quick-stats

Installation
Summary

Inline backtest runner for Indian equities with EMA crossover strategy and benchmark comparison.

  • Fetches OHLC data from OpenAlgo (with yfinance fallback) and runs a TA-Lib EMA 10/20 crossover strategy without file creation
  • Applies Indian delivery fees (0.111% + Rs 20 per order) and automatically fetches NIFTY benchmark for alpha calculation
  • Prints compact results summary including total return, Sharpe/Sortino ratios, max drawdown, win rate, and profit factor with plain-language metric explanations
  • Generates an interactive Plotly equity curve chart and accepts symbol, exchange, and interval as command arguments with sensible defaults (SBIN, NSE, daily)
SKILL.md

Generate a quick inline backtest and print stats. Do NOT create a file - output code directly for the user to run or execute in a notebook.

Arguments

  • $0 = symbol (e.g., SBIN, RELIANCE). Default: SBIN
  • $1 = exchange. Default: NSE
  • $2 = interval. Default: D

Instructions

Generate a single code block the user can paste into a Jupyter cell or run as a script. The code must:

  1. Fetch data from OpenAlgo (or DuckDB if user provides a DB path, or yfinance as fallback)
  2. Use TA-Lib for EMA 10/20 crossover (never VectorBT built-in)
  3. Clean signals with ta.exrem() (always .fillna(False) before exrem)
  4. Use Indian delivery fees: fees=0.00111, fixed_fees=20
  5. Fetch NIFTY benchmark via OpenAlgo (symbol="NIFTY", exchange="NSE_INDEX")
  6. Print a compact results summary:
Related skills
Installs
832
GitHub Stars
132
First Seen
Feb 25, 2026