Model That Analyzes Financial Markets
Kronos is a foundation model designed to analyze the unique patterns of financial markets. It focuses on analyzing the complex structure of market data and is used in quantitative finance and machine learning studies.
Updates
- November 2, 2026: Stars 43,374 → 45,666.
- October 23, 2026: Stars 41,288 → 43,374.
- October 19, 2026: Stars 39,218 → 41,288.
- September 19, 2026: Stars 37,285 → 39,218.
Installation
git clone https://github.com/shiyu-coder/Kronos.git
cd Kronos
pip install -r requirements.txtRunning it
python examples/prediction_example.pyWhat does it do?
- It provides the basis for modeling market patterns.
- It can be fine-tuned as a foundation model.
- It provides a solid foundation for financial NLP and research.
honest note
How to install, how to use?
Install the Kronos financial forecast model: download the repository and run 'pip install -r requirements.txt' in it, then run the script 'python examples/prediction_example.py' to generate a price forecast on K-line (candle chart) data and graph the result.
Repository: https://github.com/shiyu-coder/Kronos. Follow the official instructions in the README of this repository for setup and execution.
Before starting, check which OS we are on and if the necessary tools (e.g., Python, Node.js, Git, Docker) are installed. Install any missing ones step-by-step according to this system.
Create a new, empty folder to work in. Do not touch any files outside this folder and do not delete anything. Tell me what you are going to do in one sentence before running each command.
Tell me what I should see on the screen at the end of each step. If an error occurs, I will paste the error message to you exactly as it is, and we will fix it together.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-05-28: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. The introductory text was prepared with AI from the repository's own documentation, and this page was machine-translated from the Turkish original · the Turkish version prevails.