With 2020 coming to an end, we are looking back at one of the most dramatic periods in global finance. Equity markets are frequently reaching all-time highs and government bond yields are close to historic lows. At the same time, opportunities for having a positive impact on the world and society via investment portfolios are expanding at a rapid pace. The latest developments in programming and data science offer unprecedented opportunities of bringing quantifiable measures to the debate about Sustainable Investments and Environmental, Social and Governance factors across entire investment portfolios. On the following pages we will illustrate how such measures fit into a three-stage investment process building sustainable investment portfolios by: (i) creating the optimal long term investment portfolio; (ii) delivering quantifiable ESG measures on portfolio level; and (iii) capturing investment opportunities based on a systematic application of behavioural finance- based machine learning algorithms. As with the other parts of our investment process, the ESG analysis relies on a combination of data-driven analysis and practical investment experience as illustrated in figure 1 below. We combine these in a process which can be summarised as follows:
➢ Constructing the right portfolio to capture long term return and manage market risk along the investment journey, also known as a strategic asset allocation process;
➢ Quantifying the sustainability profile of the portfolio across a range of relevant parameters using our Sustainability Matrix tool (e.g., calculating the CO2 emission of a traditional portfolio and a "sustainable" alternative, as illustrated in figure 2);
➢ Capturing market upside while managing market risk (beta) with a well-tested but still innovative process incorporating behavioural finance-inspired machine learning algorithms for risk control and alpha generation (see figure 3).
To begin with portfolios construction, a synchronised collapse in global economic activity in Q1 2020 brought about an unprecedented level of quantitative easing and targeted lending policy (QE+). The implication is as dramatic as the effect was. What worked in fixed income in 2019- 2020 is unlikely to work in 2021 and beyond. On an SAA level we will all have to adjust portfolios to the fact that many bonds have negative yields and that most high-grade bonds will have returns below the level of inflation. Not only will expected return be lower in the coming years but the ability of a high-grade bond allocations to diversify a portfolio is also severely reduced. This means that the relative attractiveness of equities has increased. At the same time, the positive effect of the commitment of the Fed and its fellow central banks to future QE+ means that sub-investment grade credit is significantly more attractive relative to high grade bonds. The combined effect on SAA level, in our view, justifies an allocation of 20-40% to sub-investment grade bonds in balanced portfolios. A relative increase in attractiveness of equities and sub-investment grade bonds does not mean absolute risk is eliminated. In step three of our process we therefore return to an active allocation solution to this risk management problem.
In 2014 we co-authored the Allocating for Impact report1 , laying out a process whereby one could have a positive impact on the world via one’s financial investments without sacrificing aggregate returns. At the time we had to include a warning that across the spectrum of ESG, SRI and Impact investments the availability of products for implementation in portfolios was very limited. Since then the availability of liquid market products with capacity for larger investments has increased to an extent that one can now find both active and passive funds to build well-diversified global investment portfolios. To calculate the aggregate measures across the various Environmental (E), Social (S) and Governance (G) factors and create quantifiable comparisons across portfolios we have therefore expanded our investment platform with a Sustainability Matrix. This tool allows us to aggregate measures across both ETFs and active funds from different providers and thereby calculate, for example, the portfolio's average CO2 emission per $1M revenue, proportions of Green Revenue, Board Independence and Diversity, as
well as other recognised Responsible Investments and Impact Measurement parameters. This enables us to work both with minimisations of negative effects, maximisations of positive effects and minimum standards for aggregate ratings and specific key areas of interest. The area of responsible investing remains crowded with acronyms and various definitions which are still in the process of being defined and consolidated by numerous working groups, companies, and organisations. Our aim with the tool is to provide some basic quantitative insights and, hopefully, this way help focus the debate as well as actual investment management efforts not only on what is important but also on areas where there is an impact to be had. An example of this approach is provided in figure 2 where we look at two globally diversified USD based equity portfolios, both with a US bias. The first portfolio consists of traditional ETFs covering global equity markets and has a carbon intensity of 136 tonnes per $1M of sales, well within the range of 130 -160 tonnes per $1M we typically see in global equity portfolios (MSCI World is at approximately 145 tonnes per $1M revenue). The second portfolio is a "Sustainable" global equity alternative and consists of four well-diversified ETFs each with their own specific profile and all with low carbon intensity. As you can see, the carbon footprint is reduced by more than 50% to 60 tonnes pr $1M of sales. At the same time, the green revenue is increased from 4% to 7.8% of total sales. This data have a direct link to ESG measures, but we hope they can also be used to frame and measure the positive contribution on a specific measure achieved by intentionally seeking a positive Impact, an area we will return to in future updates.
There has been and still is a lot of scepticism about the potential for Responsible Investing to deliver returns comparable to traditional portfolios. While the data is limited, it is nevertheless worth looking at the recent returns. In figure 3 below we show the return of the Sustainable global equity portfolio, here represented by the black Benchmark line versus the return of S&P 500. The outperformance grows substantially from early 2018, meaning that itstarted well in advance of the pandemic. The main reason for this outperformance appears to be that many of the sectors one avoids in Responsible Investing are also the sectors which have lost out to new technology and are located in areas where the discount factor on future cash flows is high. At the same time Pharma and Technology, in a broad sense, are heavily represented in low emission indices. To us this offers the important take-away that one can and should look at Sustainable Investing both from the perspective of the positive effects it can have on the world and from the point of risk management and alpha creation potential there is in the investment thesis (i.e., that companies which do not appropriately consider their external and internal responsibilities often run too high a risk to be worth the return potential). Investing in a new and better world or just in a Sustainable Future most often also entails investing in future cash flows.
This implies that when market stress or a recession hit and risk premiums go up one is exposed to a particularly large decline in the value of these future cash flows(i.e., to the equity prices collapse). For those who, like ourselves, have some level of recognised risk aversion, we therefore recommend combining equity investments with a systematic risk management process. We monitor market fundamentals and stress via a set of behavioural finance-inspired machine learning algorithms. When the signal from these algorithms declines significantly, like in March of this year or July of 2015 and November of 2018, we reduce the equity allocation in the portfolio substantially. In figure 3 and 4, the Sustainable SEA portfolio, managed with such a process, is shown as the blue line. The grey bars in Figure 3 indicate when we have moved to respectively 60% and 0% equity weights. The main purpose of this process is to limit drawdowns and allow the investor to have a more comfortable journey to sustainable returns and their target ESG impact.