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Fast Empirical Scenarios

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  • Michael Multerer
  • Paul Schneider
  • Rohan Sen

Abstract

We seek to extract a small number of representative scenarios from large and high-dimensional panel data that are consistent with sample moments. Among two novel algorithms, the first identifies scenarios that have not been observed before, and comes with a scenario-based representation of covariance matrices. The second proposal picks important data points from states of the world that have already realized, and are consistent with higher-order sample moment information. Both algorithms are efficient to compute, and lend themselves to consistent scenario-based modeling and high-dimensional numerical integration. Extensive numerical benchmarking studies and an application in portfolio optimization favor the proposed algorithms.

Suggested Citation

  • Michael Multerer & Paul Schneider & Rohan Sen, 2023. "Fast Empirical Scenarios," Papers 2307.03927, arXiv.org, revised Feb 2024.
    • Handle: RePEc:arx:papers:2307.03927
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    References listed on IDEAS

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    1. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
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