The Case for Systematic Investing in Credit

We believe that now is the time for systematic investing in credit. Only more recently with the advances in technology, electronic trading, and market efficiency in credit — accelerated by the pandemic — have we finally seen an enabling environment for the capture of value-add from a systematic, factor-based investing approach.

Historical data show that a factor-based, systematic approach to investing in credit can drive outperformance relative to a broad benchmark index. In addition, systematic investing can provide a wide range of benefits to investors, such as consistent data-driven excess returns, a diversifying return profile, and clear transparency and process. Credit market innovations such as electronic trading and portfolio trading have led to greater transparency in corporate bond trading and lower transaction costs over time, facilitating the successful implementation of systematic strategies today. The implementation of systematic portfolios relies on data analysis and implementation skill to achieve three objectives: 

1. Maximize exposure to high scoring bonds;
2. Adhere to defined risk constraints; and
3. Control costs by balancing limits on turnover with expected benefits of each transaction. 

Strong Evidence for Factor-Based Signals Driving Alpha Generation in Credit

Within the investment grade corporate universe, not all issuers or bonds are created equal. Rather, some have more (or less) desirable credit characteristics than others. For example, some companies may exhibit fundamentals such as profitability or indebtedness that are not fully reflected in their pricing. Alternatively, market sentiment may favor a different set of companies. Each criteria that could potentially lead to outperformance (or underperformance) can be identified as an alpha factor to which a portfolio tilt can be applied. A systematic strategy takes a data-driven approach that evaluates all securities in an investment universe based on their exposures to these factors in order to best position the portfolio. Three alpha factors that can be identified in the investment grade corporate bond market include value, momentum, and sentiment.

A Focus on Value

As an illustration of value as an alpha factor, we looked at its performance over time. Value addresses how attractive (rich or cheap) a bond is relative to a group of peers with the same issuer fundamentals and bond characteristics (such as quality, sector, and maturity). To capture value, the Barclays Quantitative Portfolio Strategy (QPS) team developed a relative value signal for corporate bonds. QPS’ proprietary value signal assigns scores from 1 to 10 to each bond in the relevant investment universe according to its relative valuation versus peers. A high score indicates attractiveness.

In a simple performance test, over a series of months, we partitioned the bonds that made up the Bloomberg US Corporate Index into quintile portfolios based on their value scores, and measured their returns. Figure 1 shows the cumulative excess return performance (versus like-duration Treasuries) going back to 1993 of the top-quintile portfolio, the bottom-quintile portfolio, and the index.

This analysis demonstrates the power of the investment insights that the data reveal. Quite simply, were one to invest only in securities scoring highly, the results would have been favorable. High value bonds have delivered consistently better performance than low value bonds, in the form of higher average excess returns and information ratios.

Similarly, we can use signals to capture momentum and sentiment as alpha factors to learn more about the characteristics, beyond risk factors and issuer fundamentals, that make a bond attractive and likely to outperform in the future.

Harnessing the Strength of Signals: A Lesson in Systematic Investing

The evidence shows that maximizing exposure to value and other quantitative signals with demonstrated efficacy is likely to result in positive outcomes for investors. Systematic strategies rely on data analysis and implementation skill to build these alpha factor exposures in portfolios. This approach aims to outperform an index by seeking opportunities to allocate to attractive securities, and away from those deemed unattractive according to these signals. These strategies take a rules-based approach to decision-making, with a three-fold objective:

• Maximize exposure to high-scoring bonds, continuously evaluating opportunities across a broad investment universe of securities.
• Perform highly disciplined risk management, limiting issuer concentration and deviations from benchmark risk exposures, avoiding unintended risks, and restricting the possibility of large unexpected deviations from benchmark returns.
• Control costs by balancing limits on turnover with the expected benefits of each transaction.

Guardrails ensure that portfolio outcomes are driven by the issuer selection signals, rather than by unintentional exposures to market risk.

Why Now: Advances in Data and Technology Enabling the Rise of Systematic Investing in Credit

The key reason that systematic investing has been much more widely adopted in equity markets than in credit markets is that equities are considered far more liquid. However, recent innovations in fixed income markets now make it possible to cross this liquidity barrier. The proliferation of electronic trading and fixed income ETFs, giving rise to basket and portfolio trading, has improved price transparency and increased the efficiency of trading in credit, even in the face of more recent upticks in volatility. Figure 2 shows the growth of electronic trading and the rapid rise in the volume of portfolio trading inquiries over time, which have helped facilitate greater transparency and efficiency in the corporate bond market.

The key to a systematic strategy is breadth, or the ability to spread risk among a large number of small active risk exposures to issuers and bonds that score highly on various signals. This was not practical when only a thin layer of the most active corporate bonds could be traded on a liquid basis. The technological innovations in credit markets now make it more feasible to transact less liquid bonds, allowing for greater portfolio breadth. Armed with these new tools, as well as the ability to substitute hard-to-trade bonds with more investable equivalents, an experienced execution team can finally make systematic investing in credit economically viable.

Concluding Thoughts

The systematic approach provides several benefits to investors:

• Data-driven excess returns. Quantitative signals based on alpha factors can help investors differentiate between attractive and unattractive opportunities in credit, and therefore drive above-benchmark index returns.
• A diversifying return profile. By drawing on multiple data-driven signals to drive outcomes, systematic strategies can offer a differentiated return profile that can be complementary to many fundamental active managers, whose performance tends to be highly correlated with corporate bond index excess returns.
• Clear transparency and process. Awareness of how the data are being used to derive signals leads to greater transparency. The result, far from being a black box, is greater clarity on precisely how investment outcomes are achieved.
  

With clear signals and implementation processes in place, systematic strategies offer transparency; a complementary, diversifying return profile relative to fundamental active strategies; and attractive economics to investors.