Conditional Transition Loss

Climate-related transition risks—stemming from policy changes, technological innovation, and evolving consumer preferences—are increasingly central to equity portfolio management. These risks can materially affect asset valuations, sectoral exposures, and the overall risk-return profile of portfolios. At the same time, they create opportunities for firms and portfolios strategically aligned with climate objectives.

Empirical evidence on how transition risks are priced in equity markets remains mixed. Some studies identify a carbon risk premium, whereby firms with higher emissions are valued at a discount ^[1]. Others find that green stocks have outperformed brown stocks ^[2]. These discrepancies are often attributed to the distinction between realised and expected returns, as discussed by Pástor et al. (2022) ^[3]. In addition, structural barriers to pricing these risks—such as inadequate risk models and intertemporal inconsistencies—have been highlighted in recent reviews ^[4].

In this context, long-term scenario analysis has emerged as a critical complementary tool for transition risk assessment. Unlike short-term stress tests that focus mainly on carbon pricing and its impact on operating costs, long-term methodologies incorporate broader economic dynamics, including demand shifts across technologies and sectors. Regulatory initiatives such as the Network for Greening the Financial System (NGFS) have supported the development of integrated assessment models that account for both direct and indirect effects of transition drivers.

The Conditional Transition Loss (CTL) metric introduced here builds on this framework by integrating firm-level revenue data, including 'green' revenues aligned with the EU taxonomy, along with carbon intensity indicators. By linking firm-specific revenue streams to scenario variables derived from NGFS pathways, the model captures the impact of demand shifts on firm valuations. This provides a more comprehensive perspective on transition risks than models that rely solely on emissions metrics.

To reflect the inherent uncertainty of the energy transition, the CTL is estimated conditionally on the choice of scenario, time horizon, and integrated assessment model. This approach acknowledges the significant influence of these parameters on financial outcomes and supports a more robust and transparent analysis of climate-related transition risks in portfolio management.

Construction of the Conditional Transition Loss

The Conditional Transition Loss (CTL) metric is computed from a discounted cash flow model, in which the present value of a firm's future cash flows is influenced by two primary channels: revenues and operating costs.

Revenue channel: In this framework, projected revenues are sensitive to both the technological composition of a firm’s current revenue streams and to technology-specific growth rates that are scenario-dependent. For instance, revenue attributable to conventional transportation technologies is assumed to evolve in line with the trajectory of the scenario variable Final Energy | Transportation | Liquids.

Operating costs channel: Operating costs are assumed to vary as a function of the firm’s Scope 1 emissions intensity—that is, the volume of direct emissions per unit of revenue—and the carbon price pathway embedded in the scenario. As carbon prices increase, firms with higher emissions intensities are expected to face proportionally greater cost adjustments.

Letdenote the cash flows of firm at time , under the expected (baseline) transition scenario. We assume the following cash flow structure:

where represents revenue, the carbon costs rate, the operating cost rate, is the tax rate, and the (net) investments rate. Firm revenue, , is the sum of revenue its activity segments, denoted by . The dynamic of revenue is driven by a growth factor specific to each activity segment:

where  is the initial sales of product  for stock , and is the growth factor of the product’s demand over time, determined by the scenario.

The carbon costs rate is modelled as the product of the direction emissions (Scope 1) of the firm and the carbon price of the scenario. Indirect emissions, whether related to energy consumption (Scope 2) or the entire value chain (Scope 3), are not considered to directly affect the carbon cost rate. This assumption is based on the premise that their impact is already integrated at the sectoral level through the integrated assessment model, and their repercussions on the firm cash flows are captured through the revenue channel. For example, a car manufacturer may have minimal Scope 1 emissions, but significant Scope 3 emissions associated with its products’ use. Rather than directly applying a carbon price to these Scope 3 emissions – which are often challenging to quantify – the integrated assessment model is assumed to account for the effects of a carbon tax on the demand for conventional vehicles, resulting in reduced demand. For the car manufacturer, this indirect impact is therefore reflected in the revenue segment.

Finally, to avoid negative cash flows, the carbon cost rate is capped such that the sum of the carbon cost rate, tax rate, operating cost rate, and investment rate does not exceed 1:

where  is the carbon intensity of the stock and is the carbon price.

Once the cash flows are projected between the reference date and the analysis horizon, they are discounted by weighted average cost of capital (WACC):

These discounted cash flows are summed to compute the total firm value :

The conditional transition loss is finally computed as the relative change in the stock value compared to the value in the baseline scenario:

Assessing and managing transition risks with the Conditional Transition Loss

The Conditional Transition Loss (CTL) has been developed as one of several tools to support equity investors in assessing and managing their climate-related transition risks. It is designed as a scenario-based, bottom-up metric that complements the market-based climate transition factor. We recommend a three-step approach to integrate CTL into a transition risk management framework

Step 1 – Assess the potential financial materiality of transition risks

As with a traditional stress test, the CTL is scenario-dependent. Its magnitude will vary depending on the transition scenarios considered (e.g., orderly, disorderly, delayed). Therefore, the first step is to compare the CTL across several transition scenarios. This comparative analysis provides a range of potential long-term portfolio losses, allowing investors to determine whether transition risks are likely to be material for their portfolio.

This step is diagnostic in nature: it does not yet assess whether the market has priced in these risks, but helps identify whether the transition challenge warrants further action in the context of the investor’s strategic objectives and investment horizon.

Step 2 – Confirm the portfolio’s sensitivity to transition risks

It is important to recognize that not all scenarios are equally probable, and some risks may already be reflected in market prices. For this reason, we do not recommend relying on CTL alone to assess and manage transition risks.

The second step involves complementing the fundamental, scenario-based CTL measure with a market-based measure, namely the exposure to the Climate Transition Factor. This exposure captures the extent to which a portfolio is exposed to firms that the market perceives as being at risk (or well-positioned) in a low-carbon transition.

• If the CTL indicates substantial losses under credible transition scenarios,

• and the Climate Transition Factor confirms that the portfolio is exposed to transition risks as priced by the market,

then this dual confirmation strengthens the case for taking action to manage transition risks.

Step 3 – Manage transition risks through allocation and engagement

If transition risks appear to be material and your portfolio exhibits sensitivity to these risks, a risk management strategy can be implemented. The main strategy is to reduce exposure to the Climate Transition Factor, for instance by constraining its value to match that of the benchmark while controlling tracking error.

However, this strategy may not address all underlying vulnerabilities. Certain companies may still exhibit high CTL values—indicating significant risk under specific transition scenarios—even if the market has not yet priced these risks in. To address this, we recommend performing an additional check: ensure that portfolio-wide CTL is reduced after optimizing for climate transition factor exposure. If not, additional constraints may be warranted.

A major advantage of the CTL is its bottom-up granularity, allowing investors to:

• Identify top contributors (i.e., firms with high conditional transition losses – potential transition losers),

• and identify bottom contributors (i.e., firms benefiting from the transition – potential transition winners).

Investors may then apply allocation constraints to limit exposure to high-risk firms, or to ensure minimum exposure to firms likely to benefit from the transition.

In addition, by understanding the drivers of a firm’s CTL—whether linked to high carbon intensity, unsustainable revenue sources—investors can design more effective engagement strategies. These engagements can focus on improving disclosure, encouraging credible transition planning, and aligning business models with climate objectives.

References

1 Bolton, P., & Kacperczyk, M. (2023). Global pricing of carbon‐transition risk. The Journal of Finance, 78(6), 3677-3754.

2 Bauer, M. D., Huber, D., Rudebusch, G. D., & Wilms, O. (2022). Where is the carbon premium? Global performance of green and brown stocks. Journal of Climate Finance, 1, 100006.

3 Pástor, Ľ., Stambaugh, R. F., & Taylor, L. A. (2022). Dissecting green returns. Journal of financial economics, 146(2), 403-424.

4 Campiglio, E., Daumas, L., Monnin, P., & von Jagow, A. (2023). Climate‐related risks in financial assets. Journal of Economic Surveys, 37(3), 950-992.