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marketicbuilder/crypto-backtest-engine-v3

Analysis updated 2026-05-18

1PythonAudience · developerComplexity · 3/5Setup · moderate

TLDR

A crypto trading strategy backtester that scores buy/sell signals using 8 combined indicators including live Bitget market data, then measures historical performance with 17 risk metrics.

Mindmap

mindmap
  root((BitEdge))
    Scoring System
      8 signals
      0-100 score
      Buy sell hold
    Signals
      RSI MACD EMA
      Bitget L/S ratio
      Fear and Greed
    Risk Management
      Fees and slippage
      Leverage up to 10x
      Stop-loss trailing
    Output
      17 metrics
      Sharpe Sortino
      Drawdown streaks
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Code map

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What do people build with it?

USE CASE 1

Test whether a multi-indicator crypto trading strategy would have been profitable over the past several years before trading real money.

USE CASE 2

Compare Sharpe ratio, max drawdown, and win rate across different strategy parameter combinations using historical Bitget data.

USE CASE 3

Add live Bitget long/short ratio and funding rate signals to a technical analysis strategy to capture crowd sentiment.

What is it built with?

PythonFastAPIBitget API

How does it compare?

marketicbuilder/crypto-backtest-engine-v3a-bissell/unleash-liteabhiinnovates/whatsapp-hr-assistant
Stars111
LanguagePythonPythonPython
Setup difficultymoderatehardhard
Complexity3/54/53/5
Audiencedeveloperresearcherdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires a Bitget account or public API access, setup instructions are minimal since this is a hackathon submission.

No license specified in the README.

In plain English

BitEdge is a cryptocurrency trading strategy backtester built as a hackathon submission for Bitget's AI Builder competition. It lets traders test whether a trading strategy would have made money historically before risking real funds, using price data pulled directly from the Bitget exchange for free. The core of the engine is a scoring system that combines eight technical signals into a single number between 0 and 100 on every price bar. Scores above 60 produce a buy signal, below 40 produce a sell, and anything in between means hold. The signals include common technical indicators like RSI and MACD plus live data from Bitget's futures market, such as the ratio of traders who are currently long versus short and the funding rate that traders pay to hold positions. These market microstructure signals aim to capture crowd sentiment that price indicators alone cannot see. The risk management layer supports configurable fees and slippage to simulate real trading costs, leverage up to 10x, stop-loss and take-profit orders, trailing stops, and position sizing based on a fixed percentage of account equity. Backtest results include 17 performance metrics including Sharpe ratio, maximum drawdown, win rate, and streak analysis. Fetching historical data is handled by a paginating client that downloads price data in batches of 1,000 bars and caches everything as compressed files on disk. Multi-year backtests run quickly after the first download. There is a web frontend at a live demo URL and a REST API with documentation. The README is a hackathon submission document rather than a standard open-source guide, so setup instructions are minimal. No license is specified in the README.

Copy-paste prompts

Prompt 1
How do I run a backtest on BTC/USDT using the BitEdge engine and what parameters can I adjust for the 8-signal scoring system?
Prompt 2
How does BitEdge handle Bitget API rate limits when fetching multi-year historical OHLCV data?
Prompt 3
What risk management options does BitEdge support and how do I configure stop-loss and trailing stop settings?

Frequently asked questions

What is crypto-backtest-engine-v3?

A crypto trading strategy backtester that scores buy/sell signals using 8 combined indicators including live Bitget market data, then measures historical performance with 17 risk metrics.

What language is crypto-backtest-engine-v3 written in?

Mainly Python. The stack also includes Python, FastAPI, Bitget API.

What license does crypto-backtest-engine-v3 use?

No license specified in the README.

How hard is crypto-backtest-engine-v3 to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is crypto-backtest-engine-v3 for?

Mainly developer.

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