Reducing the carbon intensity of multi-factor credits strategies

Our research into sustainability integration in quantitative investment strategies shows that such strategies lend themselves well to integrating secondary objectives, such as reducing carbon intensity, next to the primary objective of realizing attractive risk-adjusted returns. This is due to the large investment universe that the strategy can screen for the most attractive opportunities.

If a company with high carbon emissions issues a bond with attractive factor scores, the portfolio construction algorithm is often able to find a bond with similar factor scores, but with lower carbon intensity. This efficiently tilts the portfolio towards bonds of more sustainable companies, without having to forgo a lot of factor exposure.

We assessed the performance impact of imposing a constraint on the carbon intensity of our global multi-factor credit and global multi-factor high yield strategies, over a 1994-2019 backtest period. The constraint specifies that the weighted average carbon intensity of the portfolio should be lower than that of the benchmark. The impact on the backtested performance is limited to a few basis points per annum. We have also researched more ambitious carbon reduction targets, e.g. 10% lower carbon intensity than the benchmark, or 20%, 30%, etc., and found that these are associated with modest reductions in the expected outperformance of the strategies.

One may wonder why reducing the carbon intensity of the multi-factor strategies comes with only a limited reduction in outperformance, even though imposing constraints in a factor strategy generally leads to lower factor exposures. We think there are three reasons for this:

1. The distribution of carbon intensity is right-skewed, so that avoiding only a few of the most carbon-intensive companies results in a relatively large reduction in the weighted average carbon intensity of the portfolio.
   
   
2. For large periods, the portfolios already have a lower carbon intensity than their benchmark, so that no adjustments need to be made in those periods.
   
   
3. In the periods that the carbon intensity of the portfolios is higher than their benchmark, the large investment universe often enables the portfolio construction algorithm to replace bonds from companies with high carbon emissions with bonds that have similar factor scores, but lower carbon intensity. This efficiently tilts the portfolio towards bonds of more sustainable companies, without having to forgo a lot of factor exposure.