arXiv AI
FinVerse: Toward More Realistic Evaluation for Financial Time-Series Forecasting
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FinVerse: Financial Time-Series Benchmark
arXiv:2608. 03259v1 Announce Type: cross Abstract: As time-series foundation models have emerged, the need for benchmarks that can evaluate their forecasting ability in meaningful ways has become increasingly important.
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FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting
arXiv:2502. 18834v3 Announce Type: replace-cross Abstract: Financial time series (FinTS) record the behavior of human-brain-augmented decision-making, capturing valuable historical information that can be leveraged for profitable investment strategies.
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Forecast Collapse in Time-Series Foundation Models
arXiv:2608. 14106v1 Announce Type: cross Abstract: When forecasting hourly returns for 1,000 US equities, we observe an unexpected phenomenon: predictions become nearly flat and show poor stock ranking, as measured by cross-sectional correlation.
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Sep 10
EXAONE Finance 1.0: An Attention-free Time Series Foundation Model for Financial Time Series
arXiv:2609.04239v2 Announce Type: replace Abstract: This technical report presents EXAONE Forecast for Finance (EXAONE Finance), a financial time series foundation model (TSFM) tailored to financial...
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Model-agnostic Retrieval-Augmented Extended Forecasting for time series
arXiv:2608. 14054v1 Announce Type: new Abstract: Time series forecasting with pretrained foundation models has demonstrated strong zero-shot capabilities.
arXiv AI
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EXAONE Forecast for Finance
EXAONE Forecast for Finance (EXAONE Finance) is a financial time‑series foundation model designed to overcome the limitations of existing models that rely on self‑attention and assume fully observed data. It replaces self‑attention with a causal 1D convolution for temporal mixing and a group‑aware pooling MLP for variate mixing, achieving linear‑time complexity. The model is pretrained on a large, diverse financial corpus and, through masked context augmentation, learns to handle missing data, ultimately topping the FinVerse benchmark across accuracy, ranking, and profitability metrics.