marketcalls/vectorbt-backtesting-skills▌

Generate complete VectorBT backtesting scripts with data fetch, signals, stats, and plots. \n \n Supports 10+ pre-built strategies (EMA crossover, RSI, Donchian, Supertrend, MACD, SDA2, momentum, and more) with template-based script generation \n Fetches data from OpenAlgo API or loads directly from DuckDB; auto-detects Historify vs custom formats \n Uses TA-Lib for standard indicators and OpenAlgo ta for specialty indicators (Supertrend, Donchian, Ichimoku); includes signal deduplication via ex

Side-by-side backtesting comparison of multiple trading strategies on the same symbol. \n \n Compares user-specified strategies (or defaults to ema-crossover, rsi, donchian, supertrend) against the same historical data and NIFTY benchmark \n Supports \"long-vs-short\" mode to test longonly, shortonly, and both directions for a given strategy \n Uses TA-Lib for standard indicators and OpenAlgo ta for specialty indicators like Supertrend and Donchian; cleans signals with exrem() to avoid consecuti

Complete Python backtesting environment setup with OS detection, virtual environment, dependencies, and configuration. \n \n Detects operating system (macOS, Linux, Windows) and installs TA-Lib system dependencies accordingly \n Creates isolated Python virtual environment with pip upgrade and installs 15+ packages including vectorbt, openalgo, plotly, ta-lib, duckdb, and quantstats \n Prompts user to select market data source (Indian Markets via OpenAlgo or DuckDB, US Markets via yfinance, or Cr

Inline backtest runner for Indian equities with EMA crossover strategy and benchmark comparison. \n \n Fetches OHLC data from OpenAlgo (with yfinance fallback) and runs a TA-Lib EMA 10/20 crossover strategy without file creation \n Applies Indian delivery fees (0.111% + Rs 20 per order) and automatically fetches NIFTY benchmark for alpha calculation \n Prints compact results summary including total return, Sharpe/Sortino ratios, max drawdown, win rate, and profit factor with plain-language metri

Backtesting strategy parameter optimization with VectorBT, generating performance heatmaps and benchmark comparisons. \n \n Accepts strategy name, symbol, exchange, and interval; creates optimization script in backtesting/{strategy}/ directory \n Loads market data from OpenAlgo via .env configuration or directly from DuckDB; uses TA-Lib for all indicators with OpenAlgo ta for specialty indicators like Supertrend and Donchian \n Tests parameter combinations across sensible ranges (e.g., EMA 5-50

$23