Backtest a moving average crossover strategy against historical crypto price data.
Upload your own CSV or Excel price data and calculate indicators like RSI and Bollinger Bands.
Explore an interactive candlestick chart with signals and volume for a chosen symbol.
Pick up a beginner friendly issue and contribute to an early stage open source trading tool.
| yashvardhancse/quantnova | aredotna/api-examples | ceelog/openweread | |
|---|---|---|---|
| Stars | 15 | 15 | 15 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 2/5 | 2/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires running a separate frontend and Python backend, each with its own install step.
QuantNova is an open source, GUI based platform for backtesting trading strategies, meaning it lets you test a trading idea against historical price data to see how it would have performed, without risking real money. It targets people who want to develop and visualize trading strategies and collaborate with others on quantitative research, and it is explicitly scoped as an early stage project meant to be beginner friendly for contributors. The project has two parts: a React, Vite, and TypeScript frontend that shows a dark trading terminal style interface, and a Python FastAPI backend that handles data and calculations. You run them separately, starting the frontend with npm install and npm run dev, and the backend by creating a Python virtual environment, installing dependencies, and running uvicorn. Once both are running, you can open the frontend in a browser and confirm the backend is working through a health check page. Current features include fetching live price candle data from Binance for a chosen symbol, interval, and date range, with a bundled sample Bitcoin dataset as a fallback if the backend is not running. You can also upload your own price data as a CSV or Excel file. The platform calculates common technical indicators such as moving averages, RSI, and Bollinger Bands, and it can run a moving average crossover backtest, showing the resulting trade log, equity curve, and performance summary on an interactive candlestick chart. The README is explicit that this is an initial version: it does not yet include user accounts, a database, real broker connections, AI powered strategies, or live trading. It does include automated tests for both frontend and backend, continuous integration checks, and documentation aimed at first time open source contributors, including a list of beginner friendly issues. The project is released under the MIT license, so it can be used and modified freely.
An open source GUI platform for testing trading strategies against historical price data, with charts and technical indicators.
Mainly TypeScript. The stack also includes React, TypeScript, Vite.
MIT license, so the code can be freely copied, modified, and reused, including commercially.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
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