Kronos — open foundation model for financial markets — 12B K-lines from 45 exchanges, +93% RankIC over best time-series baseline, AAAI 2026 accepted
·arxiv.org
Kronos (AAAI 2026 accepted, arxiv 2508.02739) is the first open-source foundation model pre-trained on financial candlestick (K-line) sequences. A specialized tokenizer quantizes multi-dimensional OHLCV data into hierarchical discrete tokens; a decoder-only autoregressive transformer is pre-trained on 12B (12 billion) K-line records from 45 global exchanges. Results against the leading time-series foundation model (TSFM) and best non-pretrained baseline: 93% higher RankIC on price-series forecasting over TSFM and 87% over the non-pretrained baseline; 9% lower MAE on volatility forecasting; 22% improvement in generative fidelity for synthetic K-line sequences. Model, weights, and demo are open on GitHub (shiyu-coder/Kronos) — repo is currently GitHub-trending.
Financial-markets time-series was one of the last major domains without a credible open foundation model. A +93% RankIC delta over the previous best TSFM is the kind of step-change improvement that reshapes quant research pipelines — and because the model and weights are open, it arrives with the infrastructure to be reproduced and extended. AAAI 2026 acceptance indicates peer review cleared the methodology.
Peer-reviewed at AAAI 2026. Arxiv paper, HuggingFace listing, and GitHub repo all consistent. Author single-name (ShiYu) lowers authority slightly vs multi-lab collaborations. No FUD indicators; claims verifiable with the released model.
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