⚡ Python library for getting publically available Mutual Funds data in India
TEFAS API Client - Türkiye'deki yatırım ve emeklilik fonlarına erişim (Python, TypeScript, Go, .NET, Java)
Web UI for tracking CAMS + KFintech investments
Free daily historical dataset for Indian financial markets: NSE & BSE stocks (1991+), 50+ years of Gold & Silver bullion rates (24K/22K/18K), and all Indian Mutual Fund daily NAVs from inception (37,000+ schemes). Updated daily.
📈 Interactive Power BI dashboard analyzing mutual fund historical performance, category distributions, and expense ratios. Includes custom DAX-powered SIP & Lumpsum calculators.
Mutual Fund Data Analysis using AI is your financial sidekick 🚀💰. It dives into the world of mutual funds with the wisdom of AI, calculating trends, cracking jokes, and presenting insights in a language even your piggy bank would appreciate! 🐷✨
Mutual Fund Data Analysis using AI is your financial sidekick 🚀💰. It dives into the world of mutual funds with the wisdom of AI, calculating trends, cracking jokes, and presenting insights in a language even your piggy bank would appreciate! 🐷✨
🚀 MCP server that gives AI assistants access to Indian mutual fund data, NSE/BSE market data and financial calculators.
Mutual Fund Holdings API
Take back control of your financial data. A 100% offline Excel tracker for Indian Mutual Fund families that replaces cloud aggregators with local CAS parsing, automated XIRR, and smart tax harvesting.
Open source projects
Free investment calculator for SIP, Lumpsum, SWP, IDCW & NCD+SIP — estimate your mutual fund returns instantly.
Flutter Package to get the current(Today's) NAVs of Mutual Funds in India
Mutual Fund Data Analysis using AI is your financial sidekick 🚀💰. It dives into the world of mutual funds with the wisdom of AI, calculating trends, cracking jokes, and presenting insights in a language even your piggy bank would appreciate! 🐷✨
Carolina Digital Access Coalition's official webpage.
Collected data on 25 mutual funds and analyzed them using pivot tables and an interactive dashboard to evaluate NAV trends, risk metrics, expense ratios, fund manager track records, and performance consistency. Based on the insights, tailored portfolios for three investor profiles were designed, aligning fund choices with their age, investment goal
This project test the accuracy of ML models on Nifty 100 companies over 3 years data. This project was made in collaboration with @Jeetmajhi10
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