Strategies

Our proprietary Natural Language Processing (NLP) algorithms allow us to analyze unstructured and semi-structured data at scale. We source both from traditional sources (news, transcripts, annual reports) as well as various open source data we collect.

We have designed our own scraping platform which enables us to collect data that is customized for our own specific needs.

Sentiment analysis relies on reading media outlets, public reports, quarterly / annual filings and whatever is accessible in order to understand how positive or negative the company narrative is. Normally this is a slow and laborious task, involving large groups of analysts with various biases of estimating sentiment. This process becomes particularly intense and sometimes impossible during earnings, four times a year, lasting six weeks.

Our systems not only offer more accurate and reliable analysis by reading accessible data at scale but also allow us to read data in various languages across the world — just imagine how hard this would be for a team of analysts and portfolio managers.

Governance is about making decisions and we believe good governance is central to the agency relationship between management and us, as shareholders. Fairness, transparency, good ethics, diversity and a well functioning board are principles which we just use in managing our business but also expect to see high and improving standards in our investments.

Our approach to investing in well-governed companies is differentiated by our technology. Our edge in identifying good governance comes from being able to infer governance scores for companies that are too small to be properly understood by the wider investment community.

It is also important to “connect the dots” when reading news, reports, quarterly filings and other sources. Which companies, what products, which key people were mentioned? How are they related? Have they been mentioned in the previous discussions?

All of these are consistently reviewed and evaluated, across all the sources we see (as well as new ones we add over time).

Society is a central pillar to economic activity. B2B enterprises and governments alike exist to ultimately serve consumers. Businesses can not prosper, in the long term, unless they have a positive contribution to society. Social order means a stable society and a stable society means a business can continue operating for a long time. Our investment process centers around looking for companies that are making positive contributions to society, as well as striving to do better.

Our approach to investing in a sustainable way is differentiated by our technology. Our edge in social investing comes from being able to infer social scores for companies that are too small to be properly understood by the wider investment community.

The environment is the medium in which we live our lives. It concerns every aspect of what we do, including making investments. Thus, it makes total sense that our investments would also act in accordance with our interests. Our investment process centers around looking for companies that are making positive contributions to the environment, as well as striving to do better.

Our approach to investing in a sustainable way is differentiated by our technology. Our edge in environmental investing comes from being able to infer environmental scores for companies that are too small to be properly understood by the wider investment community.

Machine Learning is a wonderful tool but it’s not the universal solution the media would make you believe. We believe the best approach is to mix and match best computational techniques with the appropriate tasks.

This computational technique works best at automating decisions that have to be taken in a stationary environment. In an investment context, these tend to be more mundane tasks, like detecting whether a company is impacted by a certain theme (or not). These inferences are made continuously, allowing us to detect changes in a thematic for a company ahead of the street.