  We follow the main stocks belonging to the New York Stock Exchange and to
Nasdaq from 2003 to 2012, through years of normality and of crisis, and study
the dynamics of networks built on two measures expressing relations between
those stocks: correlation, which is symmetric and measures how similar two
stocks behave, and Transfer Entropy, which is non-symmetric and measures the
influence of the time series of one stock onto another in terms of the
information that the time series of one stock transmits to the time series of
another stock. The two measures are used in the creation of two networks that
evolve in time, revealing how the relations between stocks and industrial
sectors changed in times of crisis. The two networks are also used in
conjunction with a dynamic model of the spreading of volatility in order to
detect which are the stocks that are most likely to spread crises, according to
the model. This information may be used in the building of policies aiming to
reduce the effect of financial crises.
