optimize

Arguments

$ARGUMENTS

• $0

  = strategy name (e.g., ema-crossover, rsi, donchian). Default: ema-crossover

• $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}_optimize.py

3. The script must:
   • Load

     .env

     and fetch data via OpenAlgo

     client.history()

   • Define sensible parameter ranges for the chosen strategy
   • Use loop-based optimization (not broadcasting) to collect multiple metrics per combo
   • Track: total_return, sharpe_ratio, max_drawdown, trade_count for each combination
   • Use

     tqdm

     for progress bars
   • Find best parameters by total return AND by minimum drawdown
   • Print top 10 results for both criteria
   • Generate Plotly heatmap of total return across parameter grid
   • Generate Plotly heatmap of max drawdown across parameter grid
   • Save results to CSV
4. Never use icons/emojis in code or logger output
5. For futures symbols, use lot-size-aware sizing

Default Parameter Ranges

Example Usage

/optimize ema-crossover RELIANCE NSE D

/optimize rsi SBIN