The impressive performance of mega-cap tech stocks has reshaped factor returns, leading systematic investors to rethink their strategies, according to Invesco’s ninth annual Global Systematic Investing Study (IGSIS).
Drawing insights from 131 institutional and wholesale investors managing $22.3 trillion, the study has shown that investors are adapting quickly to market shifts and are increasingly sophisticated in their use of systematic strategies.
Tech-dominated factors like momentum, growth and quality have excelled over the past year, while value lagged. Now, amid concentration risks, over half of investors (52%) have increased allocations to value as a potential hedge. This response highlights the ongoing need for strategic recalibration in a tech-driven market.
According to Georg Elsaesser, senior portfolio manager at Invesco, the recent tech surge has underscored the importance of risk management in factor strategies, noting a distinction between “momentum in a few large stocks” versus a broader momentum factor premium.
Systematic investors are further bolstered by adaptable strategies, with 46% reporting outperformance compared to traditional active and market-weighted strategies, contrasting with underperformance rates of just 8% and 6% respectively. Adaptability has become crucial, with 80% of investors valuing factor tilting, while 67% emphasize asset class rotation to stay responsive to macroeconomic changes.
When human expertise meets machine-learning
The study also pointed to an evolving preference for shorter investment horizons. Although 40% of investors still evaluate performance over a 3-5 year period, a notable 32% have shifted to a 2-3 year view, up from 23% last year.
Invesco’s findings reveal diversification trends within systematic portfolios, particularly with alternative asset classes. Now, 40% of investors apply systematic strategies to real estate, 36% to commodities, and 34% to private equity and infrastructure, helping build integrated, multi-asset portfolios. However, less liquid assets bring liquidity challenges, addressed with tools like liquid proxies or derivatives to enable dynamic rebalancing.
Finally, the study highlights the “data revolution” in systematic investing, with alternative data sources such as satellite and shipping data increasingly informing portfolio decisions. AI, viewed as transformative for systematic strategies, is gaining traction for its data-processing abilities, although challenges like data quality and security remain. Elsaesser sees AI as key to systematic investing’s evolution, offering “rapid insights” and potential sustainable alpha, yet tempered by ongoing challenges in the field.
