True Liquidity and Fundamental Prices: US Tick Size Pilot

Abstract

We develop a big-data methodology to estimate true stock prices and liquidity, explicitly considering rounding due to the minimum tick size. We apply our method to evaluate the tick size pilot (TSP), which increased the tick size for randomly chosen stocks. While the TSP increases market-maker profits, it does not improve liquidity. This is consistent with theoretical models but contrasts with existing empirical studies. Rounding-adjusted liquidity measures are validated by showing that they, unlike the existing liquidity measures, capture the TSP-induced trading restrictions, the decreased inventory holdings of market-makers, and exhibit less dispersion across exchanges. Accounting for rounding is important.

Keywords: True Liquidity, Fundamental Prices, True bid-ask spreads, US Tick Size Pilot, Machine Learning for Structural Estimation, Variational Inference, High-Frequency Data, Scalable Algorithms

JEL Classification: G14, G15, G18, C11, C55