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Data Analysis · Business / AGENT SKILL
quick-stats
0
Fetch symbol data and report backtest statistics for a default EMA crossover strategy.
Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strategy. No file creation needed - runs inline in a notebook cell or prints to console.
Understand the trade-offs.
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The full skill.
Original instructions from the publisher’s 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 OpenAlgo ta** for EMA 10/20 crossover by default (never VectorBT built-in); only use TA-Lib if the user explicitly says "talib"/"TA-Lib" 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: ``` Symbol: SBIN | Exchange: NSE | Interval: D Strategy: EMA 10/20 Crossover Period: 2023-01-01 to 2026-02-27 Fees: Delivery Equity (0.111% + Rs 20/order) ------------------------------------------- Total Return: 45.23% Sharpe Ratio: 1.45 Sortino Ratio: 2.01 Max Drawdown: -12.34% Win Rate: 42.5% Profit Factor: 1.67 Total Trades: 28 ------------------------------------------- Benchmark (NIFTY): 32.10% Alpha: +13.13% ``` 7. **Explain** key metrics in plain language for normal traders 8. Show equity curve plot using Plotly (`template="plotly_dark"`) ## Example Usage `/quick-stats RELIANCE` `/quick-stats HDFCBANK NSE 1h`