Do Stocks Stalk Other Stocks in Their Complex Network? A Complex Networks Approach to Stock Market Dynamics

Abstract

This article presents a complex network approach to analyze the dynamics of the US stock market. The authors first introduce a machine learning technique to learn a latent space representation of the financial instruments using a complex networks approach to analyze the dynamics of the stock market. They show that the clustering of co-moving assets and breaking of already existing clusters have interesting connections to regime changes in the market. The authors also present some preliminary ideas on incorporating the effects of news and announcements in the dynamics of the assets.

TOPICS: Big data/machine learning, security analysis and valuation