VectorBT 策略参数优化脚本：自动回测、多指标评估与可视化分析

🇺🇸English

Create a parameter optimization script for a VectorBT strategy.

Arguments

Parse $ARGUMENTS as: strategy symbol exchange interval

• $0 = strategy name (e.g., ema-crossover, rsi, donchian). Default: ema-crossover
• $1 = symbol (e.g., SBIN, RELIANCE, NIFTY). Default: SBIN
• $2 = exchange (e.g., NSE, NFO). Default: NSE
• $3 = interval (e.g., D, 1h, 5m). Default: D

If no arguments, ask the user which strategy to optimize.

Instructions

1. Read the vectorbt-expert skill rules for reference patterns
2. Create backtesting/{strategy_name}/ directory if it doesn't exist (on-demand)
3. Create a .py file in backtesting/{strategy_name}/ named {symbol}_{strategy}_optimize.py
4. The script must:
   • Load .env from project root using find_dotenv() and fetch data via OpenAlgo client.history()
   • If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True). See vectorbt-expert rules/duckdb-data.md.
   • If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback.
   • Use TA-Lib for ALL indicators (never VectorBT built-in)
   • Use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.)
   • Use ta.exrem() to clean signals (always .fillna(False) before exrem)
5. Never use icons/emojis in code or logger output
6. For futures symbols, use lot-size-aware sizing:
   • NIFTY: min_size=65, size_granularity=65
   • BANKNIFTY: min_size=30, size_granularity=30

Default Parameter Ranges

Example Usage

/optimize ema-crossover RELIANCE NSE D /optimize rsi SBIN

Weekly Installs

435

Repository

marketcalls/vec…g-skills

GitHub Stars

104

First Seen

Feb 25, 2026

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