Many Australian superannuation funds have made Net Zero commitments and want to decarbonise their portfolios in line with these pledges. To do so, their portfolios will need to deviate from benchmarks that do not consider climate risks. Such deviations need to be managed carefully in light of the regulatory environment. We manage portfolios with significantly lower carbon intensity while aiming to outperform benchmarks within limited risk budgets. The impact of decarbonisation on risk and return is quantified and allows for customisation along risk, return and decarbonisation objectives.
Combining our quant and sustainable investing expertise
Decarbonising fixed income portfolios means investing more in bonds from low-carbon issuers and less in bonds from high-emission issuers. This could mitigate risks, as issuers with higher emissions could face bigger challenges in the energy transition. By shifting portfolios towards countries and/or companies with lower emissions, investors can endorse issuers’ efforts to reduce emissions. However, shifting portfolio weights means deviating from market-value weighted indices. While this does not have to increase absolute risk, it introduces relative risk (i.e. tracking error). This is a relevant consideration in light of the Your Future Your Super (YFYS) framework, where performance is evaluated against market-value weighted indices described by APRA. In light of the constant need to deliver for members and given that underperformance versus indices can have major consequences for funds, we have to carefully consider the impact on risk and return when future-proofing fixed income portfolios through decarbonisation.
Table 1 - Decarbonised Enhanced Indexing fixed income strategies

Source: Robeco. The three proposed decarbonised Enhanced Indexing strategies aim to outperform their respective sector benchmarks (after costs) across a full investment cycle with an IR target of 0.75.
Our proprietary algorithms can construct portfolios of bonds with attractive factor exposures, so with bonds that score well on factors like value, momentum, low-risk and quality. In that case, we aim to add alpha while controlling risk. As presented in Table 1 above we, more often than not, utilise the algorithm to do both: construct a portfolio of bonds with attractive factor and emissions characteristics. Our simulations show that we do not need twice the tracking error to meet both goals; actually, we can often kill two birds with one stone. The portfolio construction algorithm can evaluate way more potential portfolios than any human investor ever could. Often, it can find solutions where deviations from the benchmark contribute to both decarbonisation and increased factor exposure, hence boosting the portfolio’s expected return while mitigating emissions and controlling risk.
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