Information arrives at securities markets through price quotes and trades. Informed traders impose adverse-selection costs on quote suppliers. This creates incentives for the latter to identify relatively uninformed groups and trade with them off-exchange. The marketplace turns hybrid, at the cost of thinner, highly informed (toxic) volume at the center. This pattern has largely eluded econometricians, because the standard approach to measuring information shares is biased against finding it. We show why this is the case, and design a bias-free approach. The novel approach shows that, indeed, the conjectured pattern is strongly present in the data.

Trading at decentralized exchanges (DEXs) requires traders to bid blockchain fees to determine the execution priority of their orders. We employ a structural vector-autoregressive (structural VAR) model to provide evidence that DEX trades with high fees not only reveal more private information, but also respond more to public price innovations on centralized exchanges (CEXs), contributing to price discovery. Using a unique dataset of Ethereum mempool orders, we further demonstrate that high fees do not result from traders competing with each other on private or public information. Rather, our analysis lends support to the hypothesis that they bid high fees to reduce the execution risk of their orders due to blockchain congestion.