Kempen Capital Management has long used fundamental analysis to select securities. Big data has played an increasingly important role in how we decide which investments to make over the past few years, but the challenge is to process these data in such a way that they yield information that contributes to improved decision-making and ultimately higher investment returns. Kempen applies this approach in how it selects a range of investments, including wind and solar energy companies.
In fundamental analysis, investment analysts assess the attractiveness of a firm or sector relative to other investment opportunities by researching that company’s or sector’s attributes. This kind of approach continues to form the cornerstone of many of Kempen’s strategies and our fiduciary management services for pension funds and insurers. However, we are increasingly using data analysis as a complement to our traditional fundamental research process.
“Our aim is to provide our portfolio managers with a list of securities that they can consider including in their portfolios,” data scientist David Dogon explains. “We want to be a generator of ideas, and we use machine learning to this end. We use computer algorithms to identify patterns in large datasets. For example, combining financial and historical datasets enables us to see correlations that we might otherwise not have noticed.”
Digging deeper
As an illustration he refers to a model that our Advanced Analytics team has built for investments in wind farms and solar energy plants. “You can be influenced by glossy brochures and annual reports when selecting companies. But you also need to dig deeper and include non-financial information in your analysis. This helps you to understand the differences between companies and make better choices.”