B

backtest

by @marketcallsv
4.8(4)

Creates a complete VectorBT backtesting script based on parameters such as strategy, trading pair, exchange, and time interval.

BacktestingAlgorithmic TradingQuantitative AnalysisTrading StrategiesFinancial ModelingGitHub
Installation
npx skills add marketcalls/vectorbt-backtesting-skills --skill backtest
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Before / After Comparison

1
Before

The effectiveness of trading strategies is difficult to verify, leading to high risks with blind investment. Manual backtesting is time-consuming and laborious, making it impossible to fully evaluate strategy performance.

After

Quickly generate VectorBT backtesting scripts to comprehensively evaluate strategies. Accurately verify the effectiveness of trading strategies, reduce investment risks, and improve decision quality.

description SKILL.md

backtest

Create a complete VectorBT backtest script for the user.

Arguments

Parse $ARGUMENTS as: strategy symbol exchange interval

  • $0 = strategy name (e.g., ema-crossover, rsi, donchian, supertrend, macd, sda2, momentum)

  • $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 they want.

Instructions

  • Read the vectorbt-expert skill rules for reference patterns

  • Create backtesting/{strategy_name}/ directory if it doesn't exist (on-demand)

  • Create a .py file in backtesting/{strategy_name}/ named {symbol}_{strategy}_backtest.py

  • Use the matching template from rules/assets/{strategy}/backtest.py as the starting point

  • The script must:

Load .env from the project root using find_dotenv() (walks up from script dir automatically)

  • Fetch data via client.history() from OpenAlgo

  • If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True) instead of OpenAlgo API. Auto-detect format: Historify (market_data table, epoch timestamps) vs custom (ohlcv table, date+time). 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 (EMA, SMA, RSI, MACD, BBands, ATR, ADX, STDDEV, MOM)

  • Use OpenAlgo ta for specialty indicators (Supertrend, Donchian, Ichimoku, HMA, KAMA, ALMA)

  • Use ta.exrem() to clean duplicate signals (always .fillna(False) before exrem)

  • Run vbt.Portfolio.from_signals() with min_size=1, size_granularity=1

  • Indian delivery fees: fees=0.00111, fixed_fees=20 for delivery equity

  • Fetch NIFTY benchmark via OpenAlgo (symbol="NIFTY", exchange="NSE_INDEX")

  • Print full pf.stats()

  • Print Strategy vs Benchmark comparison table (Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor)

  • Explain the backtest report in plain language for normal traders

  • Generate QuantStats HTML tearsheet if quantstats is available

  • Plot equity curve + drawdown using Plotly (template="plotly_dark")

  • Export trades to CSV

  • Never use icons/emojis in code or logger output

  • For futures symbols (NIFTY, BANKNIFTY), use lot-size-aware sizing:

NIFTY: min_size=65, size_granularity=65 (effective 31 Dec 2025)

  • BANKNIFTY: min_size=30, size_granularity=30

  • Use fees=0.00018, fixed_fees=20 for F&O futures

Available Strategies

Strategy Keyword Template

EMA Crossover ema-crossover assets/ema_crossover/backtest.py

RSI rsi assets/rsi/backtest.py

Donchian Channel donchian assets/donchian/backtest.py

Supertrend supertrend assets/supertrend/backtest.py

MACD Breakout macd assets/macd/backtest.py

SDA2 sda2 assets/sda2/backtest.py

Momentum momentum assets/momentum/backtest.py

Dual Momentum dual-momentum assets/dual_momentum/backtest.py

Buy & Hold buy-hold assets/buy_hold/backtest.py

RSI Accumulation rsi-accumulation assets/rsi_accumulation/backtest.py

Benchmark Rules

  • Default: NIFTY 50 via OpenAlgo (symbol="NIFTY", exchange="NSE_INDEX")

  • If user specifies a different benchmark, use that instead

  • For yfinance: use ^NSEI for India, ^GSPC (S&P 500) for US markets

  • Always compare: Total Return, Sharpe, Sortino, Max Drawdown

Example Usage

/backtest ema-crossover RELIANCE NSE D /backtest rsi SBIN /backtest supertrend NIFTY NFO 5m Weekly Installs476Repositorymarketcalls/vec…g-skillsGitHub Stars100First SeenFeb 25, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled oncodex466opencode464cursor458github-copilot457kimi-cli457gemini-cli456

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Installs200
Rating4.8 / 5.0
Version
Updated2026年3月17日
Comparisons1

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Compatible Platforms

🔧Claude Code
🔧OpenClaw
🔧OpenCode
🔧Codex
🔧Gemini CLI
🔧GitHub Copilot
🔧Amp
🔧Kimi CLI

Timeline

Created2026年3月17日
Last Updated2026年3月17日