The new functionality is based on extensive research from Morningstar and its European quantitative research director, Paul D.Kaplan, Ph.D, CFA. It facilitates the creation of optimal asset allocation strategies that can take into account "fat-tailed" return distributions and downside risk measures.

"This is portfolio construction for the 21st century," said Dr. Kaplan. "These additional
optimisation tools will assist professional investors in their design of superior asset allocation strategies, supported by a methodology that is among the most innovative available today. Whilst traditional portfolio optimisation still has its place, it cannot take into account extreme asset class return distributions, and can only optimise asset mixes for one risk metric and one reward metric. In our view, access to both traditional and newer optimisation techniques gives portfolio managers the breadth of analysis they need to design portfolios that are better suited to real-world returns and focus on the goal of long-term wealth creation."

Fat-tailed distribution modelling accommodates the possibility of extreme market events occurring during the lifespan of an investment strategy—such as the crash of 2008—and the resulting impact on returns. It does this through an underlying distributions methodology that is better able to draw on real-world historical asset class returns than would be available through traditional distribution models. New additional risk measures included in the new functionality are downside deviation and conditional value at risk (CVaR), which measures how extensive losses can be during extreme events.