Stock Market Data
In this chapter, we’ll introduce temporal data and dive into stock market trend analysis. To understand trends over time, we’ll return to centrality measurements on networks and introduce some more advanced algorithms. Finally, we’ll analyze stock pricing data over time using our centrality measurements and pinpoint changes in behavior over time within and across different stocks to predict spikes and crashes in price.
By the end of this chapter, you’ll be able to wrangle datasets with time components into a series of networks and analyze structural changes over time with centrality metrics. Many of the centrality metrics scale well to large networks, particularly when they are run in parallel.
Specifically, we will cover the following topics:
- Introduction to temporal data
- Introduction to centrality metrics
- Application of centrality metrics across time slices
- Extending network metrics for time series analytics ...
