# Crypto Backtest

> Crypto futures backtesting engine with built-in EMA, RSI, MACD, and Bollinger Band strategies. Fetches OHLCV data from any ccxt-supported exchange (Bybit, Binance, OKX, etc.), runs multi-strategy sweeps, calculates win rate / PnL / drawdown, and exports results to JSON. Use when backtesting trading strategies, comparing parameter combinations, evaluating crypto trading signals, or building a quantitative trading pipeline.

- Skill: `johnalbertini14-glitch/crypto-backtest` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add johnalbertini14-glitch/crypto-backtest`
- Raw SKILL.md: https://api.skillmd.com/api/skills/johnalbertini14-glitch/crypto-backtest/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: johnalbertini14-glitch (https://skillmd.com/u/johnalbertini14-glitch)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/johnalbertini14-glitch/crypto-backtest

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# Crypto Backtest Engine

Fast, scriptable backtesting for crypto futures strategies. Fetches data via ccxt, runs strategies, reports metrics.

## Quick Start

```bash
pip install ccxt numpy
python scripts/backtest_engine.py --symbol ETH/USDT:USDT --strategy ema --fast 12 --slow 26
```

## Features

- **Multi-exchange**: Any ccxt-supported exchange (Bybit, Binance, OKX, Bitget...)
- **Built-in strategies**: EMA crossover, RSI, MACD, Bollinger Bands
- **Parameter sweep**: Test all combinations automatically
- **Risk simulation**: Configurable leverage, position size, SL/TP, fees
- **JSON export**: Machine-readable results for pipeline integration
- **Custom strategies**: Simple plug-in interface

## Usage

### Single Strategy
```bash
python scripts/backtest_engine.py \
  --symbol SOL/USDT:USDT \
  --strategy rsi \
  --period 14 --oversold 30 --overbought 70 \
  --capital 1000 --leverage 5
```

### Parameter Sweep
```bash
python scripts/sweep.py \
  --symbol ETH/USDT:USDT \
  --strategies ema,rsi,macd,bbands \
  --capital 1000 --leverage 5 \
  --output results.json
```

### Custom Strategy
See `references/custom_strategy.md` for the plug-in interface.

## Output Metrics

Each backtest reports:
- Total trades, win rate, profit factor
- Total PnL (absolute + percentage)
- Max drawdown
- Best/worst trade
- Final balance

## Files

- `scripts/backtest_engine.py` — Core engine with EMA, RSI, MACD, Bollinger Bands
- `scripts/sweep.py` — Multi-strategy parameter sweep runner
- `references/custom_strategy.md` — Guide for adding custom strategies
- `references/strategy_notes.md` — Notes on each built-in strategy's edge cases