This stock portfolio tracker web application is a way for users to keep track of their stock portfolio, offering a personalized dashboard for users to have a comprehensive overview of their portfolio history. The app is built using python, flask, and HTML/CSS. The statistical visualizations are made using Bokeh and the stock data is from the yfinance package.
To use the app, just enter a stock ticker, a date, and how many shares of the stock was purchased.
stock_tracker_demo.mp4
Portfolio Forecasting : The project implements a neural network predictive model using TensorFlow and LSTM layers to forecast future stock prices. The model takes historical data as input and provides predictions for the next day's closing price. These predictions will be used as a way to forecase portfolio performance.
Data Processing: Add method to enable users to upload and export stock data so users do not have to enter their portfolio each time.
Live Stock Info: By integrating a stock price api that allows for real time stock data, the tracker will be able to make real time updates.