In the Blink of an Eye: Exchange-to-SIP Latency and Trade Classification Accuracy

Abstract

We develop two new methods for matching trades and bid-ask quotes that account for information latency in the era of fast trading. The first method adjusts for exchange-to-SIP latency. The second method constructs exchanges' Relative Best Bid and Offer (RBBO) based on exchange-to-exchange latency and data center co-locations. We test these trade classification methods using over 650 million TAQ trades matched with order executions in TAQ Integrated Feed. We find that the first method improves the Lee Ready (1991) trade classification accuracy from 86% to 92%. Our preferred method, the RBBO method, further improves accuracy by another 58 bp but is computationally expensive. Using an exogenous technological shock, we find that adjusting for latency could alter research inferences when measuring liquidity.

Keywords: Latency, Trade Classification, Exchange Network, Liquidity

JEL Classification: C15, G12, G20