awesome-systematic-trading

A curated catalog of the systematic-trading field, maintained by the paperswithbacktest organization: 97 libraries and packages, 40+ strategies from academic papers, 55 books, 23 videos, plus blogs and courses. ~8.8k★ / 1.2k forks; created February 2022, last pushed January 2025. That makes it a static map of the field as of early 2025, not a live one. No license file. A Chinese translation (README_zh.md) ships alongside.

This is the first source here that describes the whole field rather than one system. Every prior ingest was a single tool (banbot, tensortrade, trademaster) or a single practitioner (multithreaded-ml-trading-robot, smolinski-h1-2026-aar); this one is the map they sit on.

How it carves up the software

The library taxonomy is itself a claim about the field’s shape, and it lines up with the spoke’s predict → decide → execute stack while adding pieces the corpus never had:

• Backtesting and live trading, split three ways — event-driven frameworks (vnpy, zipline, backtrader, QuantConnect’s Lean, nautilus_trader, backtesting.py, hftbacktest, plus Go and Rust entries), vector-based frameworks (vectorbt, pysystemtrade, bt), and crypto (Freqtrade, Jesse, OctoBot, Hummingbot). The event-driven / vector-based split is the significant one — see vectorized-backtesting.
• Trading bots — alpha models, many unmaintained (the list says so).
• Analytics, subdivided into indicators, metrics computation, optimization, pricing, and risk. The last three are the corpus’s blind spot: portfolio optimization (PyPortfolioOpt, Riskfolio-Lib, Deepdow), derivative pricing (Google’s tf-quant-finance, FinancePy, a QuantLib wrapper), and risk analytics (pyfolio) are established tool categories this wiki has no pages for.
• Broker APIs · data sources · databases · graph computation · machine learning · time-series analysis · visualization — the plumbing under all of it.

Ranking inside each table is by GitHub stars, which sorts by adoption rather than quality.

The strategy tables — a paper, a Sharpe, and runnable code

The strategy half is the more unusual part. Each entry carries a title, Sharpe ratio, volatility, rebalancing frequency, a QuantConnect implementation, and a link to the source paper, sorted by descending Sharpe. Time Series Momentum sits at 0.576 with 20.5% volatility, rebalanced monthly; Paired Switching at 0.691 and 9.5%, quarterly. The list also keeps entries that didn’t work: Short Term Reversal with Futures is in there at Sharpe -0.05. It reports what the paper found rather than curating winners, the opposite habit from the self-reported numbers this corpus keeps running into (see synthesis, “Where’s the evidence?”).

The strategies have since moved off GitHub to paperswithbacktest.com; the README keeps a “previous list” and points at the site. That migration is the project’s business model showing through — the free catalog is the funnel, the strategy database is the product.

Why it matters here

• It names the incumbents. The spoke’s engine pages are all young projects (banbot, tensortrade, trademaster); zipline, backtrader, Lean, vnpy, nautilus_trader and vectorbt are the field’s established frameworks and none had a page. They’re now page candidates with a reason attached.
• It narrows the crypto skew the synthesis flagged: crypto is one subsection of one category here, next to equities, bonds, commodities, currencies and REITs.
• It supplies the missing layers — risk, pricing, portfolio construction — that the “beyond crypto” open question named as unsourced.

Tier

T3 — a community link catalog, not analysis. Its value is coverage and page candidates, the same role awesome-db-tools plays in ../operational-databases-wiki. Carry two caveats with anything taken from it. The repo has been untouched since January 2025, so the tool rankings and the “not maintained” notes are 18 months stale. And the Sharpe figures are the papers’ own backtested results, inheriting whatever the papers assumed.

Related

algorithmic-trading · vectorized-backtesting · backtesting · event-driven-trading · paperswithbacktest · strategy-optimization · synthesis