Investment analysts and portfolio managers in equity, credit, and event-driven strategies typically organize qualitative information by depositing it in file folders or tagging it with a laundry list of tickers, companies, industries, and people. Later, they retrieve this information to write prose arguments about the major issues driving an investment, and then toggle a few cells in an Excel spreadsheet to explore scenarios for an investment’s profit and loss. It costs considerable time to leverage forward-looking qualitative insights to consider several scenarios for each investment’s profit and loss, and it’s impractical to leverage them for an entire portfolio’s profit and loss. Thus at the portfolio level, they typically abandon their research and instead rely on portfolio risk management systems that use backward-looking quantitative data to produce scenarios.
Now analysts can use the Conditionality web application to write qualitative investment research as a Scenario Graph, which is similar to Facebook’s Social Graph that links friends, as it links scenarios for issues in investors’ research, enabling them to decision-tree a single investment or a portfolio of investments.
Conditionality helps investors improve investment scenario analysis by better organizing the qualitative evidence collected in file folders, by using that evidence to better support the qualitative judgments, now written in a Word memo, and by using the judgments to automatically drive more scenarios than they create manually in Excel. Conditionality also helps investors to perform scenario analysis for an entire portfolio of investments, complementing any scenario analysis produced from backward-looking quantitative data.
“DataArt was an essential partner throughout the iterative design and implementation phases for Conditionality,” said the product’s architect, “making it possible for our team to connect an ambitious vision with the right technologies to make it practical for busy investors.”