Financial Stock Price Web App

Data science is spread across our lives and we are surrounded by its applications. We unknowingly use the vast number of applications of data science and machine learning such as recommender systems, house price prediction, data monitoring and data analysis etc. We are in fact surrounded by data and probably have played around with it many a times (especially if you're a math loving person). So here's another web app in yet another vital application of data science.

This is a financial stock price web app. It shows the closing financial stock price values for S and P 500 companies. S and P 500 companies are 500 of the largest companies listed on stock exchanges in the US. The S and P 500 stock market index comprises of 505 common stocks issued by 500 large cap companies. The stocks of these companies trade either on the NYSE (New York Stock Exchange) or NASDAQ (National Association of Securities Dealers Automated Quotations). NYSE is an auction market whereas NASDAQ is a dealer's market. Some of the S and P 500 companies included in the dataset are Alphabet, Apple, Amazon, Facebook, Microsoft etc. 

This web app displays information about the respective user input company (from the list of S and P 500 companies) and provides its stock chart along with other company share statistics. It displays information of the company such as its GICS sector, GICS sub-industry, headquarters location, CIK, etc. Users can analyze data over the past multiple years of the respective company.

Simple moving averages have also been provided so that users can compare the present value with the average value of stocks in a particular range. This helps to determine whether an asset price will continue or if it will reverse a bull or bear trend. Historical company shares along with company share data statistics have also been provided. 

Yahoo Finance and Yahoo Finance API was used to obtain the data. Users can also move their cursor over the stock charts to get the exact date and value of the stock price. Yahoo finance provides financial data, stock quotes, press releases etc. It alsooffers other tools for personal finance management.

Added feature: I added time series forecasting using fbprophet. Many people are unable to pip install that. This might be due to some reasons: fbprophet requires a C++ compiler, so if you're operating on Windows, better use anaconda instead of VScode. Fbprophet also requires pystan so make sure that is working and check for the compatibility of those two versions. For any other build issues, contact us or drop a comment. You can also check out Stack Overflow for additional errors during installation of fbprophet: https://stackoverflow.com/questions/56701359/running-setup-py-install-for-fbprophet-error. Other solutions might also be available on Github.

Coming onto the update, yes I've finally added time series forecasting for the stocks and now the app can predict the opening and closing stock price values of companies over a period of 1 to 15 years. Time series data using rangeslider can also be seen to find out historical opening and closing stock values. The forecast plot and components have also been provided. Stock values and predictions can also be seen on a weekly basis apart from their yearly values and trends.  

We have deployed the app using Streamlit. It is an open source framework that allows data science teams to deploy web apps fairly easily. It's one of the best hosting services I've used and it's great for quick and easy deployment of web apps. The app is majorly coded in python. 

This web app helped me to improve my experience in Machine Learning and definitely helped in my future projects. Feel free to add onto this project and don't hesitate to drop by any suggestions. Hope you enjoy the app!

Link of the app: https://share.streamlit.io/braxtonova/stockpred/main/app.py