Credit Factor Investing as a Solution to Combining Sustainability and Outperformance

What is the ex-ante impact of different sustainable investment approaches on the alpha of a credit portfolio? And what can investors do who want both outperformance and sustainable credit investments? Credit factor investing provides a framework and a solution to both questions.

The volume of corporate bond portfolios managed with sustainability criteria has exploded in recent years. An increasing number of portfolios incorporate sustainability objectives by means of tilting the portfolio towards higher ESG scores or lower carbon footprints. They may exclude issuers that violate certain standards, generate revenue from undesirable economic activities or increase positions in companies that have explicit sustainability goals, such as climate transformation, as a main investment objective. However, combining sustainable investing (SI) with outperforming a credit benchmark remains a challenge.

Sustainability criteria can lead to unwanted sector biases. For example, if we apply exclusions that reduce the number of fossil fuel producers in a portfolio, the performance of the portfolio will depend on the performance of the energy sector. Such sustainability criteria therefore have a time-varying effect on performance, which may be negative in one period and positive in another.

Moreover, it is difficult for a traditional fundamental credit manager to estimate the ex-ante performance impact of a sustainability metric, as the future performance of the sectors and bonds concerned is unknown. And while the ex-post effect can be estimated by comparing the performance of portfolios with and without the sustainability criteria, this is not possible for the ex-ante performance estimate. However, quantitative portfolio characteristics provide a way to obtain a reasonable estimate of the ex-ante alpha impact.

How can a factor lens be used to estimate the impact of sustainability criteria?

Quoniam’s investment process involves the construction of credit portfolios with meaningful exposures to systematic credit factors. This approach is called ‘credit factor investing’. If you are not familiar with credit factors, please see the box adjacent with further explanations.

Fixed income factor definitions
  • Value

    Cheap bonds outperform expensive bonds. Our value signal is the standardised difference between market spread and a proprietary fair value spread estimate. We run a multi-variate regression using composite variables to arrive at a fair value estimate.

  • Momentum

    Issuers with strong recent performance of equities continue to perform well in the near future. We use equity momentum for corporate bonds because studies show that there is a lead-lag relationship between stocks and corporate bonds, and that equity momentum has predictive power for bond downgrades.

  • Carry

    Bonds with higher spreads and steeper credit curves yield higher return. We merge spread and spread rolldown into one signal. Accordingly, we focus not only on higher yield, but also on the additional higher rolldown returns of bonds at steeper parts of the curve.

We use systematic factors such as value, momentum or carry to construct a corporate bond portfolio. Typically, these factors are combined into a so-called multi-factor signal, which is used as an alpha estimate in the portfolio construction process. In contrast to return impact of sustainability measures, there is strong empirical evidence that higher factor exposure in a portfolio leads to higher expected returns. Figure 1 describes this relationship.

Figure 1: Global IG credit multi-factor quintile portfolios
Relative performance of quintile portfolios with different exposures to the Global IG Credit multi-factor signal (Q1=lowest, Q5=highest). Source: Quoniam Asset Management

The portfolio containing the 20% of bonds with the highest factor exposure, quintile 5, shows the best performance over time (Figure 1). Performance declines with each reduction in multi-factor exposure. Quintile 3, the median quintile, performs in line with the market, while quintile 2 and quintile 1 underperform the market.

How do we estimate the impact of sustainability criteria in practice?

We can use the factor approach to estimate the impact of different sustainability approaches on the expected alpha. That is, we create a new portfolio according to the client’s sustainability target, e.g., 20% less carbon emissions, and calculate the portfolio’s factor exposure. We then compare it to the investor’s original portfolio and evaluate the difference in ex-ante performance expectations.

To estimate the alpha impact of different sustainability measures, we construct and compare several corporate bond portfolios. We first construct a portfolio with no sustainability constraints and then we add sustainability constraints of increasing stringency. For all portfolios, we calculate the exposure to the multi-factor signal as a measure of ex-ante performance potential. To simulate realistic portfolios, we restrict deviations from a standard benchmark in terms of duration, credit risk, cash, active sector exposure and the maximum weight per issuer.

We consider the following sustainability metrics and requirements:

  • the Industry-Adjusted Score (IAS) by MSCI,
  • the carbon footprint of the portfolio (scope I+II),
  • and a minimum proportion of green bonds.

We apply increasingly restrictive constraints and measure the impact on the portfolio’s factor exposure.

What are the trade-off frontiers?

The results of our calculations are shown in Figure 2.

Figure 2: Trade-off between multi-factor exposure and sustainability measures
Panel A: IAS score
Panel B: Carbon footprint
Panel C: Green bond quota; Source: Quoniam Asset Management

The graphs show a trade-off between multi-factor exposure and sustainability criteria, but the trade-off is small for moderate levels of the respective sustainability variables. For the IAS score in Panel A, an unconstrained optimisation of the multifactor signal currently leads to a portfolio with an average IAS score of 6.4 and a multi-factor score of 1.3. If the portfolio is tilted to a higher score of 7.6, the loss in multi-factor exposure is moderate at 1.2. It is only when the score is tilted even higher, towards 8 and above, that the loss in multi-factor exposure becomes more significant.

The carbon footprint tilting in Panel B shows that even large reductions of 60% and more do not lead to a significant loss in multifactor exposure. For the green bond quota in Panel C, the trade-off is more visible. While no restrictions on the portfolio currently lead to a green bond position of 8%, a position of 30%, 50% and 70% leads to multi-factor scores of 1.2, 1.0, and 0.8, respectively. Again, a moderate position does not change the alpha potential significantly, but larger positions have a negative impact on ex-ante performance expectations.

The results also provide another insight. For investors who focus on sustainability in a credit portfolio, systematic and consistent outperformance becomes possible if they adopt a systematic factor approach. As can be seen from Figure 2, Panel C, investors who wish to have at least 50% green bonds in their portfolios can implement a multi-factor portfolio with a score of 1, which is about 75% of the exposure compared to the case with no mandatory allocation to green bonds. Although the expected alpha is somewhat lower, there is still significant potential for outperforming the market.

Investors who combine a sustainable investment approach with credit factor investing therefore gain several advantages:

  • A systematic factor exposure in the portfolio can be achieved leading to outperformance versus the broad market in the medium-term.
  • The ex-ante effect of any ESG criterion in terms of impact on expected alpha can be specified with reasonable precision.
  • Different sustainability measures can be compared in terms of their ex-ante impact on alpha expectations.
  • Our research shows that the MSCI ESG IAS score of an IG credit portfolio can be increased from 6.4 to 7.2 with only a negligible reduction in alpha potential as expressed by the multi-factor score. Similarly, a 30% position in green bonds does not change the alpha potential of the portfolio significantly.

We show that qualitative assessments of the impact of different sustainability measures on ex-ante alpha expectations can be made using a systematic factor investing approach in corporate bond management. Sustainability tilts and factor exposures are compatible and the goals of outperforming a standard benchmark and including a sustainability criterion in the portfolio can both be achieved with moderate compromise. Investors with a sustainability focus do not need to give up on their outperformance goal when using factor investing. The results show that systematic approaches are well-suited to implement SI strategies and achieve outperformance at the same time.


Dr. Harald Henke
Head of Fixed Income Strategy

Dr. Veronika Herzberger – CFA – CCrA
Head of Fixed Income Portfolio Management

Desislava Vladimirova
Research Associate

Please find our detailed study on the interaction of sustainability and systematic credit factor exposures here:

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