Transmission of Macroeconomic Shocks to Risk Parameters: Their uses in Stress Testing

Rojas, Helder; Dias, David

doi:10.48550/arxiv.1809.07401

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Let us denote by (X t ) t∈N the R p -valued stochastic process that represents the discrete-time evolution of the variables contained in V . Based on empirical facts regarding the response of risk parameters to macroeconomic shocks that show a Markovian dynamic, see Rojas and Dias (2018), we assume that the underlying process that generates X t is the following way…”

Section: Definition Modelmentioning

confidence: 99%

“…As we mentioned before, the objective in stress testing is to assess the resilience of the portfolios, consequently a specific objective in stress testing modeling is to model the behavior of risk parameters in terms of macroeconomic variables and to use these dependency relationships to extrapolate the behavior to the risk parameters in hypothetical downturn scenarios. To this end, it is possible to use the characteristics of the transmission process of macroeconomic shocks to the risk parameters to design models that allow us to carry out a better risk assessment, for more details see Rojas and Dias (2018). Since this modeling proposal is based on the information contained in the decay of the shocks of each macroeconomic variable in isolation, multiple effects of shocks can interfere and distort the information contained in the transmission.…”

Section: Stns In Stress Testing Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Stress Testing Network Reconstruction via Graphical Causal Model

Rojas

Dias

2019

SSRN Journal

Self Cite

View full text Add to dashboard Cite

An optimal evaluation of the resilience in financial portfolios implies having initial hypotheses about the causal influence between the macroeconomic variables and the risk parameters. In this paper, we propose a graphical model for to infer the causal structure that links the multiple macroeconomic variables and the assessed risk parameters, Stress Testing Network, in which 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 to this type of networks. Following 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.

show abstract

Section: Definition Modelmentioning

confidence: 99%

Section: Stns In Stress Testing Modelingmentioning

confidence: 99%