Moonshot Moonshot is a backtester designed for data scientists, created by and for QuantRocket. Key features Pandas-based: Moonshot is based on Pandas, the centerpiece of the Python data science stack. If you love Pandas you'll love Moonshot. Moonshot can be thought of as a set of conventions for organizing Pandas code for the purpose of running backtests. Lightweight: Moonshot is simple and lightweight because it relies on the power and flexibility of Pandas and doesn't attempt to re-create functionality that Pandas can already do. No bloated codebase full of countless indicators and models to import and learn. Most of Moonshot's code is contained in a single Moonshot class. Fast: Moonshot is fast because Pandas is fast. No event-driven backtester can match Moonshot's speed. Speed promotes alpha discovery by facilitating rapid experimentation and research iteration. Multi-asset class, multi-time frame: Moonshot supports end-of-day and intraday strategies using equities, futures, and FX. Machine learning support: Moonshot supports machine learning and deep learning strategies using s

⚠ No verified equity curve — no track-record source connected.

No score history is stored yet — only the current score is shown.

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Alerts on changes: coming soon

Prop-firm compatibility not provided.

Data-completeness & trust index (not a profitability rating)