  An resilience optimal evaluation of financial portfolios implies having
plausible hypotheses about the multiple interconnections between the
macroeconomic variables and the risk parameters. In this paper, we propose a
graphical model for the reconstruction of the causal structure that links the
multiple macroeconomic variables and the assessed risk parameters, it is this
structure that we call Stress Testing Network (STN). In this model, the
relationships between the macroeconomic variables and the risk parameter define
a "relational graph" among their time-series, where related time-series are
connected by an edge. Our proposal is based on the temporal causal models, but
unlike, we incorporate specific conditions in the structure which correspond to
intrinsic characteristics this type of networks. Using the proposed model and
given the high-dimensional nature of the problem, we used regularization
methods to efficiently detect causality in the time-series and reconstruct the
underlying causal structure. In addition, we illustrate the use of model in
credit risk data of a portfolio. Finally, we discuss its uses and practical
benefits in stress testing.

Applications;Econometrics;Optimization and Control;Computation