🤑 A free, fast, in-browser stock portfolio tracker

Web App for Stock Quotes & Building a Portfolio Using Python & Django

Graph stocks on any platform 💹

TradeIt iOS SDK to integrate trading and portfolio management.

Learning Go and Hexagonal Architecture through Stock Portfolio Management

Web-Based Stock Portfolio built with MERN (MongoDB, Express.js, React, Node.js) Stack, Redux, Sass, Recharts, IEX Cloud, and deployed with Docker

Finance portfolio to track and manage all your financial assets: stock transactions, crypto transactions, and tax calculation

Grade: 82%. My COMP3000 final year university project that allows you to manage nearly every facet of your finances with an open-source web, mobile, and desktop application, along with a self-hosted GraphQL API.

📈 Stock screener and portfolio analyzer, providing key insights on financial reports, news articles and more!

个人用来更新股票仓位和估值的工具

Symfony application to keep track of your stock portfolio 📈

Python module for tracking stock portfolio performance based on price changes and dividend payouts only, rather than value of deposits.

A stock portfolio web app demo

Stockify is a Stock Monitoring Spring Boot-based web application that allows users to manage their stock portfolios, upload stocks, receive folio summaries via email. It features JWT-based authentication with OTP verification during registration. Built with clean, scalable architecture and ready for real-world use!

A group project for CMPE285 at SJSU in Python

Smart Analyz is a web application for analyzing your all your investment into the stock market at one place.

a simple script to turn the transaction overview of an DWS account into an importable CSV for parqets activities

Utilizing the sophisticated Recurrent Neural Network (RNN) models, particularly Long Short-Term Memory (LSTM), in combination with FinBERT sentiment analysis, to improve the precision of stock portfolio analysis.

Using a google-spreadsheet to track stock prices

Application to manage portfolio and wish-lists and track recommendations