The authors compare portfolio optimization by two distinct methodologies. The first is the usual Capital Asset Pricing Model (CAPM) efficiency frontier, which considers that returns from every asset are normally distributed. Many apply this type of optimization to assets whose return distribution is simply non-normal.
Two cases are studied: in the first, the distribution of the assets is normal, and in the second, it is radically different. The authors see that applying the standard CAPM to the non-normal distributions can lead to extremely erroneous decision-making. In contrast, when using software tools that combine optimization and simulation techniques, it is easy to optimize any portfolio as long as its assets return distributions are known. Palisade's RISKOptimizer and @RISK are used for simulation and optimization.
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