When does the tick size help or harm market quality? Evidence from the Tick Size Pilot

Tick sizes affect market quality through a tradeoff between pricing fidelity and undercutting. The U.S. Tick Size Pilot (TSP), which raised the minimum tick from 1¢ to 5¢, provides a natural experiment to study this tradeoff. We find that the TSP harmed liquidity for stocks with spreads below 10¢ but improved liquidity for stocks with spreads above 15¢. These opposing effects explain the mixed results across prior studies which pool together stocks with very different prevailing spreads. We recommend researchers using the TSP for causal inference should, at minimum, split samples at 10¢-spreads to account for these heterogeneous liquidity effects. • We study the market-quality effects of a change in tick size using a difference-in-difference quantile and OLS regression approaches to compare market quality metrics between TSP test groups (G1 and G2) and control stocks. • Our analysis provides evidence of the tradeoff between price fidelity and undercutting risk faced by liquidity providers driven by a change in the tick size by analyzing quoted spreads, effective spreads, depth at National Best Bid and Offer (NBBO), cumulative depth in the order book, round-trip costs associated with trades (CRT), undercutting activity measured by QID ratio, and cancel-to-trade ratios. • We conduct our analysis in four bins of TSP stocks constructed according to their pre-TSP quoted spreads. We show that for stocks with quoted spreads less than approximately $0.10 (narrow spreads), increasing tick size harmed market quality by exacerbating pricing fidelity concerns. In sharp contrast, for stocks with quoted spreads greater than approximately $0.15 (wide spreads), increasing tick size improved market quality by mitigating undercutting behavior. • Our paper highlights that regulators like the SEC should consider varying impacts based on stock characteristics when updating tick sizes rather than applying uniform rules. • Moreover, our findings suggest that researchers using the TSP for causal inference should bifurcate samples based on prior thresholds in quoted spreads instead of treating all non-tick constrained stocks uniformly. Otherwise, the findings can be contaminated by the opposing effects of the TSP conditional on stock characteristics, which can make interpretations unreliable.