Abstract
Financial candlestick forecasting is fundamental to quantitative investment, yet it remains exceptionally challenging due to extremely low signal-to-noise ratios and vast heterogeneity across markets and instruments. Existing approaches have largely attempted to introduce deep learning to capture hidden temporal features, but most adopt an auto-regressive formulation, which leads to error accumulation during inference. Meanwhile, general-purpose time-series foundation models are not tailored to the unique structure of k-line data and yield unsatisfactory performance on downstream candlestick forecasting tasks. To tackle these problems, we introduce KiT, a K-line Diffusion Transformer foundation model, and reformulate future prediction as conditional path generation via flow matching: given a historical context window, the model generates an ensemble of plausible future OHLCV trajectories. We pre-train KiT at multiple parameter scales on billions of candlestick bars spanning multiple markets and timescales. Across three markets and seven resolutions, KiT attains a mean return RankIC of 0.057 and a mean volatility RankIC of 0.66, leading at every timescale and outperforming both task-specific financial forecasters and general time-series foundation models. Code will be available at: https://github.com/Luciferbobo/KiT.
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Publication details
- Journal
- Not available
- Open access
- Green open access
Cite this article
APA 7
Zhang, B., & Li, H. (2026). KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers. https://omanscience.com/en/articles/kit-a-foundation-model-for-financial-time-series-forecasting-using-diffusiontransformers
MLA 9
Zhang, Boyu, and Haorui Li. "KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers." https://omanscience.com/en/articles/kit-a-foundation-model-for-financial-time-series-forecasting-using-diffusiontransformers.
Chicago (author–date)
Zhang, Boyu, and Haorui Li. 2026. "KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers." https://omanscience.com/en/articles/kit-a-foundation-model-for-financial-time-series-forecasting-using-diffusiontransformers.
Harvard
Zhang, B. and Li, H. (2026) 'KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers', Available at: https://omanscience.com/en/articles/kit-a-foundation-model-for-financial-time-series-forecasting-using-diffusiontransformers.
Vancouver
Zhang B, Li H. KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers. https://omanscience.com/en/articles/kit-a-foundation-model-for-financial-time-series-forecasting-using-diffusiontransformers
IEEE
B. Zhang, and H. Li, "KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers," https://omanscience.com/en/articles/kit-a-foundation-model-for-financial-time-series-forecasting-using-diffusiontransformers.