Abstract
I study how crossing networks, a type of dark pool, affect price discovery and market liquidity in the presence of noisy and heterogeneous trader signals. I identify a buffer function of crossing networks that helps mitigate traders’ losses from false signals. Additionally, I uncover an amplification effect. That is, when signal precision is high, crossing networks enhance price discovery. By contrast, when signal precision is low, crossing networks impair price discovery. These insights reconcile conflicting empirical evidence, yielding novel predictions and regulatory recommendations for equity and emerging markets.
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