We analyse the well-known TORQ dataset of trades on the NYSE over a 3-month period, breaking down transactions depending on whether the active or passive side was institutional or private. This allows us to compare the returns on the different trade categories. We find that, however we analyse the results, institutions are best informed, and earn highest returns when trading with individuals as counterparty. We also confirm the conclusions found elsewhere in the literature that informed traders often place limit orders, especially towards the end of the day (as predicted on the basis of laboratory experiments in Bloomfield, O'Hara, and Saar (2005)). Finally, we find that trading between institutions accounts for the bulk of trading volume, but carries little information and seems to be largely liquidity-driven.