By T. R. Hurd
This quantity offers a unified mathematical framework for the transmission channels for destructive shocks which can bring about instability in monetary structures. because the name indicates, monetary contagion is comparable to the unfold of affliction, and destructive monetary crises should be larger understood by means of bringing to endure principles from learning different advanced structures in our international. After contemplating how humans have considered monetary crises and systemic possibility some time past, it delves into the mechanics of the interactions among banking counterparties. It reveals a typical mathematical constitution for kinds of crises that continue via cascade mappings that method a cascade equilibrium. Later chapters stick to this topic, ranging from the underlying random skeleton graph, constructing into the idea of bootstrap percolation, eventually resulting in recommendations that could ensure the big scale nature of contagious monetary cascades.
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Additional info for Contagion! Systemic Risk in Financial Networks
Bank balance sheets are hugely complex. Interbank exposure data are never publicly available, and in many countries nonexistent even for central regulators. Sometimes, the only way to infer exposures is indirectly, for example, through bank payment system data as done in . Interbank exposures are of a diversity of types and known to change rapidly day to day. In a large jurisdiction like the US, the banking sector is highly heterogeneous, and the systemic impact due to the idiosyncrasies of individual banks will likely overwhelm anything one might predict from their average properties.
From this fact we can expect that for large N , an E–N model with fully specified parameters will behave as if it were a stochastic model with averaged characteristics. The second important reason is that in a concrete sense, true financial networks are stochastic at any moment in time. The balance sheets of banks, between reporting dates, are not observed even in principle. Moreover, they change so quickly that last week’s values, if they were known, will have only limited correlation with this week’s values.
Thus the bank must sell all fixed assets at this moment. However, as in the E–N model, the bank continues to lose money after it defaults, further eroding the value of Xv(n) . Thus, when r ∗ = 0 this model looks very similar to the E–N 2001 model, albeit with a G–K-like condition to determine the amount of fixed assets sold. The simplification r ∗ = 0 also provides a simpler setting to address a different question: how do fire sales create contagion when banks hold different portfolios of a multiplicity of assets.
Contagion! Systemic Risk in Financial Networks by T. R. Hurd