Revise README for improved clarity and details

Updated README to enhance clarity and formatting, added new features and installation instructions.

Author: alexgaffen

README.md

@@ -1,18 +1,105 @@
-# Mock Market 📈
-
-**A Full-Stack Investment Simulation Platform featuring Hybrid AI Analysis.**
+# Mock Market 📈  
+**A Full-Stack Investment Simulation Platform featuring Hybrid AI Analysis**
 
 Mock Market is a trading simulation application that bridges the gap between traditional quantitative finance and modern Generative AI. It utilizes a high-performance **C++ engine** for technical indicator calculations and **Google Gemini** for qualitative market sentiment analysis, providing users with a comprehensive "Buy/Sell/Hold" decision for any given stock.
 
-![Project Status](https://img.shields.io/badge/Status-Active-success)
-![Tech Stack](https://img.shields.io/badge/Stack-React_Node_C++-blue)
-![AI](https://img.shields.io/badge/AI-Gemini_2.5_Flash-orange)
+![Project Status](https://img.shields.io/badge/Status-Active-success?style=for-the-badge)
+![Tech Stack](https://img.shields.io/badge/Stack-React_Node_C++-blue?style=for-the-badge)
+![AI](https://img.shields.io/badge/AI-Gemini_1.5_Flash-orange?style=for-the-badge)
 
 ## 🚀 Key Features
 
-* **Real-Time Market Data:** Fetches live pricing and historical data using Yahoo Finance and Finnhub APIs.
-* **Hybrid Intelligence Engine:**
-    * **Quantitative:** A dedicated C++ microservice calculates complex technical indicators (RSI, SMA, Bollinger Bands) in real-time.
-    * **Qualitative:** Google Gemini (GenAI) acts as a "Portfolio Manager," synthesizing news headlines with the C++ hard math to make human-like trading decisions.
-* **AI-Powered Insights:** Returns a clear textual analysis with a structured "Buy/Sell/Hold" signal and reasoning.
-* **Microservices Architecture:** Fully containerized using Docker and Docker Compose.
+- **Risk-Free Paper Trading**  
+  Users sign in securely via **Google** and instantly receive a **$100,000** virtual portfolio to practice trading strategies without financial risk.
+
+- **Real-Time Market Data**  
+  Fetches live pricing and historical data using **Yahoo Finance** and **Finnhub** APIs.
+
+- **Hybrid Intelligence Engine**  
+  - **Quantitative**: A dedicated C++ microservice calculates complex technical indicators (RSI, SMA, Bollinger Bands) in real-time.  
+  - **Qualitative**: Google Gemini (GenAI) acts as a "Portfolio Manager," synthesizing news headlines with the C++ hard math to make human-like trading decisions.
+
+- **AI-Powered Insights**  
+  Returns clear textual analysis with a structured **Buy / Sell / Hold** signal and reasoning.
+
+- **Microservices Architecture**  
+  Fully containerized using Docker and Docker Compose.
+
+## 🛠 Architecture Overview
+
+The application is split into three distinct services communicating via HTTP and TCP sockets:
+
+1. **Frontend (React)** – User interaction, portfolio management, secure authentication via **Firebase (Google Sign-In)**  
+2. **Backend (Node.js/Express)** – Orchestrator: fetches data, talks to C++ engine, feeds results + news into Gemini  
+3. **CPP-Algos (C++)** – High-performance TCP server for technical indicator calculations
+
+## 📂 Project Structure
+
+```text
+mock-market/
+├── backend/          # Node.js Express Server (API & Orchestration)
+├── cpp-algos/        # C++ Quantitative Analysis Engine
+├── frontend/         # React Client Application
+├── docker-compose.yml
+└── README.md
+⚙️ Prerequisites
+
+Node.js (v16 or higher)
+C++ Compiler (MinGW for Windows or GCC/Clang for Linux/macOS)
+Docker Desktop (recommended for easy deployment)
+API Keys:
+Finnhub API Key → finnhub.io
+Google Gemini API Key → Google AI Studio
+
+
+🔧 Installation & Setup
+Method 1: Docker (Recommended)
+Note: The current C++ code uses winsock2.h. For Docker (Linux containers), refactor socket code to standard BSD sockets (<sys/socket.h>, <netinet/in.h>).
+Bashgit clone https://github.com/yourusername/mock-market.git
+cd mock-market
+Create .env in the backend/ directory:
+envPORT=5000
+FINNHUB_API_KEY=your_finnhub_key_here
+GEMINI_API_KEY=your_gemini_key_here
+Build and run:
+Bashdocker-compose up --build
+
+Frontend → http://localhost:80
+Backend → http://localhost:5000
+
+Method 2: Manual Setup (Local Development – Windows)
+1. Start the C++ Engine
+Bashcd cpp-algos
+g++ src/main.cpp -o algo_service.exe -lws2_32 -static
+./algo_service.exe
+→ Listens on port 8080
+2. Start the Backend
+Bashcd backend
+npm install
+# Make sure .env exists with your keys
+node server.js
+→ Listens on port 5000
+3. Start the Frontend
+Bashcd frontend
+npm install
+npm start
+→ Opens at http://localhost:3000
+💡 How It Works – The "Signal" Endpoint
+When a user searches for a stock (e.g., AAPL):
+
+Data Fetch – Backend pulls last 60 days of price data (Yahoo Finance) + recent news (Finnhub)
+Quant Analysis – Price array sent to C++ engine (TCP port 8080)
+Math Calculation – C++ returns RSI, SMA, Bollinger Bands, etc.
+AI Synthesis – Backend sends technical string + news headlines to Google Gemini
+Decision – Gemini returns structured JSON:JSON{ "signal": "BUY", "confidence": 0.82, "reasoning": "Strong upward momentum..." }
+
+🚧 Cross-Platform Note
+
+Current cpp-algos/src/main.cpp uses <winsock2.h> → Windows-only
+To run inside Docker (Linux): replace with standard POSIX sockets
+Local Windows development works out-of-the-box
+
+🤝 Contributing
+Contributions are welcome! Feel free to open issues or submit Pull Requests.
+📄 License
+This project is licensed under the ISC License – see the LICENSE file for details.