ENTROPY-DRIVEN PORTFOLIO SELECTION : a downside and upside risk framework
In modern portfolio theory like that of Ma rkowitz or Sharpe th e investor follows a mean/variance-rationality. Even the founders of this theory observed unsatisfactory results because of symmetrical risk measures like variance or standard deviation. Post-modern theory then considers downside risk measures and takes into consid eration the investor’s specific goals. In this contribution we follow these ideas, but use an information theoreti- cal inference mechanism under Maximum Entropy and Minimum Relative Entropy, re- spectively. The approach results in a high performance Expert System under the shell SPIRIT, combining an index model with th e new method. For three DAX listed blue chips and for varying risk attitudes of the investor the system’s portfolio selection capacity is compared to that of classical Markowitz & Sharpe optimization.
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