An essay on price impact: how limit order book events and order flow affect price formation

Duong, Hai (2025) An essay on price impact: how limit order book events and order flow affect price formation. PhD thesis, University of Glasgow.

Abstract

This thesis studies the price impact of limit order book events and their effects on price discovery. It consists of three independent essays that begin with examining the relationship between the shape of the limit order book and price impact.

Chapter 1 introduces the slope of the limit order book as a novel measure of price impact. By analyzing both the bid and ask sides of the high-frequency limit order book snapshot data, the study shows that there is a linear relationship between the cumulative size of liquidity and price impact in the limit order book. In addition, I find that if price impact admits a nonlinear functional form, under certain circumstances, a profitable round-trip arbitrage exists. I empirically show the minimum required trading volume for a profitable self-financing arbitrage and conditions that limit arbitrage.

Chapter 2 proposes a new approach to estimate the flow of this information and the price of that information (different from the stock price), and thus the total value of that information for each stock, and then sum up this value across all stocks, obtaining an estimate of the total value of the dynamic flow of information in the stock market as a whole. The results support the notion that the cross-correlation of price impact across stocks is consistent with the CAPM: there is a single systematic component of price impact, and this is driven by the volatility of the systematic component of the stock market. This result suggests that by separating the underlying information into two components, systematic and idiosyncratic, informed traders distinguish between productive assets that have a systematic impact on the economy and those that can be diversified.

Chapter 3 presents a two-period model of strategic interactions between a spoofer and a highfrequency trader (HFT) who employs pattern recognition algorithms to predict the incoming order. Detecting this strategy, the spoofer submits a spoofing order to mislead the HFT trader about the incoming order. The HFT protects itself by reducing its market participation. A pure strategy spoofing equilibrium exists and both spoofer and HFT make positive profits. It is shown that while spoofing delays price discovery in the short run, price dislocation will be so brief as to have few economic efficiency implications. Moreover, spoofing improves market liquidity and market welfare.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Subjects: H Social Sciences > HG Finance
• Colleges/Schools: College of Social Sciences > Adam Smith Business School > Economics
• Supervisor's Name: Taub, Professor Bart and Ewald, Professor Christian
• Date of Award: 2025
• Depositing User: Theses Team
• Unique ID: glathesis:2025-84848
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 29 Jan 2025 15:14
• Last Modified: 29 Jan 2025 15:21
• Thesis DOI: 10.5525/gla.thesis.84848
• URI: https://theses.gla.ac.uk/id/eprint/84848