To this end, we introduce in our recent research paper a multi-objective investment framework which we deem ‘3D investing’. We make the argument why such framework results in the ‘best possible’ solution when jointly considering more than two portfolio objectives.
The new paper by David Blitz, Mike Chen, Clint Howard and Harald Lohre demonstrates how traditional mean-variance portfolio optimization can be enhanced by adding sustainability as a third goal, using carbon footprint and SDG (see Figure 1 below) as examples. We find the 3D investment approach generally outperforms the traditional 2D model with sustainability constraints. Our simulations support our conclusion that 3D investing yields higher sustainability metrics and expected returns than a constraint-only method when using a generic factor strategy. However, using constraints in sustainable investing still has merit. A combined strategy, blending a flexible sustainability constraint with integrating sustainability into the optimization process, we believe offers a balance between return, risk, and sustainability goals. For aggressive sustainability aims, the 3D approach, which explicitly incorporates sustainability alongside alpha and risk, we have found to be ideal.
Figure 1: Hypothetical, back-tested performance for the 3D vs 2D investment performance when targeting higher SDG scores
Source: Robeco - December 1989 to December 2022. The graph utilizes hypothetical back tested performance data to demonstrate the use of the generic factor set up in use when targeting higher SDG scores about the benchmark as opposed to using a portfolio constraint from an after-cost return perspective.
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We are a leader in sustainable investing. We’ve routinely integrated ESG across all our investment processes since the early 2000s, we are frontrunners in active ownership, and we continuously push the boundaries of impact investing.