominant themes shaping equity markets. On AI, he believes the trend is materially different from the late-1990s technology bubble because many AI-linked companies are already generating tangible earnings and cash flows. However, he cautions that the eventual winners may look different from today’s market leaders, reinforcing the need for agility and active research.
Geopolitics is also reshaping opportunity sets. Monappa points to a multi-year shift towards deglobalisation, supply-chain security and localised manufacturing, creating opportunities linked to energy, critical minerals and commodities.
For AB, lower-tracking-error strategies sit within a broader shift in how investors pay for skill. As data availability, computing power and portfolio analytics improve, Monappa expects systematic approaches to become a larger part of institutional portfolios.
“This isn’t a short-term trend,” he says. “You’re likely to see more and more allocators and asset owners make this a larger part of their portfolio.”
