# Jesse — Advanced Crypto Algo-Trading Framework

> A Python framework for developing and backtesting cryptocurrency trading strategies with a focus on simplicity, performance, and research-friendly design.

## Install

Save as a script file and run:

# Jesse — Advanced Crypto Algo-Trading Framework

## Quick Use
```bash
pip install jesse
jesse make-project my_bot
cd my_bot
jesse import-candles 'Binance Spot' 'BTC-USDT' '2024-01-01' --skip-confirmation
jesse backtest --start '2024-01-01' --finish '2024-06-01'
```

## Introduction
Jesse is a Python framework designed specifically for researching and developing cryptocurrency trading strategies. It emphasizes clean strategy syntax, fast backtesting, and seamless transition from research to live trading without rewriting code.

## What Jesse Does
- Backtests crypto trading strategies with accurate simulation of fees, slippage, and order types
- Imports and stores historical candle data from supported exchanges for offline analysis
- Provides a strategy API with built-in access to indicators, position sizing, and risk management
- Supports live and paper trading on Binance, Bybit, and other exchanges
- Offers genetic algorithm optimization for strategy parameter tuning

## Architecture Overview
Jesse stores candle data in PostgreSQL for fast retrieval during backtesting. Strategies are Python classes that define entry, exit, and position sizing logic using a declarative API. The backtesting engine simulates order fills with configurable execution models, and the same strategy code runs in live mode without modification.

## Self-Hosting & Configuration
- Install via pip with PostgreSQL as the required data backend
- Configure exchange API keys in a .env file for live trading
- Import historical candles using the built-in CLI data fetcher
- Define strategies in the strategies directory with indicator and signal logic
- Deploy with Docker for consistent production environments

## Key Features
- Clean strategy API that separates signal logic from execution details
- Fast vectorized backtesting with support for multiple timeframes per strategy
- Built-in genetic algorithm optimizer for finding robust parameter sets
- Accurate simulation of limit, market, and stop orders with partial fill support
- Research notebooks for exploratory analysis alongside strategy development

## Comparison with Similar Tools
- **Freqtrade** — More exchange support and larger community; Jesse offers a cleaner strategy API and research tools
- **Backtrader** — General-purpose; Jesse is crypto-native with exchange data import built in
- **CCXT** — A connectivity library; Jesse is a full framework that uses CCXT internally
- **QuantConnect** — Cloud-hosted and multi-asset; Jesse is local-first and crypto-focused

## FAQ
**Q: Does Jesse support spot and futures trading?**
A: Yes, it supports both spot and perpetual futures on compatible exchanges.

**Q: Why does Jesse require PostgreSQL?**
A: PostgreSQL provides fast indexed queries over large candle datasets needed for backtesting.

**Q: Can I run multiple strategies simultaneously?**
A: Yes, Jesse supports running multiple strategies across different trading pairs concurrently.

**Q: Is Jesse free?**
A: Yes, Jesse is open source under the MIT license.

## Sources
- https://github.com/jesse-ai/jesse
- https://jesse.trade

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Source: https://tokrepo.com/en/workflows/asset-d742be64
Author: Script Depot