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Cloud-Based Algorithmic Trading Strategies for High-Performance Portfolios

A cloud-based portfolio recommendation app implementing dynamic trading strategies using AI/ML and rule-based approaches to optimize portfolio performance and manage risks effectively.

GitHub

Cloud-Based Algorithmic Trading Strategies for High-Performance Portfolios

September 2023 - March 2024

A comprehensive cloud-based portfolio recommendation application that leverages modern web technologies and machine learning to provide intelligent trading strategies for high-performance portfolios.

Key Achievements

  • Dynamic User Interface: Implemented responsive UI in JavaScript using React for interactive and scalable components
  • Collaborative Development: Worked closely with UX/UI designers to translate design mockups into functional React components
  • Data Integration: Integrated Python for importing, exploring, and transforming stock market data
  • Strategic Implementation: Applied diverse strategies including AI/ML and rule-based approaches to optimize portfolio performance and manage risks
  • Database Architecture: Built a comprehensive framework for storing stock market data, processed data, and trading strategy results
  • Cloud Computing: Demonstrated expertise in database management, cloud computing, and C# development

Technical Stack

  • Frontend: JavaScript, React.js
  • Backend: Python, C#, ASP.Net
  • Cloud: AWS
  • Database: MongoDB
  • AI/ML: Machine Learning algorithms for portfolio optimization
  • DevOps: CI/CD pipeline, Git & GitHub

Impact

This project showcases the integration of modern web development with financial technology, demonstrating proficiency in full-stack development, cloud computing, and machine learning applications in the financial sector.