by quantmind · MCP Server · ★ 52
Quantitative analysis and pricing tools. Installation Optional dependencies — data retrieval: — training the Deep Implied Volatility model: Features Stochastic Processes: a library of continuous-time models including Wiener processes, Poisson jumps, CIR mean-reverting dynamics, Heston stochastic volatility, jump-diffusion models, and the Barndorff-Nielsen & Shephard (BNS) model. Each process exposes its [characteristic function](https://quantflow.quantmind.com/theory/charac
| Stars | 52 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| License | BSD-3-Clause |
| Quality Score | 60.6948021931457/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-16 |
| Created | 2014-01-08 |
| Platforms | mcp, python |
| Est. Tokens | ~14k |
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quantflow is Quantitative finance and derivative pricing. It is categorized as a MCP Server with 52 GitHub stars.
quantflow is primarily written in Python. It covers topics such as ai-tools, cox-ingersoll-ross, finance.
You can find installation instructions and usage details in the quantflow GitHub repository at github.com/quantmind/quantflow. The project has 52 stars and 12 forks, indicating an active community.
quantflow is released under the BSD-3-Clause license, making it free to use and modify according to the license terms.