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.
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