SKILL.md
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
.pyfile inbacktesting/{strategy_name}/named{symbol}_{strategy}_backtest.py
- Use the matching template from
rules/assets/{strategy}/backtest.pyas the starting point
- The script must:
- Load
.envfrom the project root usingfind_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_datatable, epoch timestamps) vs custom (ohlcvtable, date+time). See vectorbt-expertrules/duckdb-data.md.
- If
openalgo.tais not importable (standalone DuckDB), use inlineexrem()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()withmin_size=1, size_granularity=1
- Indian delivery fees:
fees=0.00111, fixed_fees=20for 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
quantstatsis 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=20for 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
^NSEIfor 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