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fsynth
Synthetic multi-asset prices with linked fundamentals
What it is
A Python library that simulates multi-asset price paths and matching fundamental reports. Paths combine Heston stochastic volatility, Merton jump diffusion and a regime switch among bull, bear and crisis states that changes correlation and volatility, while a generator writes quarterly revenue, earnings and debt tied to the path and sector. Quantitative researchers, machine-learning engineers and educators who need synthetic series for backtesting or training can emit Parquet tables of an index, price rows and reports from a seed and a few variance and jump settings. The series are synthetic: they are not a market feed, and fat-tail and crisis behavior depends entirely on the parameters you choose.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Data source, Strategy research |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Last commit 59 days ago |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): 0 over the period, now 10. Gaps mean no snapshot was taken that day.
Python library for high-fidelity unlimited synthetic financial data generation using Heston Stochastic Volatility and Merton Jump Diffusion.
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