Dynamic analysis of influential stocks based on conserved networks

TL;DR

This paper introduces a micro-level network-based approach to analyze the temporal evolution of stock markets, identifying influential stocks and sectors through conserved networks, and successfully recovers the 2008 financial crisis from this perspective.

Contribution

It proposes a novel method using conserved networks to analyze stock market dynamics and identify influential stocks over time, offering deeper insights than macro measures.

Findings

Successfully identified influential stocks and sectors during market evolution.

Recovered the 2008 financial crisis from the network analysis perspective.

Provided a new framework for longitudinal market analysis.

Abstract

Characterizing temporal evolution of stock markets is a fundamental and challenging problem. The literature on analyzing the dynamics of the markets has focused so far on macro measures with less predictive power. This paper addresses this issue from a micro point of view. Given an investigating period, a series of stock networks are constructed first by the moving-window method and the significance test of stock correlations. Then, several conserved networks are generated to extract different backbones of the market under different states. Finally, influential stocks and corresponding sectors are identified from each conserved network, based on which the longitudinal analysis is performed to describe the evolution of the market. The application of the above procedure to stocks belonging to Standard \& Pool's 500 Index from January 2006 to April 2010 recovers the 2008 financial crisis from the evolutionary perspective.