Popular GitHub Repositories for Yfinance

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

This project is about predicting stock prices with more accuracy using LSTM algorithm. For this project we have fetched real-time data from yfinance library.

Financial CrewAI Agents (LangChain, YF Tools, Ai Crew, Groq Inference)

Trading system that aims to buy stocks when they are low and sell stock when they have risen. The time horizon for trades is 2 - 45 days. The strategy has been successfully backtested in version 0.2. Next step: forward test strategy to ensure that it works in practice. Test RL to see if we can can improve results (currently only ~ 5 % of max.)

Using Machine Learning to predict future stock prices and creating a stock portfolio based on those predictions.

The Financial Analysis Crew is a Streamlit app that simplifies financial stock analysis. With the power of LLM-driven agents, users can seamlessly gather and analyze stock market data to generate comprehensive financial insights. Perfect for investors, analysts, and anyone interested in making data-driven financial decisions.

ML for finance and forecasting (LSTM, RL and BIMT)

CleverCall utilizes Cloudflare's AI for function calling, fetching dynamic data from APIs like GitHub and Yahoo Finance.

Timeseries Analysis based on Google Trends and Anomaly Detection

Predicting the future prices of cryptocurrency is based on the problem of Time series analysis

Unlock the power of AI by building intelligent agents from scratch! This repository provides a step-by-step guide to creating custom agents that can reason, act, and solve real-world problems

? YFinance Agent: An intelligent financial analysis chat Agent that leverages of yfinance data provide deep insights into stock market data. This is Your Quant Intern Researcher

Find real-time stock decision with AI-powered App using ChatGPT and LLM (Large Language Model) App.

An app for stock identification and assessment using Claude. Check it out on HF Spaces: https://huggingface.co/spaces/mchiovaro/stock-aidvisor

Nice Tutorial from DataQuest on using ML and Python for stock prediction

Real-Time AI Stock Advisor with Ollama (Llama 3) & Streamlit

Finance Assistant Bot using AI Agents

Un generador de contenido para redes sociales, que ofrece información financiera y además redacta artículos ciéntificos con la información actualizada de los papers más relevantes

AI-Driven Investment Insights by Financial Headline Sentiment Analysis

NvidiaFinRAG: Dynamic Multi-Agent is a dynamic pipeline that provides specific curated information based on the user’s specific queries regarding Nvidia’s financial dataset. It utilizes Langchain as its foundation and operates with three distinct agents to serve its knowledge base.