Vágner, Anikó SzilviaMatinya, Adaup Tafara2026-02-122026-02-122025-11-19https://hdl.handle.net/2437/404344This thesis comprises of a web application developed using Typescript and Next.js. It designed to provide an accessible alternative to expensive enterprise grade tools. The platform is built on a three tier architecture with MongoDB being employed for data persistence and Better Auth being responsible for secure authentication and session management. The web application delivers live market data through integration with Finnhub API and TradingView widgets while enabling users to create personalized watchlists and receive automated price alerts through email. Although the original scope included AI-powered algorithmic trading features this implementation successfully deliver core functionality such as user authentication, real data visualization, watchlist management and working email notifications. The project demonstrates that by leveraging modern open source technologies we can lower the barrier for retail investors to access professional grade tools.50enwebappstock marketmongodbDevelopment of an AI-Powered Algorithmic Trading Platform for Personal Investment StrategiesInformatics::Computer ScienceHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.