  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.
