Context
Stock market data can be interesting to analyze, strong predictive models can have large financial payoff. The amount of financial data on the web is seemingly endless. A large and well structured dataset on a wide array of companies can be hard to come by. Here I view a dataset with historical stock prices for all companies on the S&P 500 index.
Content
All the files have the following columns:
Date - in format: yy-mm-dd
Open - price of the stock at market open (this is NYSE data so all in USD)
High - highest price reached in the day
Low - lowest price reached in the day
Close - close price
Volume - number of shares traded
Acknowledgements
Thanks to Kaggle, Github, yahoo finance.
Purpose of creating the dataset
This dataset lends itself to a some very interesting visualizations. One can look at simple things like how prices change over time, graph an compare multiple stocks at once, or generate and graph new metrics from the data provided.
From these data informative stock stats such as volatility and moving averages can be easily calculated.
And people can build quantitative models such as: build portfoio, predict volatility, arbitrage, trading strategies.