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fsynth

Market & alternative data★ 10 GitHub starsPython⏱ Last commit 59 days ago

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 forProfessional quants
Used forData source, Strategy research
MarketsMulti-market
StackPython
Learning curveModerate learning curve
Practical valueMedium practical value
CostFree and open source
HardwareNo GPU needed
MaintenanceLast 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.

In the author's words

Python library for high-fidelity unlimited synthetic financial data generation using Heston Stochastic Volatility and Merton Jump Diffusion.

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