Time value of extra information against its timely value

TL;DR

This paper analyzes how the timing and value of new information affect market efficiency, profit distribution, and price discovery in a sequential auction setting with risk considerations.

Contribution

It introduces a model combining differential information, mutual learning, and dynamic trading strategies, with explicit formulas for expected P&L based on signal quality.

Findings

Exploiting new information promptly enhances market efficiency.

Explicit formulae for signal-based expected P&L are derived.

Market equilibrium prices can be expressed as weighted averages of individual signals.

Abstract

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.