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