Full-Stack Stock Analysis Dashboard

A comprehensive, full-stack stock analysis application designed to provide users with real-time market data, detailed stock information, and powerful screening tools. The application features a robust Java Spring Boot backend for data aggregation and a dynamic, responsive Next.js frontend for a seamless user experience.

Live Demo:

• Frontend (Vercel): [https://stock-analysis-teal.vercel.app]

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Key Features

Frontend (Next.js & React)

• Live Dashboard: A real-time overview of the market, including major indices (S&P 500, Nasdaq Composite) with data that polls automatically for fresh updates.
• Dynamic Stock Detail Pages: A dedicated page for each stock featuring live price quotes and interactive historical price charts with multi-timeframe views (1D, 5D, 1M, 1Y).
• Interactive Stock Screener: A powerful client-side tool that allows users to filter thousands of US stocks by sector, market cap, and price to discover investment ideas.
• Instant Autocomplete Search: A global search bar that provides instant search results from a pre-fetched list of all US symbols for a fast and frictionless user experience.
• General & Company-Specific News: A dedicated news page for market-wide updates and context-specific news on individual stock pages.
• Secure OAuth Login: A clean, modern login page that supports secure sign-in with Google.(in development not live yet)

Backend (Spring Boot & Java)

• Multi-Source API Aggregation: A robust REST API that connects to multiple third-party financial data providers (Finnhub, Financial Modeling Prep) to serve a wide range of data.
• Performance-Optimized Caching: A server-side caching layer implemented with Spring Cache to dramatically reduce redundant API calls, improve response times, and stay within external API rate limits.
• JWT-Based Authentication: A secure authentication flow using Google OAuth2. After a successful login, the backend generates a custom JWT to manage user sessions for subsequent API requests.
• Database Integration: Connects to a PostgreSQL database (hosted on Supabase) with Spring Data JPA to manage user data, portfolios, and watchlists.
• Cloud Deployment: The backend is deployed and running live on Heroku, providing a stable and accessible API for the frontend application.

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Tech Stack

Category	Technology
Frontend	React, Next.js, TypeScript, SWR, Recharts, Tailwind CSS
Backend	Java, Spring Boot, Spring Security, Spring Data JPA, Maven
Database	PostgreSQL (hosted on Supabase)
Deployment	Vercel (Frontend), Heroku (Backend), Git/GitHub

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Getting Started

Prerequisites

• Java 21+
• Node.js & npm
• Maven
• Heroku CLI
• A PostgreSQL database (e.g., from Supabase)
• API keys from Finnhub and Financial Modeling Prep

Backend Setup (/server)

1. Clone the repository:

   git clone [https://github.com/Matrixk1ng/StockAnalysis.git]
   cd StockAnalysis/server

2. Configure Environment Variables: Create an application.properties file in src/main/resources/ and add your secret keys and database URL. Use the provided .properties file in the source code as a template, replacing the placeholder values.

3. Run the application:

   ./mvnw spring-boot:run

   The backend server will start on http://localhost:8080.

Frontend Setup (/client)

1. Navigate to the client directory:

   cd ../client 

2. Install dependencies:

   npm install

3. Configure Environment Variables: Create a .env.local file in the client directory and add the backend API URL:

   NEXT_PUBLIC_API_BASE_URL=http://localhost:8080/api
   

4. Run the application:

   npm run dev

   The frontend will be available at http://localhost:3000.