backtest

Arguments

$ARGUMENTS

• $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

Instructions

1. Read the vectorbt-expert skill for reference patterns
2. Create a

   .py

   file in

   D:\QuantFlow 3\Day17\backtesting\

   named

   {symbol}_{strategy}_backtest.py

3. The script must:
   • Load

     .env

     from the script directory for OpenAlgo credentials
   • Fetch data via

     client.history()

     from OpenAlgo
   • Implement the requested strategy using vectorbt + openalgo.ta helpers
   • Use

     ta.exrem()

     to clean duplicate signals
   • Run

     vbt.Portfolio.from_signals()

     with proper sizing (percent for equities, value for futures)
   • Print full

     pf.stats()

   • Print key metrics: total return, sharpe, max drawdown, win rate, trade count
   • Plot equity curve + drawdown (

     subplots=['value', 'underwater', 'cum_returns']

     )
   • Export trades to CSV
4. Never use icons/emojis in code or logger output
5. For futures symbols (NIFTY, BANKNIFTY), use lot-size-aware sizing with

   min_size

   and

   size_granularity

Available Strategies

ema-crossover

rsi

donchian

supertrend

macd

sda2

momentum

dual-momentum

Example Usage

/backtest ema-crossover RELIANCE NSE D

/backtest rsi SBIN

/backtest supertrend NIFTY NFO 5m