  We use insight from a model of earth tectonic plate movement to obtain a new
understanding of the build up and release of stress in the price dynamics of
the worlds stock exchanges. Nonlinearity enters the model due to a behavioral
attribute of humans reacting disproportionately to big changes. This nonlinear
response allows us to classify price movements of a given stock index as either
being generated due to specific economic news for the country in question, or
by the ensemble of the worlds stock exchanges reacting together like a complex
system. Similar in structure to the Capital Asset Pricing Model in Finance, the
model predicts how an individual stock exchange should be priced in terms of
the performance of the global market of exchanges, but with human behavioral
characteristics included in the pricing. A number of the models assumptions are
validated against empirical data for 24 of the worlds leading stock exchanges.
We show how treshold effects can lead to synchronization in the global network
of stock exchanges.
