Data to Value’s research in the VW scandal has applications both in the long only asset management space and also in the hedge funds space for both managing risks and also identifying investment opportunities or developing a graph-based trading strategy. For example, based on the insights uncovered, the shares of indirectly affected companies could be shorted in order to achieve returns. Although not directly exposed to the crisis, these companies are indirectly affected by the reputational impact, decline in profitability of VW and unplanned costs if the matter is not resolved effectively e.g. fleet buyers bearing modification costs themselves or seeing reduced demand for VW rentals.
“The same insights could also help a risk manager understand a portfolio or entire investment manager’s risk profile associated with systemic or counterparty risks. Graph technology is perfect for performing these types of network analysis” explains Phare.
Research processes are traditionally very manual and document driven. Analysts look at broker’s reports, newspapers, market data. This makes sense when the velocity of the information is low but doesn’t scale up to today’s high data volume. Techniques like machine learning and semantic analysis can automate a lot of this work and make the job of analysts easier. Combined with this kind of self-service graph analysis enabled by Linkurious this presents an innovative approach for investment managers.