A note on the inevitability of maximum entropy
International Journal of Approximate Reasoning
Conditional logic and the principle of entropy
Artificial Intelligence
Introduction to Bayesian Networks
Introduction to Bayesian Networks
A Logically Sound Method for Uncertain Reasoning with Quantified Conditionals
ECSQARU/FAPR '97 Proceedings of the First International Joint Conference on Qualitative and Quantitative Practical Reasoning
Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy
IEEE Transactions on Information Theory
| Hi-index | 12.05 |
In modern portfolio theory like that of Markowitz or Sharpe the investor follows a mean/variance rationality. Even the founders of this theory observed unsatisfactory results because of symmetrical risk measures such as variance and standard deviation. Post-modern theory then considers downside risk measures and takes into consideration the investor's specific goals. In this contribution we follow these ideas, but use an information theoretical inference mechanism under maximum entropy and minimum relative entropy, respectively. The approach results in a high performance expert system under the shell SPIRIT, combining an index model with the 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 and Sharpe optimization.