Quantitative strategies are proving to be a powerful tool for diversification in fixed income portfolios, offering portfolio managers access to new sources of alpha while enabling efficient decision-making, according to Patrick Duplessis, fixed income portfolio manager at Trans-Canada Capital Inc.
Speaking at the Canadian Investment Review’s 2024 Investment Innovation Conference, he described quantitative strategies as rules-based, systematic and automated models that provide several advantages. Indeed, he noted they excel at optimizing processes, analyzing large datasets and reacting quickly to changing market environments.
“Portfolio managers are biased, but computers and models aren’t. We use quantitative models in our portfolios as an ally to catch different patterns or to execute different types of strategies in order to tackle and benefit from different sources of alpha — of value-added — into our portfolios.”
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However, successfully integrating quantitative models into a fixed income portfolio requires careful consideration, said Duplessis. The model selection process involves evaluating multiple factors, including the investable universe, volatility and other constraints, to ensure compatibility with the portfolio’s objectives. Additionally, he noted that analyzing model output, such as the information ratio, maximum drawdown and duration, is critical to determine their suitability.
He outlined two primary approaches to implementing quantitative models: quantitative investment strategies and proprietary models. QIS are pre-packaged solutions typically offered by third-party providers. In contrast, proprietary models are custom-built, providing a more personalized and controlled approach.
“Proprietary is usually our favourite implementation method because everything is built in house. You have control over the parameters, the signals, the universe, everything. It’s a tailored solution. . . . It’s also easier for us to maintain and to provide enhancements to these models.”
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That said, opting for QIS models can be practical, said Duplessis, particularly given the vast array of options available in the fixed income space, which includes more than 1,300 models.
In addition, when choosing between QIS and proprietary solutions, cost is a significant factor. He emphasized the importance of running comprehensive backtests to validate the strategy, ensure reasonable trading and assess the impact of fees. He also cautioned institutional investors to monitor for crowding, a phenomenon more common in QIS models where popularity can lead to alpha decay, as well as to negotiate the costs of the strategy with the providers.
Regardless of the implementation approach, Duplessis stressed the importance of a substantial time commitment and dedication from the investment team. These strategies require strong oversight, but deliver significant benefits. By eliminating behavioural biases and fostering diversification, quantitative strategies serve as invaluable allies for portfolio managers.
Read more coverage of the 2024 Investment Innovation Conference.