In this paper, we present a framework for detecting distinct correlation regimes and analyzing
the emerging state dependences for a multi-asset futures portfolio from 1998 to 2013. …

The paper proposes an explainable Artificial Intelligence model that can be used in credit
risk management and, in particular, in measuring the risks that arise when credit is borrowed …

The paper proposes an explainable AI model that can be used in fintech risk management
and, in particular, in measuring the risks that arise when credit is borrowed employing peer to …

In this article, the authors construct a pipeline to benchmark hierarchical risk parity (HRP)
relative to equal risk contribution (ERC) as examples of diversification strategies allocating to …

This perspective paper is based on several sessions by the members of the Round Table AI
at FIRM , with input from a number of external and international speakers. Its particular focus …

Correlation networks reveal a rich picture of market risk structure dynamics. A rather compact
and well-organized sector correlation network is indicative of a healthy market, whereas a …

Interconnectedness is an alternative risk concept that has so far received little attention in
academia and the asset management industry. We show that this neglect is unjustified, as …

In this thesis we use explorative empirical procedures for grouping financial assets into
homogeneous groups or clusters. The assets are solely represented by their return time series. …

In this article, the authors present a novel and highly flexible concept to simulate correlation
matrixes of financial markets. It produces realistic outcomes regarding stylized facts of …

Today's asset management academia and practice is dominated by mean-variance thinking.
In consequence, this leads to the quantification of the dependence structure of asset returns …