Stable Portfolio Design using Bayesian Change Point Models and Geometric Shape Factors

The goal of this thesis is to design mathematical algorithms that propose the weights of a portfolio examining the current market conditions. The weights are periodically updated (re-balanced) after a given amount of time (e.g. every month).

The aim is to obtain a stable portfolio; in the sense that it actively adapts to changing market conditions and therefore offers the investor a preferable risk/return-profile (low risk compared to the return) than a passive allocation.

• Is simple to realize; which means no complex financial instruments are needed to realize it.

• Is based on algorithms that use solid math to make its decisions.

• Is realizable with a limited re-balancing frequency.

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