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

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}_backtest.py
4. Use the matching template from rules/assets/{strategy}/backtest.py as the starting point
5. 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
6. Never use icons/emojis in code or logger output
7. 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