Transform Your Financial Future with SERA: The Ultimate Gamified Stock Trading Platform for Young Adults (16-25). Experience the Thrill of Real-Time Market Simulations & Handling wallet credits. Empower Yourself with Comprehensive Educational Content, and Stay Engaged with Interactive Features. SERA is Designed to Help You Learn Investing, Develop Smart Money Management Skills, and Build a Robust Financial Foundation. Dive into Realistic Market Scenarios, Participate in Exciting Challenges, and Unlock Your Potential with SERA – Where Learning and Investing Come to Life.
- Website Flow
- Problem Statement
- USPs
- Objective
- Solution
- Tech Stack
- Implementation
- Features
- Challenges Faced
- Contributors
- Project Structure
Task: Gamified stock trading platform designed for young adults (ages 16-25) to learn about investing, manage their money effectively, and build a strong financial foundation. It combines real-time market scenarios, educational content, and engaging features.
- User Onboarding: Simplify registration and profile setup.
- Educational Content: Create interactive lessons and quizzes on investing.
- Real-Time Simulations: Integrate live market data and practice trading scenarios.
- Gamification: Add points, badges, and challenges to enhance engagement.
- Security and Analytics: Ensure data protection and provide performance tracking.
- Advanced Blockchain Security and Transparency:
- Immutable Ledger: Blockchain ensures that every transaction is recorded in an immutable ledger, preventing tampering and enhancing trustworthiness.
- Decentralized Verification: By decentralizing transaction verification, the platform offers unparalleled transparency and security, allowing users to verify and audit all trading activities.
- Real-Time Trading and Market Data:
- Live Stock Trading: Users can engage in real-time trading with up-to-the-minute market data, replicating the experience of live financial markets.
- Instantaneous Feedback: Immediate updates and feedback on trades help users understand market reactions and adjust strategies dynamically.
- Comprehensive Educational Content:
- Structured Learning Paths: The platform offers a range of educational modules tailored to different skill levels, from basic investing principles to advanced trading strategies.
- Interactive Simulations: Realistic trading simulations allow users to practice and apply concepts in a controlled environment, bridging theoretical knowledge with practical experience.
- Machine Learning-Driven Insights and Predictions:
- Stock Prediction Models: Advanced ML algorithms analyze historical data and market trends to provide predictive insights, helping users make informed trading decisions.
- Personalized Recommendations: ML models tailor trading recommendations and strategies based on individual user behavior, preferences, and performance history.
- Trend Analysis: Continuous analysis of market trends and user data helps refine trading strategies and improve decision-making over time.
- Actionable Performance Insights:
- Detailed Analytics: Users receive comprehensive reports and analytics on their trading performance, highlighting strengths, weaknesses, and areas for improvement.
- Skill Enhancement Tools: Actionable insights from performance data help users identify skill gaps and optimize their trading strategies for better results.
- Expert Guidance and Learning Resources:
- Exclusive Video Sessions: Access to paid content featuring expert analysts and market strategists who offer in-depth analysis, personalized advice, and advanced trading techniques.
- Interactive Q&A: Opportunities for users to engage with experts through live Q&A sessions, webinars, or personalized coaching, providing targeted learning and support.
- Engaging Gamification Features:
- Motivational Mechanics: Gamified elements such as points, badges, and leaderboards drive engagement and foster a competitive yet educational environment.
- Dynamic Challenges: Regularly updated challenges and competitions encourage users to test their skills, apply new strategies, and stay motivated.
- Enhanced User Engagement and Retention:
- Customizable Alerts: Users can set personalized alerts and notifications based on market conditions, trading performance, or educational milestones.
- Progress Tracking: Visual progress tracking and achievements provide users with a clear view of their learning journey and trading success.
- Scalable and Adaptable Technology:
- Cloud Infrastructure: Utilizes scalable cloud services to handle large volumes of data and ensure reliable performance, even during peak trading hours.
- Continuous Improvement: The platform is designed to adapt and integrate new technologies and features, ensuring it remains cutting-edge and responsive to user needs.
- Educate Young Adults: Provide a comprehensive platform for young adults (ages 16-25) to learn about stock trading and investment fundamentals through interactive content and real-time simulations.
- Facilitate Practical Experience: Offer users the opportunity to trade real stocks in a live market environment, enabling them to gain hands-on experience and better understand market dynamics.
- Enhance Financial Literacy: Equip users with the knowledge and tools to manage their money effectively, make informed investment decisions, and build a strong financial foundation.
- Promote Continuous Improvement: Deliver actionable insights, performance reports, and expert guidance to help users identify areas for improvement and enhance their trading skills.
- Increase Engagement Through Gamification: Incorporate gamified elements such as points, badges, and challenges to make the learning process engaging and motivating, encouraging users to actively participate and track their progress.
- Secure and Transparent Trading:
- Utilizes blockchain technology to ensure all transactions are recorded securely and transparently, minimizing fraud and unauthorized tampering.
- Real-Time Market Access:
- Offers users the ability to trade real stocks with live market data, providing an authentic trading experience and immediate feedback.
- Educational Resources:
- Provides comprehensive educational content and interactive simulations to help users understand stock trading and investment strategies.
- Actionable Insights and Expert Guidance:
- Delivers performance reports, actionable insights, and access to expert video sessions to help users improve their trading skills and make informed decisions.
- Gamified Engagement:
- Incorporates gamified elements such as points, badges, and challenges to enhance user engagement, motivation, and learning experience.
- Frontend: HTML, CSS, JavaScript, React.js
- Framework: Bootstrap
- Backend: Express.js, Node.js, Flask, Python
- Blockchain: Polygon
- Machine Learning: scikit-learn, numpy, pandas
- Decentralized Server Used: IPFS
Prerequisites:
- Node.js
- JavaScript
- Python (Jupyter Notebook)
- Git
- React.js
- Polygon
- IPFS
- Install Truffle:
npm install -g truffle - Verify Installation:
truffle version
- Download IPFS: Go to the IPFS installation page and download the appropriate version for your operating system.
Integrating Polygon (formerly Matic Network) into your website can provide several advantages, particularly if your platform involves blockchain features such as stock trading and financial transactions.
- Fast Transactions: High-speed processing with minimal latency for real-time trading.
- Low Fees: Reduced transaction costs compared to Ethereum’s mainnet.
- Enhanced Security: Secure and transparent transactions on an immutable ledger.
- Easy Integration: Compatible with Ethereum, using existing tools and smart contracts.
- Improved User Experience: Quick transaction confirmations and efficient data handling.
The primary machine learning model used is the Isolation Forest algorithm, which excels in anomaly detection. This section outlines the usage, training, and prediction processes for the machine learning components.
- Historical Transaction Data: Collect historical transaction data including features such as transaction amount, timestamp, location, merchant details, and user information.
- Labeling Data: For supervised algorithms, label the data to indicate whether each transaction is legitimate or fraudulent.
- Data Cleaning: Remove duplicates, handle missing values, and correct any inconsistencies in the data.
- Feature Engineering: Create new features or modify existing ones to improve the model's predictive power (e.g., transaction frequency, average transaction amount).
- Normalization: Scale the features to a standard range to ensure the model's performance is not biased by the scale of the input data.
- Isolation Forest: An unsupervised learning algorithm specifically designed for anomaly detection. Ideal for identifying fraudulent transactions by isolating anomalies from the normal transaction patterns.
- Live Market Data: Provides up-to-date information on stock prices, market trends, and trading volumes.
- Instant Trade Execution: Allows users to execute buy and sell orders quickly, reflecting real-time market conditions.
- Real-Time Alerts: Sends notifications about price changes, trade executions, and market events.
- Secure Transactions: Uses blockchain technology for secure and tamper-proof recording of all trading activities.
- Transparent Ledger: Provides an immutable and transparent transaction history that users can verify.
- Decentralized Control: Ensures greater security and reliability by decentralizing transaction validation.
- Interactive Modules: Offers lessons on investing basics, market analysis, and advanced trading strategies.
- Quizzes and Assessments: Includes quizzes to test knowledge and track learning progress.
- Progressive Learning Paths: Provides structured learning paths to guide users from beginner to advanced levels.
- Predictive Analytics: Uses machine learning algorithms to forecast stock trends and market movements.
- Personalized Recommendations: Tailors trading suggestions and strategies based on individual user behavior and performance.
- Trend Analysis: Continuously analyzes market trends to refine and improve user strategies.
- Points and Badges: Rewards users with points and badges for achieving milestones and completing educational activities.
- Leaderboards: Displays top performers to foster a competitive and engaging environment.
- Challenges and Competitions: Organizes regular challenges and trading competitions to motivate users and enhance engagement.
- Detailed Reports: Provides comprehensive reports on trading performance, including profit/loss analysis and transaction history.
- Skill Improvement Metrics: Tracks and displays metrics related to user skill development and trading efficiency.
- Customizable Dashboards: Allows users to customize their dashboards to monitor key performance indicators and personal metrics.
- Video Sessions: Offers access to paid video content featuring market experts and analysts.
- Live Webinars: Hosts live webinars and Q&A sessions with experts for real-time advice and insights.
- Personalized Coaching: Provides opportunities for one-on-one coaching and mentorship for tailored support.
- Intuitive Design: Features a clean and intuitive user interface for easy navigation and interaction.
- Responsive Layout: Ensures a seamless experience across desktop and mobile devices.
- Interactive Elements: Includes interactive charts, graphs, and tools for an engaging user experience.
- Forums and Chatrooms: Facilitates discussions and knowledge sharing among users.
- Social Sharing: Allows users to share achievements and trading insights on social media.
- Mentorship Programs: Connects novice traders with experienced mentors for guidance and support.
- Authentication: Implements secure authentication methods such as OAuth or JWT for user verification.
- Encryption: Uses SSL/TLS encryption to protect data transmission and user privacy.
- Fraud Prevention: Integrates measures to detect and prevent fraudulent activities and unauthorized access.
- Financial Services: Integrates with decentralized finance (DeFi) applications for services like lending, borrowing, and staking.
- Liquidity Pools: Provides access to DeFi liquidity pools for enhanced financial services and opportunities.
Embed or link to the demo video showcasing the features and functionality of the platform.
- Data Security and Privacy: Ensuring that sensitive transaction data used for machine learning is kept secure and private while being processed. Implementing privacy-preserving machine learning techniques to comply with data protection regulations.
- Interoperability: Integrating machine learning models with blockchain infrastructure seamlessly. Ensuring that the outputs of machine learning models can be effectively utilized within the Web3 ecosystem.
- Blockchain Interoperability: Ensuring seamless interaction between the blockchain layer and the application layer.
- Performance and Scalability: Handling the potential performance bottlenecks of blockchain, such as transaction throughput and confirmation times. Implementing solutions to scale the blockchain network as the number of users and transactions increases.
- Repository Management: Managing repository access and permissions to ensure that team members have the necessary access while maintaining security. Handling issues related to repository cloning, pushing, and pulling due to account or authentication problems.
- Version Control: Ensuring that all team members are using consistent version control practices to avoid conflicts and merge issues. Resolving merge conflicts that arise from simultaneous development efforts.
- Collaboration: Coordinating among team members to ensure smooth collaboration and avoid issues like code overwriting or accidental deletions. Utilizing GitHub features like branches, pull requests, and issues effectively for team collaboration.
- Infrastructure Setup: Setting up and configuring the development and production environments, including servers, databases, and blockchain nodes. Ensuring that all components of the application are correctly configured and can communicate with each other.
- Deployment Challenges: Deploying the application on cloud platforms and ensuring that all services are up and running. Handling deployment issues such as server downtime, configuration errors, and dependency management.
- API Integration: Integrating third-party APIs and services into the application and handling any compatibility or configuration issues. Ensuring that the APIs are secure and perform well under load.
- Bug Fixing and Testing: Identifying and fixing bugs that arise during development and testing phases. Ensuring comprehensive testing of the application to detect and resolve issues early in the development process.
- Documentation and Knowledge Sharing: Maintaining up-to-date documentation to ensure that all team members are aware of the system architecture, configuration, and best practices. Facilitating knowledge sharing and troubleshooting among team members to quickly resolve technical issues.
- Anusha Arora: Made login page, transaction pages, data processing, README, PPT, and integration of backend with ML model.
- Aditi Mehta: Developed the entire front end and blockchain integration.
- Arshiya Garg: Created the ML model, training dataset, data preprocessing, and learned about IPFS. Also contributed to README.
- Vania Goel: Assisted with front end, integrated ML and blockchain using IPFS, integrated APIs, and deployed ML and blockchain in the backend.
/SERA
│
├── /frontend
│ ├── /public
│ │ ├── index.html
│ │ └── assets/ # Static assets (images, fonts, etc.)
│ ├── /src
│ │ ├── /components # React/Angular components
│ │ ├── /pages # Page components
│ │ ├── /hooks # Custom React hooks
│ │ ├── /context # Context API files
│ │ ├── /services # API service functions
│ │ ├── /utils # Utility functions
│ │ ├── /styles # Global styles and themes
│ │ ├── App.js # Main App component
│ │ └── index.js # Entry point for React/Angular
│ ├── package.json # Frontend dependencies and scripts
│ └── .env # Environment variables
│
├── /backend
│ ├── /controllers # Route handlers and business logic
│ ├── /models # Database models
│ ├── /routes # API routes
│ ├── /services # Business logic and external API interactions
│ ├── /middleware # Middleware functions (auth, validation)
│ ├── /config # Configuration files (DB, blockchain)
│ ├── /scripts # Scripts for setup, migrations, etc.
│ ├── /utils # Utility functions
│ ├── app.js # Express app setup
│ └── server.js # Server entry point
│ ├── package.json # Backend dependencies and scripts
│ └── .env # Environment variables
│
├── /blockchain
│ ├── /contracts # Smart contracts
│ ├── /migrations # Contract migrations
│ ├── /scripts # Deployment and interaction scripts
│ ├── truffle-config.js # Truffle configuration
│ └── hardhat.config.js # Hardhat configuration (if used)
│
├── /ml
│ ├── /models # Machine learning models and training scripts
│ ├── /notebooks # Jupyter notebooks for analysis
│ ├── /scripts # Scripts for data preprocessing, training, etc.
│ ├── requirements.txt # Python dependencies
│ └── config.json # Configuration for ML tasks
│
├── /docs # Documentation files
│ ├── API.md # API documentation
│ ├── USER_GUIDE.md # User guide and FAQs
│ └── ARCHITECTURE.md # System architecture and design decisions
│
├── /tests # Test cases
│ ├── /frontend # Frontend tests
│ ├── /backend # Backend tests
│ ├── /blockchain # Smart contract tests
│ └── /ml # ML model tests
│
├── .gitignore # Git ignore file
├── README.md # Project overview and setup instructions
└── docker-compose.yml # Docker Compose file (if using Docker)