What is a stock correlation network?

It’s a type of scientific research used to predict movements in the stock market. It looks at the relationship between stocks using linked data such as daily closing prices, trading volume, opening prices and price returns.

Where have you heard about stock correlation networks?

In recent years there has been much emphasis placed on how network theory can be used to explain and better understand the financial markets. Stock correlation networks are increasingly being used to forecast market dynamics.

What you need to know about stock correlation networks.

There are two main steps involved in building a stock correlation network. The first considers how stocks traded in a market are affected by varying time series, or sequence of data points. The second step then tries to connect the stocks based on their correlation.

The most popular method for connecting two correlated stocks is the minimum spanning tree method, which connects all the vertices of a graph together. This can be pictured by thinking of a telecommunications company trying to lay out phone cables in new neighbourhood.

Find out more about stock correlation networks.

For background information, read our definition of correlation.