  We consider issues of time in automated trading strategies in simulated
financial markets containing a single exchange with public limit order book and
continuous double auction matching. In particular, we explore two effects: (i)
reaction speed - the time taken for trading strategies to calculate a response
to market events; and (ii) trading urgency - the sensitivity of trading
strategies to approaching deadlines. Much of the literature on trading agents
focuses on optimising pricing strategies only and ignores the effects of time,
while real-world markets continue to experience a race to zero latency, as
automated trading systems compete to quickly access information and act in the
market ahead of others. We demonstrate that modelling reaction speed can
significantly alter previously published results, with simple strategies such
as SHVR outperforming more complex adaptive algorithms such as AA. We also show
that adding a pace parameter to ZIP traders (ZIP-Pace, or ZIPP) can create a
sense of urgency that significantly improves profitability.
