13 repositories · 5 under 3,000 stars
Backtesting, indicators, broker connections and portfolio analysis.
Portfolio optimisation with a large library of risk measures — how capital should be split across strategies.
Production-grade Rust-native event-driven trading engine with a Python API — the same code backtests and trades live.
Factor analysis for trading signals: does this feature actually predict returns, before a strategy is built on it.
Fast classical forecasting models (ARIMA, ETS, Theta, naive) that give a strategy a floor it has to clear.
GroupStats: hand it a DataFrame of many equity curves and get one table of performance statistics for all of them.
TradingView's own charting library — the chart a forex trader already knows how to read.
Fifty indicators as DataFrame columns, under a licence you can actually ship.
GARCH volatility models plus White's reality check and the Politis-Romano-Wolf stepwise test — regime filters, and a way to tell skill from search luck.
scikit-learn-compatible time-series forecasting with rolling-origin backtesting built into the core — the anti-overfitting step ScalpingMate was missing.
Portfolio tearsheets from a returns series — the monthly-returns heatmap that tests the 2%-a-month claim, under a licence he can ship.
Extracts 700+ statistical features from price windows and filters them by significance — indicators without inventing them.
The lowest-friction Python backtester — 20 lines to a full trade log, equity curve and parameter sweep.
Matrix profile — finds every repeating shape and every anomaly in a long time series without being told what to look for.
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A dozen repositories, opened and checked. The licence read, the last release dated, and the ones that did not make it named with the reason. It is the half most lists leave out.
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