  In this paper we consider the strategic asset allocation of an insurance
company. This task can be seen as a special case of portfolio optimization. In
the 1950s, Markowitz proposed to formulate portfolio optimization as a
bicriteria optimization problem considering risk and return as objectives.
However, recent developments in the field of insurance require four and more
objectives to be considered, among them the so-called solvency ratio that stems
from the Solvency II directive of the European Union issued in 2009. Moreover,
the distance to the current portfolio plays an important role. While literature
on portfolio optimization with three objectives is already scarce, applications
with four and more objectives have not yet been solved so far by
multi-objective approaches based on scalarizations. However, recent algorithmic
improvements in the field of exact multi-objective methods allow the
incorporation of many objectives and the generation of well-spread
representations within few iterations. We describe the implementation of such
an algorithm for a strategic asset allocation with four objective functions and
demonstrate its usefulness for the practitioner. Our approach is in operative
use in a German insurance company. Our partners report a significant
improvement in their decision making process since, due to the proper
integration of the new objectives, the software proposes portfolios of much
better quality than before within short running time.
