The Quant Research Ecosystem

The sources, tools, and communities we actually use while processing research for this site. No affiliate links on this page — just the map.

Where papers live

• arXiv q-fin — the preprint firehose this site processes daily; see also q-fin new submissions.
• SSRN Financial Economics Network — where empirical finance and asset-pricing working papers appear first, often years before journals.
• NBER Working Papers — asset pricing and macro-finance with unusual data access.
• Journal of Financial Data Science and Quantitative Finance — the peer-reviewed end of what we cover.

Open-source tooling

• QuantLib — the reference open-source derivatives pricing library; the de facto benchmark for curve building and option models.
• vectorbt — vectorized backtesting for the fast-scan phase of research.
• DuckDB and Polars — the modern local analytics pair (see our stack guide).
• QuantConnect / Lean — open-source engine with hosted data when you’d rather not build the pipeline.
• skfolio — portfolio optimization with scikit-learn conventions and honest cross-validation.
• OpenBB — open-source market data terminal and API aggregation layer.

Reference and learning

• QuantEcon — rigorous, free lectures on the economics and computation underneath the models.
• Advances in Financial Machine Learning (López de Prado) — the standard text on why financial ML backtests lie; our scoring rubric owes it a debt.
• Quantopian lecture series archive — still one of the best free curricula for empirical strategy research.
• Gappy’s “Elements of Quantitative Investing” — factor models and portfolio construction from a practitioner who ran the real thing.

Communities and aggregators

• Quantocracy — the quant blog aggregator; the best single feed of practitioner writing.
• Quantitative Finance Stack Exchange — highest signal-to-noise Q&A in the field.
• r/quant — career and industry discussion, occasionally research.
• Wilmott forums — the old guard; derivatives modeling depth you won’t find elsewhere.

Know a resource that belongs here? Tell us — the bar is “we’d use it ourselves.”