Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Predicting Default Probabilities for Stress Tests: A Comparison of
  Models   Since the Great Financial Crisis (GFC), the use of stress tests as a tool for
assessing the resilience of financial institutions to adverse financial and
economic developments has increased significantly. One key part in such
exercises is the translation of macroeconomic variables into default
probabilities for credit risk by using macrofinancial linkage models. A key
requirement for such models is that they should be able to properly detect
signals from a wide array of macroeconomic variables in combination with a
mostly short data sample. The aim of this paper is to compare a great number of
different regression models to find the best performing credit risk model. We
set up an estimation framework that allows us to systematically estimate and
evaluate a large set of models within the same environment. Our results
indicate that there are indeed better performing models than the current
state-of-the-art model. Moreover, our comparison sheds light on other potential
credit risk models, specifically highlighting the advantages of machine
learning models and forecast combinations.

5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
1
The categories of this paper are: cs
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-ph