Produced in partnership with Robeco
Active quant strategies combine systematic investing with active flexibility to capture high, stable alpha in a risk-controlled, benchmark-aware manner. But unlike many benchmark-agnostic active funds, which might struggle when deviating too far from index heavyweights, active quant ensures balance – seizing opportunities for excess return without excessive deviation from the benchmark.
Active quant also provides a structured, research-backed approach that systematically captures market inefficiencies. It integrates insights from both traditional factors (such as value and momentum) and next-generation AI-powered signals, ensuring that portfolios remain adaptable to changing market conditions.
Robeco’s active quant strategies combine systematic investing with active flexibility to capture alpha systematically, identifying and capitalising on proven investment factors such as value, momentum, quality, and analyst revisions. And they allow risk control without sacrificing returns, ensuring benchmark alignment while generating targeted outperformance.
Integrating alternative data sources, AI-powered signals and machine learning models leads to enhanced decision-making. And it is transparent – it’s not a black box. Every investment decision is fully research-backed and explainable. A multi-layered active-quant approach adapts dynamically to evolving markets.
Navigating today’s challenges and opportunities
The dominance of a few mega-cap tech stocks in market indices presents a challenge. Passive investors are unavoidably fully exposed, whereas active managers run the risk of underweighting these stocks too aggressively. Active quant balances benchmark awareness with factor-based stock selection, ensuring investors don’t fall behind in market trends, while also capitalising on opportunities for alpha.
The integration of AI-driven stock selection and next-generation alternative data sources is reshaping the investing landscape. Active quant leverages machine learning insights, such as job momentum tracking and sentiment analysis from earnings calls, to provide a cutting-edge advantage in stock selection. This approach enables active quant to stay ahead of the pack.
Institutional investors need strategies that meet both financial and sustainability objectives amid rising ESG mandates. Active quant offers customisable sustainability integration while monitoring ESG risks, ensuring that investment strategies are both responsible and effective.
Robust risk control
Unlike high-conviction active funds that hold 20 to 50 stocks, active quant maintains 200 to 250 holdings, ensuring greater diversification and stability. This approach reduces stock-specific risk, crucial for superannuation funds managing large portfolios, while still aiming for an expected excess return of 2.5 per cent, striking the ideal balance between active stock selection and controlled risk exposure.
By combining long-term factors such as value and quality with dynamic AI-driven signals, active quant provides a structured, repeatable approach to alpha generation that is adaptable to varied market conditions.
Active quant integrates AI, alternative data and machine learning, but it is not run by machines alone. Researchers and portfolio managers continuously refine and validate the models, ensuring they remain relevant, effective and risk-aware. Combining cutting-edge technology with deep human expertise means active quant offers confidence in both the process and the outcomes.
Customisation
Australian institutional investors have unique priorities, including return profiles, sustainability integration, and risk management. Active quant can be tailored to meet specific risk-adjusted return targets; ESG and climate-conscious investment mandates; and regional or sector-specific allocation preferences.
This customisability ensures that active quant fits seamlessly into institutional portfolios, complementing existing investment approaches while providing a structured, repeatable source of alpha.
Active quant strategies provide benchmark-aware, systematic approaches to alpha generation as a resilient, cost-effective complement to fundamental active investing. It employs AI-enhanced signals to uncover new sources of return and allows ESG integration for investors with a responsible investment outlook.
With a proven track record, deep quant expertise and transparent investment processes, active quant delivers a smart, adaptable way forward for institutional investors.
Rob Huisman is a client portfolio manager in quant investing at Robeco, based in Hong Kong, covering the APAC region, including Australia.
