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G. Marti et al.
ual financial institutions, may amplify aggregate fluctuations if they are widely
adopted:
For example, if the riskiness of assets held by one bank increases due to heightened
market volatility, to meet its VaR requirements the bank will have to sell some of these
risky assets. This liquidation may restore the bank’s financial soundness, but if all banks
engage in such liquidations at the same time, a devastating positive feedback loop may
be generated unintentionally. These endogenous feedback effects can have significant
implications for the returns of financial institutions, including autocorrelation, increased
correlation, changes in volatility, Granger causality, and, ultimately, increased systemic
risk, as our empirical results seem to imply.
• In [78], authors find that the move towards integration started some time ago and
there is probably no way to stop or refrain it. However, regulation authorities may
act in order to prevent prices shocks from occurring, especially in places where
their impact may be important.
• In [36], the author shows how Bayesian networks (and probabilistic graphical
models in general) can be used to model complex networks of debt dependencies
between firms. These particular types of networks allow for causal and counterfactual reasoning: What would happen if a set of institutions defaults? What would
happen if this institution is bailed out?
10.7 Practical Fruits of Clusters, Networks,
and Hierarchies
10.7.1 Stylized Facts
Stylized facts can be described as follows [30]
1 :
A set of [statistical] properties, common across many instruments, markets and time periods,
[which] has been observed by independent studies.
From the papers we reviewed, we can list the following stylized facts:
• Firms belonging to some economic sectors are strongly connected within themselves, whereas others are much less connected.
• The Energy and Financial sectors are examples of strong connections whereas
elements belonging to the Conglomerates, Consumer cyclical, Transportation, and
Capital Goods sectors are weakly connected.
• General Electric is at the center of US stocks networks (for several centrality
criteria) [15, 20, 89, 108].
• The Energy, Technology, and Basic Materials sectors are sectors of elements significantly connected among them but weakly interacting with stocks belonging to
different economic sectors.
1 reference to the book Practical Fruits of Econophysics [137]
G. Marti et al.
ual financial institutions, may amplify aggregate fluctuations if they are widely
adopted:
For example, if the riskiness of assets held by one bank increases due to heightened
market volatility, to meet its VaR requirements the bank will have to sell some of these
risky assets. This liquidation may restore the bank’s financial soundness, but if all banks
engage in such liquidations at the same time, a devastating positive feedback loop may
be generated unintentionally. These endogenous feedback effects can have significant
implications for the returns of financial institutions, including autocorrelation, increased
correlation, changes in volatility, Granger causality, and, ultimately, increased systemic
risk, as our empirical results seem to imply.
• In [78], authors find that the move towards integration started some time ago and
there is probably no way to stop or refrain it. However, regulation authorities may
act in order to prevent prices shocks from occurring, especially in places where
their impact may be important.
• In [36], the author shows how Bayesian networks (and probabilistic graphical
models in general) can be used to model complex networks of debt dependencies
between firms. These particular types of networks allow for causal and counterfactual reasoning: What would happen if a set of institutions defaults? What would
happen if this institution is bailed out?
10.7 Practical Fruits of Clusters, Networks,
and Hierarchies
10.7.1 Stylized Facts
Stylized facts can be described as follows [30]
1 :
A set of [statistical] properties, common across many instruments, markets and time periods,
[which] has been observed by independent studies.
From the papers we reviewed, we can list the following stylized facts:
• Firms belonging to some economic sectors are strongly connected within themselves, whereas others are much less connected.
• The Energy and Financial sectors are examples of strong connections whereas
elements belonging to the Conglomerates, Consumer cyclical, Transportation, and
Capital Goods sectors are weakly connected.
• General Electric is at the center of US stocks networks (for several centrality
criteria) [15, 20, 89, 108].
• The Energy, Technology, and Basic Materials sectors are sectors of elements significantly connected among them but weakly interacting with stocks belonging to
different economic sectors.
1 reference to the book Practical Fruits of Econophysics [137]