Climate change is now a real reporting duty for most NZ licensed fund managers with new greenhouse gas metrics due next year. Daniel Aguet, Scientific Beta index director and deputy CEO, explores some strategies to measure and manage carbon exposures in portfolios and how his firm is tackling transition risk…
Measuring and controlling the carbon intensity of a portfolio is usually a key part of a climate investing strategy. However, carbon intensity can be cut down in many ways, and the how matters more than the how much. Carbon emission is not necessarily the best metric for measuring carbon transition risk – a more robust approach exists.
Measuring carbon intensity serves as a core part of investors’ net zero commitments: what gets measured gets managed. Secondly, a portfolio’s carbon intensity remains a rough proxy for its exposure to climate transition risks, according to the Task Force on Climate-related Financial Disclosures (TCFD).
The carbon intensity of a portfolio can be reduced in different ways. Recently the Net Zero Asset Owner Alliance (NZAOA) and the Institutional Investors Group on Climate Change (IIGCC), have been working on a guidance on how to better measure the different drivers of decarbonisation.
But the question must be asked, how good is decarbonisation at reducing climate transition risks?
Limitations of carbon emissions to reflect carbon transition risks
The task of the TCFD (2017) is to produce “recommendations for disclosing clear, comparable and consistent information about the risks and opportunities presented by climate change” and Weighted Average Carbon Intensity (WACI) remains their primary, specific disclosure recommendation however WACI has two main limitations:
First, WACI relies on emissions that have already occurred. Current emission intensities are unlikely to change radically in the short term, but the closer one gets to the 2050 horizon built into net zero frameworks, the less the recent past will be a guide to the distant future. While a company’s carbon track record is of interest, past performance is no guarantee of future results.
Second, carbon intensity may in aggregate, at portfolio level, be indicative of companies’ transition risk exposures. But it provides less insights at individual stock level: a manufacturer of air conditioners may have the same carbon intensity as one building windmills, but while the former might benefit from unbridled global warming, the latter’s so-called climate solutions would stand to benefit from tighter climate regulations.
To address limitations of carbon emissions, the industry has therefore sought to create more forward-looking climate transition metrics. Three broad categories of approaches can be distinguished – the Crystal Ball, the Rule of Thumb and the Wisdom of Crowds approaches.
Crystal balls
One common approach is to build a proprietary forecasting model. Such models typically involve estimating companies’ carbon trajectories and comparing these to benchmark trajectories for different technologies/sectors/regions. However, projecting a company’s emissions long into the future is fraught with uncertainty, plus there are conflicting benchmark scenarios to choose from.
Moreover, this first step of assessing whether companies align themselves on different transition scenarios only partly answers the objective of having a risk estimate.
Moving from alignment to risk assessments adds a second layer of uncertainty, most notably when estimating and incorporating the future costs of carbon. The level of convergence across providers for climate risk metrics is no more reassuring than the substantial divergence observed between more qualitative and subjective ESG scores (Can We Make ESG Scores Great Again? Scientific Beta, 2024).
Bingler et al. (2021) find that “convergence between metrics is significantly higher for the firms most exposed to transition risk” and that “the risk distribution in the energy sector is significantly higher compared to the other sectors.” This conclusion is obvious.
Rule of thumb
Few doubt that companies producing fossil fuels are most at risk if humankind decides to transition away from carbon-rich energy. To address this, investors can more easily rely on fossil fuels divestment policies, from coal and tar sands. These fossil fuel screens need to evolve over time since what is at stake is a transition, not a disruption. At Scientific Beta, we apply a gradual year-by-year phase out of coal-fuelled electricity by 2030 in developed markets, and 2040 globally.
Wisdom of crowds
An alternative to the wisdom of expert models, is to exploit the wisdom of crowds to extract from market prices, representing consensus between investors, relevant information on which companies win or lose from shifts in climate transition risks. Two types of such market-based climate risk models have been proposed:
Maeso and O’Kane (2023) apply sentiment analysis, i.e. measuring how a company’s stock price reacts to climate related news. Others have proposed to measure stock price sensitivities to climate risks –climate betas – by regressing a stock’s returns on a long/short portfolio of high-risk versus low-risk stocks.
At Scientific Beta we use a similar factor-based approach to compute our Climate Transition Risk Beta (CTR Beta), but we use only carbon intensity inputs at stock level, refraining from relying on proprietary climate scores, which are opaque and divergent across providers. We rank stocks based on their emissions intensity within sectors, and we apply a sector classification system that is used, for example, in the European Central Bank’s climate stress test framework.
The resulting CTR Betas are expected to reflect the market wisdom: a CTR Beta above zero means an above average climate transition risk estimate. Since investors determine stock prices from their projections and riskiness of future cash flows, CTR Betas are forward-looking.
An innovative way to manage climate transition risks
Scientific Beta climate change screen tackles climate transition risks in two ways. First, we apply a carbon intensity screen that shuns sector laggards. Hence, we avoid pulling the plug form whole sectors, which is in line with IIGCC recommendations for Enhancing the Quality of Net Zero Benchmarks.
Second, we screen companies with the highest CTR betas, which are extracted from market prices and that reflect their sensitivity to climate transition risk as perceived by investors. This screen integrates forward-looking information while carbon emissions are backward-looking.
To conclude, Scientific Beta climate change screen is going beyond simple decarbonisation of equity portfolios and aims at favouring real economy carbon reductions and integrating robust forward-looking information to reduce equity portfolios exposure to climate transition risks.