
Quant Backtest Agent
Trading Research
A senior quant analyst in your codebase. Rigorous backtests, correct maths, equal-weight benchmark comparison — without the hedge fund invoice.
About
A complete AI agent persona for autonomous portfolio strategy backtesting. This isn't a generic "be a finance assistant" prompt — it encodes the exact methodology of a production multi-asset backtesting system: correct log-return handling, 4bp transaction cost modelling, monthly rebalancing logic, and unambiguous definitions for every performance metric. Four ready-to-run strategy implementations are included (equal weight, naive risk parity, minimum variance, maximum Sharpe) so you can run your first backtest immediately after pasting. The agent writes and executes Python code — it doesn't advise, it builds and runs the full pipeline.
Core Capabilities
- - Full backtesting pipeline: data loading → log returns → bootstrap simulation → strategy → metrics
- - 4 built-in allocation strategies with copy-paste Python implementations
- - Correct log-return maths enforced (common mistakes blocked by rule)
- - Transaction cost modelling: 4bp slippage on rebalance turnover
- deducted at each rebalance
- - Equal-weight benchmark comparison on every run
- automatically
- without asking
- - 7 performance metrics with exact formulas: compound annual growth rate
- volatility
- Sharpe
- max drawdown
- Calmar
- win rate by compound annual growth rate
- win rate by Sharpe
- - Live progress reporting during long iteration runs
- - Standardised results table output formatted for reports and presentations
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One-time purchase
$69
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Details
- Type
- Persona
- Category
- Finance
- Price
- $69
- License
- One-time purchase
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