The louder the narrative, the stronger the case for systematic investing

Please note, this interview was recorded Wednesday, 15 April 2026

The Shawshank Redemption is one of my favourite movies of all time, and one of its most poignant moments arrives following Brooks Hatlen's release after 50 years in prison. He reflects on a world that has moved on without him.

“The world went and got itself in a big damn hurry.”

I don't know about you, but right now, across markets and beyond, that observation feels uncomfortably accurate. AI, geopolitics, energy shocks, and an explosion in both the volume and speed of data are reshaping the investment landscape at a pace few could have imagined even a decade ago. For investors, the challenge is no longer access to information, but the ability to interpret it - and, critically, to separate signal from noise.

Because if there is one thing markets consistently prove, it is that humans are not particularly good at this task. As Franklin Templeton’s Subash Pillai puts it:

“I think we have got excited about 10 of the last five new things… and for those five that were real, we probably got under-excited.”

That behavioural mismatch - overreacting to noise and underreacting to signal - is precisely the problem systematic investing is designed to solve.

“What systematic investing does is it does not take a view on the narrative itself. It looks at what is happening in the data.”

In this interview, we explore how that process works in practice, where it excels, and why it may be more relevant than ever in today’s market.

INTERVIEW SUMMARY

Why narrative-driven markets favour systematic investing

Markets today are increasingly shaped by powerful narratives. While these themes can drive sharp price movements, Subash Pillai argues they often lead investors astray.

“When you have a very strong narrative, people can get swept up in that story. Quite often there is a lot of hype to some of these situations.”

Rather than trying to predict which narratives will endure, Franklin Templeton’s systematic approach focuses on whether those stories are showing up in the data. That includes tangible metrics such as margins, earnings revisions, and the breadth of impact across industries.

In Pillai’s view, that discipline is particularly relevant in today’s market, where mega-cap concentration has become a defining feature. Rather than taking an explicit stance for or against those names, the process seeks to neutralise that exposure and let the underlying signals determine positioning.

According to Pillai, this has become a recurring theme in conversations with allocators, many of whom are grappling with increasingly concentrated benchmarks.

This creates a key advantage. While systematic strategies may not capture the very start of a thematic move, they are designed to participate in the majority of it once the underlying data confirms its validity. Just as importantly, they avoid being drawn into themes that ultimately fail to translate into real outcomes.

The edge lies in breadth and consistency

At the heart of the approach is scale. Pillai highlights that systematic investing enables the firm to process information across thousands of companies simultaneously.

“We are every day using our factor models to look at new information for thousands of companies… and the model does not get tired, the model does not get sick… and it is unemotional.”

This breadth allows the model to identify subtle trends that would be difficult for human investors to detect. Importantly, it is not about one single signal, but the aggregation of many small signals.

“While statistically one factor improving by a small amount is nothing, it is very powerful when it is 15 factors all improving a little bit.”

Combined with discipline and repeatability, this creates a process that is both scalable and consistent - two attributes that are difficult to maintain in discretionary investing.

Finding patterns others cannot see

A defining feature of the framework is its ability to bring together multiple factors - including quality, value, sentiment, and alternative data - into a cohesive signal.

“Those individual signals on their own are not enough to act on, but when you see them confirmed across the full range of factors… that is where the edge emerges.”

This includes more advanced techniques such as textual analysis, where the model evaluates company disclosures, earnings calls, and management commentary. One practical application is assessing whether companies prioritise organic growth or acquisitions, a distinction that has been shown to influence long-term performance.

By combining these inputs, the model can uncover insights that are both nuanced and difficult to replicate through traditional fundamental analysis.

Adapting to change without losing discipline

A common critique of systematic investing is that it can struggle during regime shifts. Pillai counters this by outlining how the process is designed to evolve.

First, factor diversification ensures that no single driver dominates performance. Quality, value, and sentiment each play a role, and tend to perform differently across market environments.

Second, continuous validation ensures that factors remain relevant. The team constantly reviews existing signals and researches new ones, recognising that models must adapt as markets change.

“If you have a static model that does not change, the market catches up.”

Finally, diversification at the portfolio level ensures that risks are spread across multiple dimensions, reducing reliance on any single outcome.

Redefining risk in a systematic framework

Perhaps the most notable distinction lies in how risk is defined. For Pillai, risk is not volatility or benchmark deviation in isolation.

“We see risk as the amount of expected tracking error that we cannot explain by our factors.”

This shifts the focus to unintended exposures - positions that fall outside the model’s defined sources of edge. As a result, the portfolio is constructed with tight controls across regions, sectors, and other dimensions unless there is a clear rationale to take risk.

This discipline was particularly evident during periods of shifting macro conditions, where the team focused on identifying and mitigating exposures to potential losers rather than making directional bets.

The role of AI and the human investor

While technology plays a central role, Pillai is clear that AI is not replacing human decision-making.

“AI enables us to do things more efficiently… but it is not taking away decision rights from humans.”

Instead, it enhances the process by improving data quality, accelerating analysis, and enabling more robust testing. Humans remain responsible for defining the problem, interpreting outputs, and making final decisions.

Where systematic investing fits in portfolios

For investors, the question is not whether systematic investing works, but where it fits. Pillai’s answer is clear: it belongs at the core.

“Systematic strategies sit at the core of your equity portfolio”

Using a cricket analogy, he describes systematic strategies as the reliable bowler delivering consistent performance, providing stability and diversification across market regimes.

Around that core, investors can layer more active or thematic strategies, creating a portfolio that balances consistency with opportunity.

Managed Fund

Franklin Global Systematic Equity Fund

Global Shares

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