TradeCompass: Stock Trading and Journaling App
TradeCompass is a comprehensive stock trading and journaling application that provides real-time data, customizable trading strategies, AI-driven insights, and a range of advanced features to help traders make informed decisions.
Goals
1. Track account balances from brokerage accounts.
2. Log and analyze active trades and trading history.
3. Manage stock profiles and watchlists with ratings and favorites.
4. Provide customizable trading strategies with buy/sell points.
5. Integrate AI for analyzing trades and scanning the internet for stock news.
Technologies
- Next.js
- PostgreSQL
- Prisma ORM
- Auth0 for authentication
- TradingView open-source library for charting
- MUI (Material-UI) for frontend UI components
Features
1. Real-time market data integration.
2. Social trading features like strategy sharing.
3. AI-driven insights for trading suggestions and portfolio analysis.
4. Advanced charting with candlesticks, line, bar, and pie charts.
5. Dividend and income tracking.
6. Enhanced security with two-factor authentication.
7. Exportable reports for tax and analytics.
Trading Strategies
Basic Dip-Buying Strategy
Set thresholds for dips and recoveries to automate buy/sell actions based on percentage drops.
Dollar-Cost Averaging with Dips
Incremental purchases at deeper dips to average entry prices.
RSI-Based Dip Buying
Use RSI to identify oversold conditions for strategic entries and exits.
Moving Average Crossover with Dips
Combine moving average crossovers with dip thresholds for confirmations.
Volume Spike Dip Buying
Leverage unusually high trading volumes during dips to identify potential reversals.
Timeline
Approximately 5.3 months with a 25% buffer for unforeseen delays.
UML Database Diagram
TradeCompass Development Plan
A comprehensive development plan for the TradeCompass app, covering planning, backend and frontend development, AI integration, testing, and deployment.
Total Duration: 5.3 months (21.25 weeks), including a 25% buffer for unforeseen delays.
Planning and Setup (Weeks 1–3)
Deliverables:
Finalize project requirements and scope.
Set up the development environment.
Define Prisma schema and run migrations.
Key Tasks:
Create folder structure for the project.
Configure environment variables.
Implement CI/CD pipelines for deployment.
Database and Backend API Development (Weeks 4–8)
Deliverables:
Develop Prisma models for all database tables.
Build API endpoints for CRUD operations.
Implement backend logic for stock data retrieval and portfolio management.
Key Tasks:
Test API endpoints with Postman.
Optimize database queries for performance.
Frontend Development (Weeks 9–14)
Deliverables:
Design and implement responsive UI components using MUI.
Integrate backend APIs with frontend components.
Implement advanced charting features using TradingView.
Key Tasks:
Customize MUI theme.
Ensure mobile responsiveness for all pages.
AI and Machine Learning Integration (Weeks 15–18)
Deliverables:
Integrate OpenAI for chatbot functionality and sentiment analysis.
Implement AI-driven trading suggestions and backtesting.
Key Tasks:
Configure data pipelines for real-time news.
Train AI models for personalized insights.
Testing and Quality Assurance (Weeks 19–20)
Deliverables:
Perform end-to-end testing.
Ensure security compliance and load testing.
Fix bugs and optimize performance.
Key Tasks:
Use Jest, Cypress, or Playwright for automated testing.
Gather user feedback from beta testing.
Deployment and Enablement (Weeks 21–22)
Deliverables:
Deploy the app to production using Vercel.
Provide user documentation and training.
Key Tasks:
Monitor app performance post-deployment.
Create a feedback loop for improvements.