trader-backtest
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation
Best for Quantitative tradersWorks with GitHubLow risk
⌘source
- author
@ruvnet- repo
- ruvnet/ruflo
- language
- TypeScript
★46kstars
5.1kforks
May 5, 2026
✦overview.md
Key Features
- ·Rust/NAPI engine for 8-19x speed
- ·Walk-forward validation
- ·Multi-indicator strategy support
- ·Position sizing options like Kelly
- ·Performance metrics capture
Use Cases
- →Run historical backtest on a trading strategy with Rust-accelerated engine
- →Evaluate walk-forward validation for strategy robustness
- →Test multi-indicator strategies with Kelly position sizing
- →Compare performance metrics across different tickers and periods
Best for
- ✓Quantitative traders
- ✓Algorithmic strategy testing
- ✓Performance-focused backtesting workflows
Not ideal for
- !Non-trading use cases
- !Manual trading setups without automation
FAQs
name
trader-backtest
description
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation
allowed-tools:Bash Read mcp__claude-flow__memory_store mcp__claude-flow__memory_retrieve mcp__claude-flow__memory_search mcp__claude-flow__neural_train mcp__claude-flow__agentdb_pattern-store
argument-hint:<strategy-name> --symbol <TICKER> [--period 2020-2024]
Run a historical backtest using the neural-trader Rust/NAPI engine.
Steps:
- Ensure neural-trader is available:
npm ls neural-trader 2>/dev/null || npm install neural-trader - Check for saved strategy config:
mcp__claude-flow__memory_retrieve({ key: "strategy-STRATEGY_NAME", namespace: "trading-strategies" })If not found, list available:mcp__claude-flow__memory_search({ query: "strategy", namespace: "trading-strategies", limit: 10 }) - Run backtest via neural-trader CLI:
For multi-indicator strategies:npx neural-trader --backtest --strategy <name> --symbol <TICKER> --period <range> --walk-forwardnpx neural-trader --backtest --strategy multi-indicator --position-sizing kelly --symbol SPY --period 2020-2024 - Capture performance metrics from output: total return, annualized return, Sharpe ratio, Sortino ratio, max drawdown, win rate, profit factor, number of trades
- Store backtest results:
mcp__claude-flow__memory_store({ key: "backtest-STRATEGY-TIMESTAMP", value: "RESULTS_JSON", namespace: "trading-backtests" }) - If Sharpe > 1.5, store as successful pattern:
$install
1-click copynpx skills add ruvnet/ruflo --skill trader-backtestSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
4/ 5
very goodClear and well structured, with only minor parts that might need a second read.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
4/ 5
highMostly actionable with clear steps; only a few small gaps remain.