This project involves developing a comprehensive stock price prediction platform that leverages machine learning algorithms to analyze historical market data and predict future stock prices. The platform aims to provide investors and traders with insights to make informed decisions regarding stock trading.
User Interaction Overview
User Registration and Authentication
Sign Up: New users can create an account by providing their email and password. Once registered, they will receive a confirmation email to verify their account.
Login: Registered users can log in using their email and password. The API will support multi-factor authentication (MFA) for enhanced security.
Data Input and Prediction
Stock Data Input: Users can input historical stock data, including prices and volumes, for analysis.
Price Prediction: The API will provide predictions for future stock prices based on the input data
Historical Data Analysis
Trend Analysis: Users can access historical stock price trends and performance metrics.
Visualization Tools: The platform will include tools to visualize stock price trends overtime.
Feedback Mechanism:
User Feedback: Users can provide feedback on predictions to help improve the model's accuracy over time.
Objectives
Allow users to sign up, log in, and manage their accounts securely.
Enable users to input historical stock data for prediction.
Provide accurate stock price predictions based on machine learning algorithms.
Offer tools for historical data analysis and visualization.
Ensure robust security and user data protection.
Functional Requirements
User Management
Sign Up: Users can create an account using their email and password.
Login: Users can authenticate using their email and password.
Profile Management: Users can update their profile information.
Data Input and Prediction
Input Stock Data: Users can upload historical stock data in various formats (e.g., CSV).
Get Predictions: Users can request future stock price predictions based on the uploaded data.
Historical Data Analysis
View Trends: Users can access historical data trends for specific stocks.
Visualization Tools: Provide graphical representations of stock price trends and predictions.
Feedback Mechanism
Submit Feedback: Users can provide feedback on the accuracy of predictions to improve the model.
Non-Functional Requirements
Scalability: The API should handle a growing number of users and interactions.
Performance: The API should deliver fast response times for predictions and data retrieval.
Security: Implement authentication and authorization mechanisms to protect user data.
Reliability: The API should be highly available and handle failures gracefully.
Usability: The API should be easy to use, with clear documentation.
Use Cases
User Sign Up and Login: New users create an account, and existing users log in.
Input Stock Data: Users upload historical stock data for analysis.
Get Predictions: Users retrieve future stock price predictions.
View Historical Trends: Users analyze historical stock price trends and visualizations.
Submit Feedback: Users provide feedback on prediction accuracy.
User Stories
As a user, I want to sign up for an account so that I can access stock predictions.
As a user, I want to log in to my account so that I can manage my data and predictions.
As a user, I want to upload historical stock data to receive predictions.
As a user, I want to visualize historical trends to understand stock performance.
As a user, I want to provide feedback on predictions to help improve the system.
Technical Requirements
Programming Language: Choose an appropriate backend language (e.g., Python, Node.js).
Machine Learning Framework: Utilize an ML framework (e.g., TensorFlow, scikit-learn) for predictive modeling.
Database: Use a database to store user data and stock information (e.g., PostgreSQL, MongoDB).
Authentication: Implement JWT for secure user authentication.
API Documentation: Use Swagger or similar tools for API documentation.
API Endpoints
User Management
POST /signup: Register a new user.
POST /login: Authenticate a user.
GET /profile: Retrieve user profile details.
PUT /profile: Update user profile.
Data Input and Prediction
POST /stock/data: Upload historical stock data
GET /stock/predict: Retrieve stock price predictions based on uploaded data.
Historical Data Analysis
GET /stock/trends: Access historical price trends for specific stocks.
GET /stock/visualize: Retrieve graphical representations of stock trends.
Feedback Mechanism
POST /feedback: Submit feedback on prediction accuracy.
Security
Use HTTPS to encrypt data in transit.
Implement input validation and sanitization to prevent security vulnerabilities.
Use strong password hashing algorithms like bcrypt.
Performance
Implement caching strategies to improve response times for frequent requests.
Optimize machine learning models for efficient predictions.
Documentation
Provide comprehensive API documentation using tools like Swagger.
Create user guides and developer documentation to assist with integration and usage.
Glossary
API: Application Programming Interface.
ML: Machine Learning.
JWT: JSON Web Token.
Appendix
Include any relevant diagrams, data models, and additional references.
