The data driving decision making in our Systematic Fixed Income strategies is provided by the Barclays Quantitative Portfolio Strategy team, or QPS, which is well-recognized as an innovator within the fixed income space. Their analytical scale is an important input to the process we at State Street Global Advisors will use in the management of Systematic Fixed Income strategies.
In this blog post, we explain who they are, how this collaboration came about, and why it is meaningful for our systematic strategies.
QPS was started in late 80’s. The group helped launch a number of Fixed Income indices and related portfolio analytics that are still in use today.
QPS developed a deep understanding of index construction, and investors began to turn to QPS with questions on best practices in managing bond portfolios relative to these benchmark indices, quantifying and optimizing risk, attributing performance to intentional and unintended index exposures, among other queries. By the early 1990s, the group was providing major institutional fixed income managers with research on a broad range of quantitative issues in fixed income portfolio construction.
This continued to be the QPS group’s focus for the next three decades. The group has been engaged in a research dialog with some of the largest investment managers in the world, including pension funds, Sovereign Wealth Funds, Hedge Funds, insurance companies, asset managers and central banks.
QPS publications tend to have a very long shelf life as they are methodological in nature and not tied to current markets. Based on this work, the QPS group has also been consistently highly ranked in the Institutional Investor Fixed Income Research Survey.
Below, we dig deeper into some of QPS’ innovative research, much of which has been transformative for fixed income traders and portfolio managers.
In a study first published in 2005, QPS showed that spread duration (then the accepted measure of credit risk) was not optimal. QPS introduced a superior measure known as Duration Times Spread (DTS). In a series of research reports spanning over 15 years, the group has shown that credit spreads tend to move not in parallel (as implied by using spread duration) but rather proportionately – spread change is linearly proportional to spread level. A measure of sensitivity to such a move is DTS. DTS has since been shown to give superior estimates of credit risk across a broad spectrum of credit assets such as high yield, emerging markets, Euro sovereign debt, and other market regimes. DTS has become a standard metric in institutional credit risk management.
In response to the Global Financial Crisis, in 2008, QPS launched Liquidity Cost Scores (LCS) based on quotes from Barclays trading desks and modelling of unquoted securities. LCS has been proven to reliably estimate transaction costs both over time and cross-sectionally.
QPS has researched and published extensively on systematic fixed income signals, especially in credit markets. Its recent book Systematic Investing in Credit (Wiley, 2021) gives a high level overview of some of these signals and portfolio construction methodologies.
Over the past decade, QPS has broadened its focus to include cross-asset research and to integrate information based on signals beyond fixed income and across the full capital structure of an issuer. This has led to the development of several cross-market credit signals, some of which are being leveraged in State Street Global Advisors’ systematic active fixed income strategies.
Using its cross-asset research capabilities, QPS has performed important research on the impact of a tilt in ESG criteria (an issuer-level attribute) on performance. QPS has also provided insights into credit and equity methodologies for isolating the ESG risk premium.
QPS is excited to collaborate with State Street Global Advisors on research to support the development of Systematic Active Fixed Income Strategies. The first strategies introduced by State Street resulting from our collaboration are Investment Grade credit, where three signals form inputs to the systematic process. In addition to the momentum, value and sentiment factors used in the initial collaboration, QPS is working on a broad spectrum of new strategies using novel data sets, natural language processing, extending equity market methodologies to credit, and developing best practices for signal combination and imposition of turnover constraints.
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Exp. Date: 05/31/2024