⚡ Python library for getting publically available Mutual Funds data in India

This library utilizes Kite Connect APIs to fetch the option chain of all the derivatives traded in the Indian stock market.

In Stock Market Prediction, our aim is to build an efficient Machine Learning model to predict the future value of the financial stocks of a company.Our machine learning model will be presented to retail investors with a third-party web app with the help of Streamlit.

An unofficial Python API for BSE India Stock Exchange

Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.

That script is getting data of NFO`s OPTIDX from AngelOne using SmartApi

This repository contains code and videos related to financial data analysis using python.

Scrapes indian market news data

A Golang module to read the symbols listed Indian stock exchange and their valuations.

An Async library for accessing Indian stock broker API and Websockets.

This NSE Tool app is developed using C# that scrapes NSE live Stocks prices and gives you Pivot, Resistance and DMA for your selected stocks.

Get the current and historic stock information in your terminal.

This is a simple trading bot which generates live market data then use that same data in a simple sell strategy and finally show everything(profit & loss) on screen.

Wi-Fi Stock Crossover Notifier is an Arduino-based project that monitors stock data in real-time and sends email notifications when specific moving average crossovers occur in a specific stock.

An agent that helps you predict the next day's stock data.

Your Market Data Research Ends Here

extracting knowledge about indian stock market IPOs by analysing different types of clustering and graph plots for visualization.

An AI-driven workflow to monitor, analyze, and optimize your Indian stock portfolio using free tools and local LLM inference via Ollama.

Dynamic Financial Markets is a data-driven project analyzing stock interactions in the Indian cement sector. Using models like GARCH, Johansen Cointegration, and VAR, it explores volatility, long-term relationships, and dynamic dependencies among Shree Cement, UltraTech, and Ambuja Cement.

This is an AI Trading System currently in its early stages yet to be deployed and tested. The core idea is to create a system that can think on its own and make decisions and stratergies to make trades in FnO segment in Indian stock market.