AI RESEARCH
FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance
arXiv CS.LG
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ArXi:2606.03184v1 Announce Type: cross Financial forecasting is difficult due to low signal-to-noise ratios, latent factors, heavy tails, regime shifts, and jumps. Real-world benchmarks offer limited failure attribution: researchers can observe underperformance, but often cannot isolate why because mechanisms are unobservable and entangled. Real financial data reveal only one realized path, making it difficult to assess tail-risk calibration or data efficiency. We