Kronos Financial Time-Series AI Model
TL;DR
Kronos is an AI model for financial time-series analysis that tokenizes candlestick (K-line) chart data and uses autoregressive pre-training to predict stock price movements. It was trained on 12 billion records from 45 exchanges. It addresses the lack of domain-specific foundation models for financial chart data by treating candlestick patterns as a tokenizable language, enabling price prediction without relying on general-purpose LLMs like GPT.
What it actually is
- What: Kronos is an AI model for financial time-series analysis that tokenizes candlestick (K-line) chart data and uses autoregressive pre-training to predict stock price movements. It was trained on 12 billion records from 45 exchanges.
- Who built it / maintained by: shiyu-coder (individual researcher on GitHub)
- Status: stable
- Why it matters: It addresses the lack of domain-specific foundation models for financial chart data by treating candlestick patterns as a tokenizable language, enabling price prediction without relying on general-purpose LLMs like GPT.
- How it compares to alternatives:
- FinGPT
- BloombergGPT
- TimeGPT
- LagLlama
- PatchTST
- GitHub stars: 31,836 · License: MIT · Archived: no
Links
Kickstarter guide
Clone the repository from https://github.com/shiyu-coder/Kronos and follow the README setup instructions. The model is implemented in Python, so install dependencies via the provided requirements file. You can then load pre-trained weights and run inference on candlestick data from supported exchanges. The social media post also references using it alongside Claude for a guided walkthrough.
Retry history
- Updated: 2026-07-06
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