I study asset pricing when re-trade can take place in co-existing and interconnected markets. In my framework, there is a divisible asset and a finite set of traders. They are distributed over a trading network. Traders can acquire shares at a common price, and then they may trade with their connections at possibly different prices. I find that trading centrality, a novel network metric, is a sufficient statistic for the equilibrium. Trading centrality processes information about expected re-trade equilibria, and maps it to traders’ behavior before trade. A trader’s asset acquisition is proportional to his centrality, and the asset common price is defined by aggregating centrality globally. For the re-trades in the network, a trader demands the gap between his optimal level of asset and his centrality; while each price is defined by aggregating centrality locally in the seller’s network. I investigate what market outcomes and welfare arise at different trading networks. Implications for asset issuance and interdealer markets are examined.