Trading, Profits, and Volatility in a Dynamic Information Network Model

Abstract We introduce a dynamic noisy rational expectations model in which information diffuses through a general network of agents. In equilibrium, agents who are more closely connected have more similar period-by-period trades, and an agent’s profitability is determined by a centrality measure that is related to Katz centrality. Volatility after an information shock is more persistent in less central networks, and volatility and trading volume are also influenced by the network’s asymmetry and irregularity. Using account-level data of all portfolio holdings and trades on the Helsinki Stock Exchange between 1997 and 2003, we find support for the aggregate predictions, altogether suggesting that the market’s network structure is important for these dynamics.