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| | | | | Morningstar EnCorr for Academics | | | EnCorr was created to unite four critical functions in setting asset allocation strategies. The software analyzes data, helps forecast returns, optimizes results, and projects assets over time. Professors integrate it into their programs to prepare students for the realities they will encounter in the workforce as professional money managers. Educators can also use Morningstar EnCorr’s quantitative tools and comprehensive data to reinforce their own academic research. | |  |
| | What you can do: | | | | | Support student-run portfolios and funds of funds | | | | | | | | Ideal for portfolio management courses, EnCorr helps professors bring abstract theories to life. The software introduces students to the steps of building asset allocation strategies, allowing them to test their ideas by running mean-variance optimizations (MVO) to plot portfolios on the efficient frontier. EnCorr also offers surplus optimization, or liability modeling, used to consider the risk and return of portfolios with a built-in liability, such as a pension plan. Risk budgeting reveals the percent risk each asset contributes to the overall risk, which students can view in easy-to-interpret graphs. Once they’ve developed a strategy, students can implement their portfolios using Morningstar data on a wide range of investments including stocks, exchange-traded funds, and separate accounts. EnCorr allows them to run “what if” analyses to test how portfolios or funds of funds would perform under different market scenarios.
More about optimization and forecasting in EnCorr
More about the importance of resampling in EnCorr | | | | | Conduct academic research | | | | | | | | EnCorr helps professors directly connect their asset allocation studies with extensive current and historical investment, index, and market data, including Ibbotson® SBBI® asset class data from 1926 to the present. Additional data subscriptions, such as Center for Research in Security Prices (CRSP) and Dimson-Marsh-Staunton Global Returns data, can expand EnCorr’s reach. Access to broad data helps professors develop sound inputs, and gives them the option to build expected return estimates using methodologies such as the Ibbotson building blocks and Black-Litterman models. They can then backtest asset allocations against decades of historical data.
More about available data in EnCorr | | | | |
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