Systematic Active Fixed Income: A Straightforward Guide to the SAFI Investment Process
SAFI (the “Strategy”) employs a quantitative approach to alpha generation that is both rules based and data-driven.
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SAFI: A Modern Approach to Fixed Income Investing
Quantitative signals in the form of factor scores are used to drive security selection, while the Strategy also seeks to maintain structural risk alignment with the underlying benchmark. In this way, the Strategy seeks to generate alpha, predominantly from security selection. This approach ensures not only a high consistency in the security selection decision, but also does this rapidly and at scale, essentially evaluating thousands of securities simultaneously to identify and harness alpha potential. Furthermore, with the ability to integrate sustainability considerations such as climate into the security selection decision, SAFI can deliver this attractive alpha potential while aligning with any client-specific sustainable investment preferences and objectives.
Our systematic, factor-based approach has been applied to identify investment opportunities across the full credit spectrum from investment grade to high yield. The approach capitalizes on the much improved pricing transparency and frequency of today’s credit markets, that has been facilitated by the improvements in electronic trading. A systematic approach, being both quantitatively driven and rules based, is different from the majority of existing active fixed income strategies, which are highly qualitative and rooted in fundamental analysis. These differences in approach drive very different outcomes in the form of differentiated return streams, and this is one of the key attractions of systematic strategies. It is not just the level of alpha they can potentially generate, but it’s the way in which it is generated, which has shown to provide attractive manager diversification benefits for investors.
The quality of the factor research is a critical element underpinning any quantitative approach, and that is why we at State Street Global Advisors have partnered with arguably one of the most experienced and respected quantitative research teams in fixed income, namely Barclays Quantitative Portfolio Strategy (QPS). Each day, Barclays QPS provides us with factor scores delivered through custom systematic strategy indices that we combine with our expertise in precise portfolio construction and efficient implementation. As a result, we believe that we have an unrivaled combination that can convert this robust theory into practice through portfolios that are constructed to generate attractive yet differentiated return streams.
Through this collaboration with Barclays QPS (see: Introduction to Barclays QPS), State Street Global Advisors combines its own robust portfolio management and execution expertise with advanced factor research to offer a comprehensive suite of systematic active strategies.
The Backbone of the Strategy
The SAFI investment process and alpha generation is underpinned by three key signals, or factors:
Quantitative Signals Can Identify Outperformance Opportunities in Fixed Income
* Peer group categories such as sector, rating and maturity control for systematic risk.
Source: State Street Global Advisors, Barclays QPS, as of March 20, 2025.
By systematically applying informative signals to identify mispriced securities, SAFI aims to implement portfolios that are poised to outperform standard benchmarks in a consistent, unbiased and structured manner.
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Our new piece details the investment process behind SAFI and explains how it puts proven, data-driven factors to work to generate alpha. The piece summarizes the SAFI investment process, explains the alpha factors that drive credit returns, and provides insights into the integration of climate criteria.
The Investment Process in Steps
The Strategy employs a systematic, algorithmic approach to evaluate all securities in the investment universe based on their exposure to each factor. It aims to maximize exposure to those factors in an efficient and practical way.
Signal Generation
Signals for the three factors—value, momentum and sentiment — are delivered daily by Barclays QPS for each bond in the benchmark through custom systematic strategy indices. Each bond in the investment universe receives four scores: one for each factor and a composite score.1
The performance contributions of each signal vary over time due to differences in their characteristics and behaviors. The value signal is the primary contributor to active risk during “normal” market environments, while the momentum signal plays an important complimentary role (both in terms of risk and alpha during periods of heightened volatility). In contrast, the sentiment (ESI) signal, which is predominantly used to screen out issuers with high short interest, has a relatively small contribution at the overall portfolio level compared to value or momentum. This is because few names in the corporate index are actively shorted by equity investors at any one time. Excluding these issuers is an effective way to limit downside risks.
Portfolio Construction
Our rules-based portfolio construction is guided by three main principles:
- Optimal portfolio exposure to the factors
- Control for unintended risks relative to the benchmark index
- Execute efficiently
Securities are selected based on their exposure to factor scores, with the portfolio optimized to balance potential returns against risk constraints while ensuring effective execution with low transaction costs. The less liquid portion of index constituents are excluded from the eligible universe based on bond-level liquidity analytics such as traded volumes and bid-offer spreads.2
The investor’s specific objectives and constraints are incorporated in this process. This includes any desired sustainability exclusions, metrics and targets. The liquidity-filtered universe is fed into our proprietary portfolio construction and analytics framework, which produces a model portfolio that maximizes the overall composite factor score subject to the designated constraints.
These constraints ensure portfolio alignment to client investment guidelines as well as to the various exposures and allocations of the reference benchmark, so that factor-based security selection — and not structural differences from the benchmark — is the key driver of excess returns.
Key Benefits of SAFI
For prospective investors, SAFI offers several compelling advantages:
- Strong Alpha Potential: Systematic application of proven signals has demonstrated strong and consistent excess returns over benchmarks with relatively low risk usage, leading to high information ratios.
- Diversification: The demonstrated low correlation of active returns from our systematic credit strategies with traditional fundamental active credit strategies offers attractive diversification benefits, while maintaining the risk characteristics of the benchmark index.
- Transparent, Disciplined Process: The rules-based methodology provides consistency in security selection decisions that can be applied at scale across broad investment universes.
- Reduced Human Bias By relying on data-driven insights, systematic approaches remain objective and transparent, and avoids the influence of emotional or cognitive biases in investment decisions.
- Sustainability Integration Incorporating sustainability screening aligns investment decision-making with global sustainability goals, appealing to socially responsible investors.
Our systematic credit strategies represent a relatively new and sophisticated investment approach that is built upon quantitative rigor that can also integrate sustainable investment practices. By embracing the transparency of the approach, the diversification benefits of the results, along with the integration of sustainability, SAFI offers a compelling proposition for investors seeking to invest actively and responsible in their fixed income portfolios today.