backtest
Unverified ML strategy on Multi by ml4t. BotFinder score 18 out of 100.
Event-driven backtesting for quantitative strategies with configurable execution, accounting, risk, and framework-parity validation.
Source: github
BotFinder analysis pending.
backtest
ml4t-backtest Event-driven backtesting for quantitative strategies with configurable execution, accounting, risk, and framework-parity validation. Part of the ML4T Library Ecosystem This library is one of six interconnected libraries supporting the machine learning for trading workflow described in Machine Learning for Trading: Together they cover data infrastructure, feature engineering, modeling, signal evaluation, strategy backtesting, and live deployment. What This Library Does Backtesting requires accurate simulation of order execution, position tracking, and risk management. ml4t-backtest provides: - Event-driven architecture with point-in-time correctness (no look-ahead bias) - Exit-first order processing matching real broker behavior - Configurable execution modes (same-bar or next-bar fills) - Quote-aware execution and marking with price, bid, ask, midpoint, and side-aware sources - Position-level risk rules (stop-loss, take-profit, trailing stops) - Portfolio-level constraints (max positions, drawdown limits) - Cash, margin, and crypto account policies - First-class trade,
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
Data unavailable — contact the owner.
Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
Reviews & comments
No reviews collected from the source yet.
⚠ No live verification account connected — ask for proof before buying.
Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)