Limit Order Flow and Book Resilience at the Meso-Scale

Summary

This study analyzes how order flow and limit order book structure relate to price formation on a meso-scale, a horizon motivated by execution scheduling. Tick-by-tick data are grouped into volume-based buckets, and the analysis considers market and limit order submissions alongside measures of book depth and shape. The empirical sample covers six large-tick Nasdaq assets.

The study finds a nonlinear relationship between trade imbalance and price changes, while a weighted combination of market and limit order flows yields a linear link. Trade imbalance also has a hockey-stick relationship with one-sided limit order flows, indicating asymmetries between active and passive trading. Statistical models assess predictive power for price formation, liquidity, and resilience; limit order flows and relative addition or cancellation rates are most informative at this horizon. Deeper book shape contributes more than imbalance alone. These findings are specific to the assets and timescale analyzed, and the document does not describe a deployable execution strategy or report out-of-sample trading results.

Key ideas

• The analysis aggregates tick data into volume-based buckets to study meso-scale dynamics.
• A weighted combination of market and limit order flows linearizes their link with price changes.
• Trade imbalance has an asymmetric, hockey-stick relationship with one-sided limit order flow.
• Limit order flows and relative addition or cancellation rates have the strongest predictive power in the study.
• Deeper order book shape is more informative than book imbalance alone at this timescale.

Tags

# Order Flows and Limit Order Book Resiliency on the Meso-Scale


# Order Flows and Limit Order Book Resiliency on the Meso-Scale









We investigate the behavior of limit order books on the meso-scale motivated by order execution scheduling algorithms. To do so we carry out empirical analysis of the order flows from market and limit order submissions, aggregated from tick-by-tick data via volume-based bucketing, as well as various LOB depth and shape metrics. We document a nonlinear relationship between trade imbalance and price change, which however can be converted into a linear link by considering a weighted average of market and limit order flows. We also document a hockey-stick dependence between trade imbalance and one-sided limit order flows, highlighting numerous asymmetric effects between the active and passive sides of the LOB. To address the phenomenological features of price formation, book resilience, and scarce liquidity we apply a variety of statistical models to test for predictive power of different predictors. We show that on the meso-scale the limit order flows (as well as the relative addition/cancellation rates) carry the most predictive power. Another finding is that the deeper LOB shape, rather than just the book imbalance, is more relevant on this timescale. The empirical results are based on analysis of six large-tick assets from Nasdaq.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.