openclawby/clawby-quant — explained in plain English
Analysis updated 2026-05-18
Backtest a crypto perpetual futures strategy against historical data before risking real money.
Run automated paper trading with a virtual balance to observe how strategies perform.
Monitor 56 live market and on chain factors that feed into the trading strategies.
Route live trading orders across Binance, Bitget, and OKX from a single dashboard.
| openclawby/clawby-quant | aevella/sky-pc-mcp-companion | alicankiraz1/gemma-4-31b-mtp-vllm-server | |
|---|---|---|---|
| Stars | 26 | 26 | 26 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | moderate | hard |
| Complexity | 4/5 | 3/5 | 4/5 |
| Audience | developer | vibe coder | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Requires Python 3.10+, Node.js 20+, a Binance futures API key, and a Clawby API key for aggregated data factors.
Clawby Quant is a self-hosted trading system for automatically buying and selling crypto perpetual futures contracts, a type of margin traded crypto derivative traded against a US dollar equivalent stablecoin. Everything runs on your own machine, including your exchange API keys, which never get sent anywhere else. The project comes with a clear warning that it is meant for research and education, that derivatives trading carries real risk of loss, and that past backtest results do not guarantee future performance. The system ships with four ready made trading strategies, each of which can be cloned into multiple independent copies with their own settings, coins, and capital. Decisions are driven by a library of 56 data factors, ranging from official Binance exchange statistics like open interest and long/short ratios to aggregated data such as cross exchange liquidations, funding rates, and on chain metrics. Before risking real money, strategies can be tested against historical data using a backtesting engine that runs the exact same strategy code used in live trading, so there is no gap between what was tested and what actually runs, and it accounts for real trading costs like fees, slippage, and funding payments. Live trading orders can be routed to Binance, Bitget, or OKX, while market data and the factor library are based on Binance. The system strictly separates paper trading, which uses a virtual balance and is the default mode, from live trading, which requires typing a confirmation word before it activates. Several layers of risk controls are built in, including position sizing limits, a maximum margin multiplier cap, per coin exposure caps, a daily loss circuit breaker, and a quiet period around major market events. The dashboard is available in both English and Chinese and includes an overview of account performance, a trade journal, and factor and risk monitoring pages. Setup requires Python, Node.js, a Binance futures API key, and an API key from the related Clawby data service.
A self-hosted crypto perpetual futures trading bot with 56 market data factors, a replay-accurate backtester, and strict paper versus live trading separation.
Mainly Python. The stack also includes Python, FastAPI, React.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.