{"slug": "ai-portfolio-analyzer", "title": "AI Portfolio Analyzer", "summary": "A developer built AI Portfolio Analyzer, a web application that combines data engineering, machine learning, and full-stack development to help investors analyze portfolios, forecast prices, assess risk, and estimate capital gains taxes. The app supports NSE and NYSE stocks with real-time WebSocket updates, uses a multi-model forecasting pipeline for 30-day price predictions, and leverages Llama 3 for natural language portfolio insights.", "body_md": "Over the last few months, I wanted to build a project that combined everything I enjoy working on—data engineering, machine learning, backend APIs, and modern frontend development.\n\nThe result is **AI Portfolio Analyzer**, a web application that helps investors analyze portfolios, forecast prices using machine learning, understand portfolio risk, and estimate capital gains taxes.\n\n🔗 **Live Demo:** [https://portfolio-analyzer-sigma-amber.vercel.app/](https://portfolio-analyzer-sigma-amber.vercel.app/)\n\n💻 **GitHub:** [https://github.com/abhinavsharma11pix/portfolio-analyzer](https://github.com/abhinavsharma11pix/portfolio-analyzer)\n\nMost portfolio tracking applications focus on showing holdings and returns. I wanted to build something that could answer questions like:\n\nThis project became an opportunity to combine quantitative finance, machine learning, and full-stack engineering into a single application.\n\nThe application supports both NSE and NYSE stocks with real-time market updates through WebSockets.\n\nThis enables live portfolio valuation without constantly refreshing the page.\n\nOne of the most interesting parts of the project was building the forecasting pipeline.\n\nInstead of relying on a single model, I combined multiple approaches:\n\nEach model captures different characteristics of market behavior.\n\nThe application generates a 30-day forecast and presents it alongside historical prices for comparison.\n\nThe application uses **Llama 3** to generate portfolio insights.\n\nRather than simply explaining metrics, it analyzes portfolio composition and produces natural language summaries that are easier for investors to understand.\n\nExamples include:\n\nThe platform calculates several commonly used portfolio metrics including:\n\nThese metrics provide additional context beyond simple profit and loss.\n\nAnother feature I wanted to include was tax estimation.\n\nThe application supports:\n\nThis allows investors to understand the tax implications of selling holdings.\n\nEvery project comes with tradeoffs.\n\nSome of the interesting challenges included:\n\nEach iteration improved both the user experience and the architecture.\n\nBuilding this project strengthened my understanding of:\n\nMore importantly, it reminded me how much you learn by building end-to-end products rather than isolated models.\n\nSome ideas I'm currently exploring include:\n\nIf you have suggestions or feedback, I'd love to hear them.\n\n⭐ GitHub:\n\n[https://github.com/abhinavsharma11pix/portfolio-analyzer](https://github.com/abhinavsharma11pix/portfolio-analyzer)\n\n🚀 Live Demo:\n\n[https://portfolio-analyzer-sigma-amber.vercel.app/](https://portfolio-analyzer-sigma-amber.vercel.app/)", "url": "https://wpnews.pro/news/ai-portfolio-analyzer", "canonical_source": "https://dev.to/abhinavsharma11pix/ai-portfolio-analyzer-6il", "published_at": "2026-07-12 18:42:06+00:00", "updated_at": "2026-07-12 19:15:34.816793+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "developer-tools", "ai-products"], "entities": ["Abhinav Sharma", "Llama 3", "NSE", "NYSE", "GitHub", "Vercel"], "alternates": {"html": "https://wpnews.pro/news/ai-portfolio-analyzer", "markdown": "https://wpnews.pro/news/ai-portfolio-analyzer.md", "text": "https://wpnews.pro/news/ai-portfolio-analyzer.txt", "jsonld": "https://wpnews.pro/news/ai-portfolio-analyzer.jsonld"}}