  In this paper we demonstrate a striking regularity in the way people place
limit orders in financial markets, using a data set consisting of roughly seven
million orders from the London Stock Exchange. We define the relative limit
price as the difference between the limit price and the best price available.
Merging the data from 50 stocks, we demonstrate that for both buy and sell
orders, the unconditional cumulative distribution of relative limit prices
decays roughly as a power law with exponent approximately 1.5. This behavior
spans more than two decades, ranging from a few ticks to about 2000 ticks. Time
series of relative limit prices show interesting temporal structure,
characterized by an autocorrelation function that asymptotically decays as
tau^(-0.4). Furthermore, relative limit price levels are positively correlated
with and are led by price volatility. This feedback may potentially contribute
to clustered volatility.
