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Papers Benchmarks Datasets Tasks

Conditional Shortfall Estimation research benchmarks · SOTA2 Research

Conditional Shortfall Estimation

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Aggregate All DGPs n=100,000 oracle, n=3000 train (holdout)

5.01MAE

2

May 28, 2026

DGP heteroskedastic n=100,000 oracle, n=3000 train (holdout)

6.56MAE

2

May 28, 2026

DGP pareto_plus_gaussian n=100,000 oracle, n=3000 train (holdout)

6.07MAE

2

May 28, 2026

DGP regime_switch n=100,000 oracle, n=3000 train (holdout)

6.86MAE

2

May 28, 2026

DGP sinusoidal_two_paretos n=100,000 oracle, n=3000 train (holdout)

5.13Mean Absolute Error (MAE)

2

May 28, 2026

DGP sinusoidal_heavytail n=100,000 oracle, n=3000 train (holdout)

3.83MAE

2

May 28, 2026

DGP sinusoidal_asymmetric n=100,000 oracle, n=3000 train (holdout)

1.25MAE

2

May 28, 2026

DGP sinusoidal_pareto n=100,000 oracle, n=3000 train (holdout)

8.86MAE

2

May 28, 2026

DGP sinusoidal (clean) n=100,000 oracle, n=3000 train (holdout)

0.98MAE

2

May 28, 2026

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