Minimizing emotion, maximizing technology in investing

To navigate the growing complexities of equity markets, Fidelity Portfolio Manager Shashi Naik and his team rely on a cutting-edge, model-driven approach that blends active management with benchmark-relative risk management, aiming to reduce the influence of human emotion.

“By following a systematic approach, investments are guided not by guesswork, but by data, precision and innovation,” says Naik, who co-manages Fidelity’s comprehensive suite of Enhanced exchange-traded funds alongside Anna Lester and George Liu. “We believe objectivity, discipline and minimizing the human element are key to avoiding common investing pitfalls.”

The ETFs cover a broad range of equity categories, including U.S. large-, mid- and small-cap core, growth and value, as well as developed international and emerging markets. Leveraging proprietary research from a dedicated group of quantitative analysts and a robust risk-management framework – rather than relying primarily on individual judgment – Naik and team evaluate thousands of companies in seeking to identify evidence-based drivers of performance.

“A key point of differentiation is that traditional index-based offerings require investors to take the bad with the good,” he notes. “Our approach, by contrast, offers a more selective and thoughtful alternative.”

Naik adds that these ETFs don’t just track an index. Rather, they are built with a clear view of benchmark characteristics and risk, while incorporating proprietary return drivers – referred to as factors – to objectively evaluate securities and construct portfolios with favorable relative return opportunities.

He says the team’s approach is grounded in the belief that data and technology are essential to every aspect of investing. In practice, Naik says that their quantitative approach allows them to apply computational power to systematically uncover insights across a wide array of businesses, ultimately informing decisions about every stock within a fund’s investable universe.

“It’s important to underscore that this is not something that can be created overnight,” he affirms. “It is so much more than just a few smart signals or models. It also requires access to clean, reliable data from multiple sources, along with systems to manage, update and validate those inputs. Without that foundation, even the most sophisticated investment ideas can break down.”

As one example, Naik cites a signal that measures the sustainability of growth through the patent-filing process. Rather than relying solely on top-line metrics such as the number of patent filings, he and his co-managers dig deeper, using data to assess both the potential value of a company’s patent portfolio as well as the pace of innovation. They also can view this across multiple lookback periods to compare it with peers as well as the firm’s own history, he says.

At the same time, Naik acknowledges that there are moments when data does not capture the full picture, such as when unforeseen risks emerge or news developments rapidly shift the landscape.

“Those are the moments when a steady human touch can help, which is why an investment team provides daily oversight of the ETFs and makes adjustments when needed,” he adds. For example, during the 2021 meme-stock rally, the co-managers closely monitored and, in some cases, tightly managed holdings in stocks driven by social media fads, which made them quite challenging to evaluate quantitatively.

“One common criticism of quantitative investing is that data is available to everyone,” Naik concludes. “I would argue that access does not equal advantage. What truly sets managers apart is how they use the data. In our case, it reflects the team’s willingness and ability to make extensive – and often surprising – use of information rather than emotion, giving us greater control and a clearer understanding of why our strategies work.”

For specific fund information, including full holdings, please click on the fund trading symbol above.