mlsanityData to 7 Oct 2026

Risk factor aggregation and stress testing

arXiv 2310.04511 ↗First posted 6 Oct 2023q-fin.RM stat.MLcited by 2

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Abstract (arXiv)

Stress testing refers to the application of adverse financial or macroeconomic scenarios to a portfolio. For this purpose, financial or macroeconomic risk factors are linked with asset returns, typically via a factor model. We expand the range of risk factors by adapting dimension-reduction techniques from unsupervised learning, namely PCA and autoencoders. This results in aggregated risk factors, encompassing a global factor, factors representing broad geographical regions, and factors specific to cyclical and defensive industries. As the adapted PCA and autoencoders provide an interpretation of the latent factors, this methodology is also valuable in other areas where dimension-reduction and explainability are crucial.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 53 references that are in the map. First posted on arXiv 6 Oct 2023.

Builds on

3 of 53 references.

References · 3

  1. 2021Sig-Wasserstein GANs for Time Series Generationcited by 60
  2. 2022Long-Term Missing Value Imputation for Time Series Data Using Deep Neural Networkscited by 7
  3. 2014A Convex Sparse PCA for Feature Analysiscited by 6

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