  The time proximity of high-frequency trades can contain a salient signal. In
this paper, we propose a method to classify every trade, based on its proximity
with other trades in the market within a short period of time, into five types.
By means of a suitably defined normalized order imbalance associated to each
type of trade, which we denote as conditional order imbalance (COI), we
investigate the price impact of the decomposed trade flows. Our empirical
findings indicate strong positive correlations between contemporaneous returns
and COIs. In terms of predictability, we document that associations with future
returns are positive for COIs of trades which are isolated from trades of
stocks other than themselves, and negative otherwise. Furthermore, trading
strategies which we develop using COIs achieve conspicuous returns and Sharpe
ratios, in an extensive experimental setup on a universe of 457 stocks using
daily data for a period of four years.
