Expert discuss on climate data: Analysing, combining and integrating signals

Climate change is the challenge of our time. Companies and investors must address the associated risks, but also want to benefit from the opportunities. In conversation with Dr Laura Jehl, Research Analyst at Quoniam Asset Management, on how to address climate change with a data-driven investment approach.

The topic of climate risks is playing an increasingly important role for companies. But how important is the topic for investors?

It is becoming more and more important, and we can see that in the increased demand from our clients. Investors are realising that there is a very real financial risk for companies. Achieving the climate targets is most likely only possible through massive regulatory intervention, such as a significant increase in the carbon price.

„No company or investor can afford to ignore climate risks.“

Dr Laura Jehl
Research Analyst

And if the climate targets are not met?

If climate change continues unchecked, the risks for companies will of course also increase. Then we will be dealing primarily with physical risks, such as extreme weather events. These physical risks will certainly become even more relevant in the long term – also for investors. This means that no company or investor can afford to ignore climate risks. This is another reason why the topic is finding its way more and more into our standard strategies.

How does Quoniam approach the topic as a data-based quant manager, especially in contrast to fundamental managers?

In contrast to fundamental managers, where analysts look closely at individual companies, we try to identify trends and patterns based on relevant data. Our expertise lies primarily in the analysis of signals, but also in the sophisticated combination of individual signals and their integration into our existing investment models.

How do you then approach the data and what challenges do you face?

It is important to first get an overview. That means a thorough methodological and quantitative analysis in advance. Important keywords here are distribution of data, coverage, history and the like. One challenge is that some of the data is often only relevant for a few industries. For example, does a company have a risk of stranded assets, such as large coal or oil reserves that have not been extracted? We try to make a forecast based on historical data. That is difficult if the data is not available or only insufficiently available. This is especially true for climate data.

What about the quality of the available data?

Often the data varies from provider to provider because there are still few standards. We therefore like to have access to raw data, not just aggregated metrics or model estimates. But even with greenhouse gas emissions, the data can differ, for example if companies do not report figures and providers have to estimate them themselves. In addition, climate data is often forward-looking. When it comes to the question of what risks a company is exposed to due to climate change, scenario analysis plays a major role in addition to current key figures, and many assumptions come into play.

You have now developed a special climate strategy. What can investors expect?

With the strategy, we want to reduce the climate risks in the portfolio. But we also want to invest in transformation candidates, i.e. in companies that are well equipped to reduce their emissions in the long term and exploit the opportunities of climate change through new technologies and business models. The amazing thing is that many companies that currently have high emissions are still interesting from a portfolio perspective.

„Companies with low emissions in the portfolio are not enough. We want companies with good return potential that are also good transformation candidates.“

Dr Laura Jehl
Research Analyst

You’ll have to explain that to us in more detail.

Not all signals rate the same companies as “green” or “brown” – for example, companies with high emissions often have a better rating in terms of forward-looking metrics such as a Carbon Emission Management Score or the number of patents on climate-relevant technologies. This must be taken into account when constructing signals. Ultimately, this means that it is not enough to only bring companies into the portfolio that have low emissions. Rather, we want companies with good return potential, but which are also good transformation candidates according to the metrics.

Allow me to ask you one more question about yourself. Where does the special interest in this topic come from?

Initially I studied humanities, more precisely philosophy, sinology and German studies, but I always had an affinity for technical subjects. That’s why I then added a Master’s degree in Scotland, which combined both aspects well. It was mainly about machine language processing, linking language and technical aspects. This was followed by a doctorate in Heidelberg at the Institute for Computational Linguistics.

And how did you end up at Quoniam Asset Management?

At Quoniam, as you know, we work a lot with data-based signals. Traditionally, this concerns balance sheet ratios, which are usually prepared in a structured way. However, Quoniam also works on alternative, unstructured text data to add value versus competitors and because the technical possibilities in this area have become greater. My expertise fits in very well here.

You have now expanded your expertise even further…

Yes, since the end of 2020, in addition to the topic of alternative data, I have also been intensively involved with sustainable investing in the research team at Quoniam. On the one hand, the topic is meaningful for me for me personally. And, opportunities are arising for new products that are no longer measured only in terms of return, but also in terms of their social and ecological impact. For example, in our SDG product we measure the extent to which companies pursue activities that contribute to the SDGs (“Sustainable Development Goals”) of the United Nations.

Can unstructured data also be used in the field of climate?

At the moment we only use the classic data, but there are efforts on the part of research, data providers, but also on our part to improve the data situation and also to use and filter unstructured data such as news articles, earnings calls and company reports for additional information.

Is there enough data or would you like more?

The data situation, especially on the topic of climate, is indeed very heterogeneous in part. What all market participants would certainly like to see in the long term is truly mandatory reporting on the topic that is also standardised so that there are fewer opportunities for greenwashing. This standardisation of data is desirable, especially in view of the probably stronger regulation in the area of climate reporting. In my view, however, it is also important that the data is generally accessible. Up to now, we have often been dependent on the data providers. In this area, I think there are still quite interesting treasures to be discovered.

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