Since the beginning of the new millennium, stock markets went through every state from long-time troughs, trade suspensions to all-time highs. The literature on asset pricing hence assumes random processes to be underlying the movement of stock returns. Observed procyclicality and time-varying correlation of stock returns tried to give the apparently random behavior some sort of structure. However, common misperceptions about the co-movement of asset prices in the years preceding the Great Recession  , is said to have even fueled the crisis' economic impact. Here we show how a varying macroeconomic environment influences stocks' clustering into communities. From a sample of 296 stocks of the S\&P 500 index, the periods 2000 to 2007 and 2007 through 2009 are used to develop networks of stocks. The Minimal Spanning Tree analysis of those time-varying networks of stocks demonstrates that the crisis drove the market from a star-like random network in the pre-crisis period, to a highly clustered community structure during theGreat Recession . A comparison with theGeneral Industry Classification Standard conveys the impression that the crisis, besides its devestating macroeconomic effect, helped to  restore the stock market's ceased order of the pre-crisis era  .
Since the beginning of the new millennium, stock markets went through every state from long-time troughs, trade suspensions to all-time highs. The literature on asset pricing hence assumes random processes to be underlying the movement of stock returns. Observed procyclicality and time-varying correlation of stock returns tried to give the apparently random behavior some sort of structure. However, common misperceptions about the co-movement of asset prices in the years preceding the Great Recession and theGlobal Commodity Crisis , is said to have even fueled the crisis' economic impact. Here we show how a varying macroeconomic environment influences stocks' clustering into communities. From a sample of 296 stocks of the S\&P 500 index, distinct periods in between 2004 and 2011 are used to develop networks of stocks. The Minimal Spanning Tree analysis of those time-varying networks of stocks demonstrates that the crises of 2007-2008 and 2010-2011 drove the market to clustered community structures in both periods, helping to restore the stock market's ceased order of the pre-crises era. However, a comparison of the emergent clusters with theGeneral Industry Classification Standard conveys the impression that industry sectors do not play a major role in that order .
A
and the
A
Global Commodity Crisis
R
the periods 2000 to 2007 and 2007 through 2009
distinct periods in between 2004 and 2011
R
crisis
crises of 2007-2008 and 2010-2011
D
from a star-like random network in the pre-crisis period, to a highly clustered community structure during the
D
Great Recession
D
. A comparison with the
D
General Industry Classification Standard
D
conveys the impression that the crisis, besides its devestating macroeconomic effect, helped
A
clustered community structures in both periods, helping to
R
pre-crisis era
pre-crises era. However, a comparison of the emergent clusters with the
A
General Industry Classification Standard
A
conveys the impression that industry sectors do not play a major role in that order