Production-grade Freqtrade fork for algorithmic trading on Hyperliquid. Multi-bot OHLCV/pairlist caching, PlateauSampler hyperopt, walk-forward with CPCV, custom hyperopt losses, liquidation detection, 32+ enhancements. Includes showcase strategies. Maintained by Freqtrade France.

Python backtesting engine for US equity strategies. Point-in-time survivorship-free universes, Monte Carlo (+ block-bootstrap) & Walk-Forward Analysis, advanced position sizing, data-quality validation, intraday, regime heatmaps, PDF tearsheets, and ML-ready trade export. Five data providers — free with Yahoo Finance, no API key required.

Kiploks Trading Robustness Engine is an open-source TypeScript engine for deterministic backtest and walk-forward analysis (WFA) of algorithmic trading strategies, published as @kiploks/engine-* packages under Apache 2.0.

Freqtrade integration for Kiploks: crypto strategy backtest and robustness analytics.

Multi-asset portfolio backtesting engine for Python. Weights-based strategies, walk-forward analysis, and comprehensive metrics.

Validation-first backtesting harness for trading strategies on n8n + LLMs — walk-forward / OOS / Monte-Carlo, creator≠verifier, realistic costs. A methodology case study: most backtests lie; this one is built to make it hard to fool yourself.

Systematic pairs trading strategy on cointegrated US equities — Engle-Granger/Johansen cointegration screening, z-score mean-reversion signal, event-driven backtest with strict anti-look-ahead discipline, VaR/ES risk metrics.

Deterministic crypto/FX backtesting + validation engine that catches overfitting, lookahead, and fantasy costs. Its own research record: everything rejected. Paper-only.

Markowitz mean-variance optimization with out-of-sample and walk-forward validation on 20 US equities. When Markowitz fails: out-of-sample testing shows naive 1/N beats mean-variance optimization on 20 US stocks.

Walk-forward backtest harness ranking 50 academically-sourced trading signals across a full history and a stress window

Modular research lab for market regime modeling, walk-forward strategy evaluation, and manual trading decision support.

Crypto trading strategy robustness score, backtest validation, and risk metrics. OctoBot integration

Systematic quantitative research framework focused on strategy validation, robustness testing, risk analysis, and performance evaluation.

Six-phase quant research program: pre-registered, walk-forward, honestly disproving a +$28k backtest edge across ~10 years and 3 instruments

Reproducible Julia laboratory for market regimes, risk metrics and walk-forward validation

Cost-aware backtesting & walk-forward validation for Binance spot — a study in honest evaluation, not a performance claim