  We introduce an interactive market setup with sequential auctions where
agents receive variegated signals with a known deadline. The effects of
differential information and mutual learning on the allocation of overall
profit \& loss (P\&L) and the pace of price discovery are analysed. We
characterise the signal-based expected P\&L of agents based on explicit
formulae for the directional quality of the trading signal, and study the
optimal trading pattern using dynamic programming and provided that there is a
common anticipation by agents of gains from trade. We find evidence in favour
of exploiting new information whenever it arrives, and market efficiency. Brief
extensions of the problem to risk-adjusted gains as well as risk-averse agents
are provided. We then introduce the `information-adjusted risk premium' and
recover the signal-based equilibrium price as the weighted average of the
signal-based individual prices with respect to the risk-aversion levels.
