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strategy-compare

Name: Strategy Compare
Author: marketcalls

// Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.

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stars:148

forks:38

updated:March 5, 2026 at 15:28

SKILL.md

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name	strategy-compare
description	Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.
argument-hint	[symbol] [strategies...]
allowed-tools	Read, Write, Edit, Bash, Glob, Grep

Create a strategy comparison script.

Arguments

Parse $ARGUMENTS as: symbol followed by strategy names

$0 = symbol (e.g., SBIN, RELIANCE, NIFTY)
Remaining args = strategies to compare (e.g., ema-crossover rsi donchian)

If only a symbol is given with no strategies, compare: ema-crossover, rsi, donchian, supertrend. If "long-vs-short" is one of the strategies, compare longonly vs shortonly vs both for the first real strategy.

Instructions

Read the vectorbt-expert skill rules for reference patterns
Create backtesting/strategy_comparison/ directory if it doesn't exist (on-demand)
Create a .py file in backtesting/strategy_comparison/ named {symbol}_strategy_comparison.py
The script must:
- Fetch data once via OpenAlgo
- If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True). See vectorbt-expert rules/duckdb-data.md.
- If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback.
- Use TA-Lib for ALL indicators (never VectorBT built-in)
- Use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.)
- Clean signals with ta.exrem() (always .fillna(False) before exrem)
- Run each strategy on the same data
- Indian delivery fees: fees=0.00111, fixed_fees=20 for delivery equity
- Collect key metrics from each into a side-by-side DataFrame
- Include NIFTY benchmark in the comparison table (via OpenAlgo NSE_INDEX)
- Print Strategy vs Benchmark comparison table: Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor
- Explain results in plain language - which strategy performed best and why
- Plot overlaid equity curves for all strategies using Plotly (template="plotly_dark")
- Save comparison to CSV
Never use icons/emojis in code or logger output

Example Usage

/strategy-compare RELIANCE ema-crossover rsi donchian /strategy-compare SBIN long-vs-short ema-crossover

related-skills.json

same repository

backtest.md

from "marketcalls/vectorbt-backtesting-skills"

Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.

2026-03-05148

optimize.md

from "marketcalls/vectorbt-backtesting-skills"

Optimize strategy parameters using VectorBT. Tests parameter combinations and generates heatmaps.

2026-03-05148

quick-stats.md

from "marketcalls/vectorbt-backtesting-skills"

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.

2026-03-05148

setup.md

from "marketcalls/vectorbt-backtesting-skills"

Set up the Python backtesting environment. Detects OS, creates virtual environment, installs dependencies (openalgo, ta-lib, vectorbt, plotly), and creates the backtesting folder structure.

2026-03-05148

vectorbt-expert.md

from "marketcalls/vectorbt-backtesting-skills"

VectorBT backtesting expert. Use when user asks to backtest strategies, create entry/exit signals, analyze portfolio performance, optimize parameters, fetch historical data, use VectorBT/vectorbt, compare strategies, position sizing, equity curves, drawdown charts, or trade analysis. Also triggers for openalgo.ta helpers (exrem, crossover, crossunder, flip, donchian, supertrend).

2026-03-05148

package.json

"author": "marketcalls"

"repository": "marketcalls/vectorbt-backtesting-skills"

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name	strategy-compare
description	Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.
argument-hint	[symbol] [strategies...]
allowed-tools	Read, Write, Edit, Bash, Glob, Grep

Create a strategy comparison script.

Arguments

Parse $ARGUMENTS as: symbol followed by strategy names

$0 = symbol (e.g., SBIN, RELIANCE, NIFTY)
Remaining args = strategies to compare (e.g., ema-crossover rsi donchian)

Instructions

Read the vectorbt-expert skill rules for reference patterns
Create backtesting/strategy_comparison/ directory if it doesn't exist (on-demand)
Create a .py file in backtesting/strategy_comparison/ named {symbol}_strategy_comparison.py
The script must:
- Fetch data once via OpenAlgo
- If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True). See vectorbt-expert rules/duckdb-data.md.
- If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback.
- Use TA-Lib for ALL indicators (never VectorBT built-in)
- Use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.)
- Clean signals with ta.exrem() (always .fillna(False) before exrem)
- Run each strategy on the same data
- Indian delivery fees: fees=0.00111, fixed_fees=20 for delivery equity
- Collect key metrics from each into a side-by-side DataFrame
- Include NIFTY benchmark in the comparison table (via OpenAlgo NSE_INDEX)
- Print Strategy vs Benchmark comparison table: Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor
- Explain results in plain language - which strategy performed best and why
- Plot overlaid equity curves for all strategies using Plotly (template="plotly_dark")
- Save comparison to CSV
Never use icons/emojis in code or logger output

Example Usage

/strategy-compare RELIANCE ema-crossover rsi donchian /strategy-compare SBIN long-vs-short ema-crossover

strategy-compare

Arguments

Instructions

Example Usage

More from this repository

More from this repository

Arguments

Instructions

Example Usage