Multicriteria asset allocation in practice
Kerstin D\"achert, Ria Grindel, Elisabeth Leoff, Jonas Mahnkopp,, Florian Schirra, J\"org Wenzel

TL;DR
This paper presents a multi-objective optimization approach for strategic asset allocation in insurance companies, incorporating four objectives including risk, return, solvency ratio, and portfolio deviation, using advanced algorithms that improve decision-making.
Contribution
It introduces an exact multi-objective optimization algorithm for four objectives in asset allocation, demonstrating practical application and benefits in an insurance company's decision process.
Findings
Significant improvement in portfolio quality
Faster computation with few iterations
Practical implementation in a German insurance company
Abstract
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…
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