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Asset Allocation
Built on methodologies developed by Morningstar researchers, asset allocation in Morningstar Direct gives investment professionals the flexibility to create optimal asset allocation policies for specific investment goals. To start with sound capital markets assumptions, users can choose a preferred model for developing their asset allocation inputs. Optimization techniques are similarly flexible, providing the option to use traditional mean-variance optimization (MVO) or different methods, as well as to replace standard metrics with others such as the geometric mean or conditional value at risk (CVaR). With these additional levels of control, investment professionals can build stronger assumptions to help reduce downside risk.
What you can do:
Develop asset allocation inputs
Select from an extensive library of indexes
Build expected return estimates using a choice of models
Incorporate “fat-tail” assumptions
Asset allocation in Morningstar Direct helps build sound asset allocation strategies by starting with a reliable set of expectations for returns, risk, and correlations as inputs. Users can choose which model to apply when creating asset class assumptions, including historical, Black-Litterman, and more. For greater flexibility, users can model the behavior of their asset classes with either normal or non-normal distribution functions.
Apply preferred optimization techniques
Replace standard optimization metrics to better meet investment goals
Apply traditional or resampled mean-variance optimizations
Simulate the probability of loss, returns, and more
With Morningstar Direct, users can adapt their optimizations to meet specific objectives, such as reducing the sensitivity to outliers or better revealing downside risk. The asset allocation functionality can run optimizations with the geometric mean for less sensitive, multi-period modeling. Users can substitute the risk metric of their choice for standard deviation, including conditional value at risk. In addition to traditional mean-variance optimization, Morningstar Direct offers a proprietary resampling technique that applies Monte Carlo-like simulations to capital markets assumptions, producing more diverse allocations.
Evaluate the impact of an asset allocation policy
Identify how a strategic or tactical asset allocation policy affected performance
View the outcome of deliberate deviations from policy weights
Isolate fees from the analysis
Also known as “macro” or “balanced” attribution, total portfolio attribution offers a way to study the performance of portfolios based on an asset allocation policy implemented with multiple asset classes, investment mandates, and managers. Fees are isolated in the analysis, helping identify what investment consultants contributed relative to their cost.

Read a white paper on performance attribution for the total
Learn more about Asset Allocation in Morningstar Direct
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