This project aims to perform stock market analysis using Python, utilizing the yfinance API from Yahoo Finance to collect stock price data for the last year from the current date. It also utilizes the Plotly library to generate various graphs, such as a candlestick chart, bar plot, and time period selectors.

Analyzing DJIA stocks using fundamental analysis with Python

I've developed a web-based stock market dashboard using Python and Streamlit that provides real-time market data visualization and analysis.

Stock analysis website allowing investors real-time sentiment analysis of news articles related to specific stock tickers, alongside features like tracking sentiment trends over time and personalized watchlist recommendations, enhancing investment decision-making.

adding all working code in main.py and data contains the example of t… …he data fetched an mcap-- excel contains the list of all stocks present in nse by march 31 2024 and symbol result contains two sheets valid and invalid sshhet, here valid sheet contain all the stocks symbols by which this script can fetch the data using yfinace

Data visualization app for S&P500 tickers, with Machine Learning

Algorithmic Trading is the use of algorithms in the financial market to make trading decisions. JP Morgan Chase & Co. is one of the businesses that use Algorithmic Trading for investment decisions.

A Flask app that serves as a sentiment analysis RESTful API and serves JSON responses.

Project I completed for SRS Consulting Inc. after my work experience placement. Involves web scraping, APIs and sends email to users after validation of data. I can't share all of the code as there is some sensitive data like passwords but I have shared all of the code that doesn't include personal data.

Use Backtrader python library to create a trading strategy and applied on several ASX stocks

I'm testing APIs to collect financial data from cryptocurrencies and stocks.

stock analysis and visualisation app using streamlit app and yfinance API

Stock prediction webapp using LSTM model for prediction, Streamlit for frontend /backend and yfinance for datafetching.

Study of a system for analyzing historical stock data with predictions using a neural network.

The code starts by importing the necessary libraries to perform data analysis, such as pandas for data manipulation, matplotlib and seaborn for data visualization, and yfinance for collecting financial data.

Stock price prediction using lstm. Model Deployment using streamlit

Final Project: Analyzing Stock Performance and Building a Dashboard

Analyzing Historical Stock/Revenue Data and Building a Dashboard

Proyecto escolar que permitirá desplegar un dashboard con NextJS que utiliza la API de Yahoo Finance, para desplegar diversos algoritmos de Minería de Datos.