yashvardhancse/quantnova

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.