Investors are increasingly building portfolios with explicit carbon-reduction targets, temperature alignment goals, and climate objectives such as mitigation and adaption. To inform the thinking around such efforts, we recently constructed and back-tested five equity portfolios targeting carbon reduction, varying across risk and return dimensions.
Two portfolios used a screening approach, two used a tilting approach, and one used an optimization approach:
Divest 10 (screened): The 10% highest carbon emitters in the MSCI World Index universe are removed (i.e., 10% of market cap is removed).
Divest 20 (screened): The 20% highest carbon emitters in the MSCI World Index universe are removed (i.e., 20% of market cap is removed).
Pure Tilting: A simple tilt is applied on carbon intensity with no constraints applied.
Iterative Tilting: A cumulative normal distribution is applied to carbon emissions, and weights are assigned to securities based on their transformed carbon scores. Additional security, sector, and country constraints are applied.
SSGA Low-Carbon Framework (optimized): A mean-variance optimization is employed to either minimize tracking error at a target carbon-reduction level or minimize carbon emissions at a target tracking error.
Ultimately, our research suggests that employing optimization for building reduced-carbon portfolios is a preferred approach, as it best balances the multiple objectives investors have beyond just reducing carbon. In particular, tracking error to the benchmark, which measures the amount of active risk investors have to take on to reduce carbon, appears to be best managed using optimization.
The optimized Low-Carbon Framework approach appears to produce the greatest amount of carbon reduction over time, and this same approach also appears to produce the most stable level of carbon reduction per unit of tracking error. The latter finding is critical, as this measure suggests the best potential outcome for investors who also care about risk.
The research reviewed the active country exposures of the different strategies and suggests that Iterative Tilting stood out with much more controlled active exposures. Sector exposures across the five portfolios were found to be similar to those of the country exposures, though we note also that a strategy of simply rotating out of carbon-intensive sectors and overweighting low-carbon sectors may result in significant tracking error. A more appealing approach for index investors might be to derive a majority of the carbon reduction from security selection within sectors.
In sum, our research suggests that the tradeoff between carbon reduction and tracking error could be best managed using optimization. In this preferred approach, investors can meet their carbon-reduction targets while also minimizing the amount of risk they have to assume in deviating from their policy benchmarks. In contrast to rules-based approaches, optimization is generally more risk-efficient. Please download the full article, containing detailed performance data and analysis, below.
This information is for informational purposes only, not to be construed as investment advice or a recommendation or offer to buy or sell any security. Investors should always obtain and read an up-to-date investment services description or prospectus before deciding whether to appoint an investment manager or to invest in a fund. Any views expressed herein are those of the author(s), are based on available information, and are subject to change without notice. Individual portfolio management teams may hold different views and may make different investment decisions for different clients. There are no guarantees regarding the achievement of investment objectives, target returns, portfolio construction, allocations or measurements such as alpha, tracking error, stock weightings and other information ratios. The views and strategies described may not be suitable for all investors. SSGA does not provide tax or legal advice. Prospective investors should consult with a tax or legal advisor before making any investment decision. Investing entails risks and there can be no assurance that SSGA will achieve profits or avoid incurring losses.
Performance quoted represents past performance, which is no guarantee of future results. Investment return and principal value will fluctuate, so you may have a gain or loss when shares are sold. Current performance may be higher or lower than that quoted.