In a financial market, for agents with long investment horizons or at times
of severe market stress, it is often changes in the asset price that act as the
trigger for transactions or shifts in investment position. This suggests the
use of price thresholds to simulate agent behavior over much longer timescales
than are currently used in models of order-books.
We show that many phenomena, routinely ignored in efficient market theory,
can be systematically introduced into an otherwise efficient market, resulting
in models that robustly replicate the most important stylized facts.
We then demonstrate a close link between such threshold models and queueing
theory, with large price changes corresponding to the busy periods of a
single-server queue. The distribution of the busy periods is known to have
excess kurtosis and non-exponential decay under various assumptions on the
queue parameters. Such an approach may prove useful in the development of
mathematical models for rapid deleveraging and panics in financial markets, and
the stress-testing of financial institutions