Showing results for JPM TICKER
GitHub Repo
https://github.com/GonzaloMaidana2000/web_Scrapping_yahoo_finances
GonzaloMaidana2000/web_Scrapping_yahoo_finances
The data science team would like to retrieve information on some blue chip companies. They found it on YahooFinance webpage and they know that the information that they want is not available in the YahooFinance’s API. Write a web scraping script to gather the information that the data scientist team wants from YahooFinance. Tickers = [“JNJ”, “BRK.B”, “JPM”, “MMM”, “ABBV”, “DIS”, “T”, “PG”, “LOW”, “CI”] Fields = [Operating Income, Net Income From Continuing Operations, Retained Earnings, Change In Cash, Net Borrowings] Webpage = https://finance.yahoo.com/quote/Ticker/financials?p=Ticker Periods: Last 4 Quarters Provide for the data science team the code for a code review and a CSV with the following fields: Ticker, Field, Value, End Date, Scrape Date (date you ran your code).
GitHub Repo
https://github.com/Saikanth-G/Market-Anomaly-Detection-Forecasting
Saikanth-G/Market-Anomaly-Detection-Forecasting
End-to-end financial data analysis project covering 6 years of daily OHLCV data for 6 tickers (AAPL, JPM, XOM, AMZN, SPY, GLD). Detects market anomalies using Isolation Forest ML combined with rolling Z-score analysis, forecasts SPY 90 days forward with Prophet, and quantifies risk-adjusted performance for each asset.
GitHub Repo
https://github.com/Ollie-Gullery/stock_movement
Ollie-Gullery/stock_movement
A python program that scrapes https://finance.yahoo.com/ based on a list of input tickers (default is 'JPM', 'AAPL', 'AMZN', 'WMT') and uses Random Forest to classify upwards or downwards movements.
GitHub Repo
https://github.com/ChaseModules/JPMC-tech-task-1-py3
ChaseModules/JPMC-tech-task-1-py3
module 1, getting prices from stock ticker
GitHub Repo
https://github.com/llew-dev/stock_ticker
llew-dev/stock_ticker
A program that retrieves and displays real-time stock prices for any user given ticker symbol (i.e "JPM") using Finnhub's API's. I built this project to learn how to interact with live financial API's and to implement robust error handling (using try...except blocks) to manage potential runtime issues like connection failures or invalid inputs.
GitHub Repo
https://github.com/jagguvarma15/Time-Series-Forecasting-on-Stock-Data