scholarly journals The price impact of order book events: market orders, limit orders and cancellations

2012 ◽  
Vol 12 (9) ◽  
pp. 1395-1419 ◽  
Author(s):  
Zoltán Eisler ◽  
Jean-Philippe Bouchaud ◽  
Julien Kockelkoren
Keyword(s):  
Price Impact ◽  
Order Book ◽  
Limit Orders ◽  
Market Orders

scholarly journals Trade informativeness and liquidity in Bitcoin markets

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255515
Author(s):  
J. Christopher Westland
Keyword(s):  
Trading Volume ◽  
Limit Order Book ◽  
Small Sample ◽  
Market Liquidity ◽  
Order Book ◽  
Information Asymmetries ◽  
Limit Order ◽  
Limit Orders ◽  
Market Orders ◽  
Book Markets

Liquid markets are driven by information asymmetries and the injection of new information in trades into market prices. Where market matching uses an electronic limit order book (LOB), limit orders traders may make suboptimal price and trade decisions based on new but incomplete information arriving with market orders. This paper measures the information asymmetries in Bitcoin trading limit order books on the Kraken platform, and compares these to prior studies on equities LOB markets. In limit order book markets, traders have the option of waiting to supply liquidity through limit orders, or immediately demanding liquidity through market orders or aggressively priced limit orders. In my multivariate analysis, I control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity. The current research offers the first empirical study of Glosten (1994) to yield a positive, and credibly large transaction cost parameter. Trade and LOB datasets in this study were several orders of magnitude larger than any of the prior studies. Given the poor small sample properties of GMM, it is likely that this substantial increase in size of datasets is essential for validating the model. The research strongly supports Glosten’s seminal theoretical model of limit order book markets, showing that these are valid models of Bitcoin markets. This research empirically tested and confirmed trade informativeness as a prime driver of market liquidity in the Bitcoin market.

High Frequency Asymptotics for the Limit Order Book

2016 ◽  
Vol 02 (01) ◽  
pp. 1650004 ◽  
Author(s):  
Peter Lakner ◽  
Josh Reed ◽  
Sasha Stoikov
Keyword(s):  
Poisson Process ◽  
High Frequency ◽  
Limit Order Book ◽  
Order Book ◽  
Limit Order ◽  
Limit Orders ◽  
Long Run ◽  
Frequency Regime ◽  
Market Orders ◽  
The One

We study the one-sided limit order book corresponding to limit sell orders and model it as a measure-valued process. Limit orders arrive to the book according to a Poisson process and are placed on the book according to a distribution which varies depending on the current best price. Market orders to buy periodically arrive to the book according to a second, independent Poisson process and remove from the book the order corresponding to the current best price. We consider the above described limit order book in a high frequency regime in which the rate of incoming limit and market orders is large and traders place their limit sell orders close to the current best price. Our first set of results provide weak limits for the unscaled price process and the properly scaled measure-valued limit order book process in the high frequency regime. In particular, we characterize the limiting measure-valued limit order book process as the solution to a measure-valued stochastic differential equation. We then provide an analysis of both the transient and long-run behavior of the limiting limit order book process.

Optimal Hedge Tracking Portfolios in a Limit Order Book

2017 ◽  
Vol 03 (02) ◽  
pp. 1850003
Author(s):  
Simon Ellersgaard ◽  
Martin Tegnér
Keyword(s):  
Three Dimensional ◽  
Limit Order Book ◽  
Order Book ◽  
Limit Order ◽  
Limit Orders ◽  
Viscosity Sense ◽  
Quasi Variational Inequality ◽  
Market Orders ◽  
Hamilton Jacobi Bellman ◽  
Optimal Hedge

Derivative hedging under transaction costs has attracted considerable attention over the past three decades. Yet comparatively little effort has been made towards integrating this problem in the context of trading through a limit order book. In this paper, we propose a simple model for a wealth-optimizing option seller, who hedges his position using a combination of limit and market orders, while facing certain constraints as to how far he can deviate from a targeted (Bachelierian) delta strategy. By translating the control problem into a three-dimensional Hamilton–Jacobi–Bellman quasi-variational inequality (HJB QVI) and solving numerically, we are able to deduce optimal limit order quotes alongside the regions surrounding the targeted delta surface in which the option seller must place limit orders vis-à-vis the more aggressive market orders. Our scheme is shown to be monotone, stable, and consistent and thence, modulo a comparison principle, convergent in the viscosity sense.

Liquidity and Information in Limit Order Markets

2019 ◽  
Vol 55 (6) ◽  
pp. 1792-1839 ◽  
Author(s):  
Ioanid Roşu
Keyword(s):  
Dynamic Model ◽  
Informed Trading ◽  
Price Impact ◽  
Limit Order ◽  
Limit Order Markets ◽  
Bid Ask Spread ◽  
Limit Orders ◽  
Informed Traders ◽  
Market Orders

How does informed trading affect liquidity in limit order markets, where traders can choose between market orders (demanding liquidity) and limit orders (providing liquidity)? In a dynamic model, informed trading overall helps liquidity: A higher share of informed traders i) improves liquidity as proxied by the bid–ask spread and market resiliency, and ii) has no effect on the price impact of orders. The model generates other testable implications, and suggests new measures of informed trading.

scholarly journals Price Discovery in the U.S. Treasury Cash Market: On Principal Trading Firms and Dealers

2020 ◽  
Vol 2020 (095) ◽  
pp. 1-36
Author(s):  
James Collin Harkrader ◽  
◽  
Michael Puglia ◽  
Keyword(s):  
Theoretical Models ◽  
Limit Order Book ◽  
Price Impact ◽  
Market Liquidity ◽  
Order Book ◽  
Limit Order ◽  
Limit Orders ◽  
Cash Transaction ◽  
Informational Advantage

We explore the following question: does the trading activity of registered dealers on Treasury interdealer broker (IDB) platforms differ from that of principal trading firms (PTF), and if so, how and to what effect on market liquidity? To do so, we use a novel dataset that combines Treasury cash transaction reports from FINRA’s Trade Reporting and Compliance Engine (TRACE) and publicly available limit order book data from BrokerTec. We find that trades conducted in a limit order book setting have high permanent price impact when a PTF is the passive party, playing the role of liquidity provider. Conversely, we find that dealer trades have higher price impact when the dealer is the aggressive party, playing the role of liquidity taker. Trades in which multiple firms (whether dealers or PTFs) participate on one or both sides, however, have relatively low price impact. We interpret these results in light of theoretical models suggesting that traders with only a “small” informational advantage prefer to use (passive) limit orders, while traders with a comparatively large informational advantage prefer to use (aggressive) market orders. We also analyze the events that occurred in Treasury markets in March 2020, during the onset of the COVID-19 pandemic.

scholarly journals The Impact of Iceberg Orders in Limit Order Books

2017 ◽  
Vol 07 (03) ◽  
pp. 1750007 ◽  
Author(s):  
Stefan Frey ◽  
Patrik Sandås
Keyword(s):  
Informed Trading ◽  
Price Impact ◽  
Order Book ◽  
Limit Order ◽  
Reduced Order ◽  
Market Participants ◽  
Limit Orders ◽  
Order Books ◽  
Limit Order Books ◽  
The Impact

We examine the impact of iceberg orders on the price and order flow dynamics in limit order books. Iceberg orders allow traders to simultaneously hide a large portion of their order size and signal their interest in trading to the market. We show that when market participants detect iceberg orders they tend to strongly respond by submitting matching market orders consistent with iceberg orders facilitating the search for latent liquidity. The greater the fraction of an iceberg order that is executed, the smaller is its price impact consistent with liquidity rather than informed trading. The presence of iceberg orders is associated with increased trading consistent with a positive liquidity externality, but the reduced order book transparency associated with iceberg orders also creates an adverse selection cost for limit orders that may partly offset any gains.

OPTIMAL EXECUTION COST FOR LIQUIDATION THROUGH A LIMIT ORDER MARKET

2016 ◽  
Vol 19 (01) ◽  
pp. 1650004 ◽  
Author(s):  
ETIENNE CHEVALIER ◽  
VATHANA LY VATH ◽  
SIMONE SCOTTI ◽  
ALEXANDRE ROCH
Keyword(s):  
Optimal Solution ◽  
Jump Process ◽  
Arrival Process ◽  
Order Book ◽  
Continuous Control ◽  
Limit Order ◽  
Bid Ask Spread ◽  
Limit Orders ◽  
Market Orders ◽  
Limit Order Market

We study the problem of optimally liquidating a large portfolio position in a limit-order market. We allow for both limit and market orders and the optimal solution is a combination of both types of orders. Market orders deplete the order book, making future trades more expensive, whereas limit orders can be entered at more favorable prices but are not guaranteed to be filled. We model the bid-ask spread with resilience by a jump process, and the market-order arrival process as a controlled Poisson process. The objective is to minimize the execution cost of the strategy. We formulate the problem as a mixed stochastic continuous control and impulse problem for which the value function is shown to be the unique viscosity solution of the associated variational inequalities. We conclude with a calibration of the model on recent market data and a numerical implementation.

scholarly journals Optimal Liquidity-Based Trading Tactics

2021 ◽  
Author(s):  
Charles-Albert Lehalle ◽  
Othmane Mounjid ◽  
Mathieu Rosenbaum
Keyword(s):  
Control Problem ◽  
Utility Function ◽  
Expected Utility ◽  
Optimal Strategy ◽  
Price Impact ◽  
Time Interval ◽  
Order Book ◽  
Short Time Interval ◽  
Limit Orders ◽  
Short Time

We consider an agent who needs to buy (or sell) a relatively small amount of assets over some fixed short time interval. We work at the highest frequency meaning that we wish to find the optimal tactic to execute our quantity using limit orders, market orders, and cancellations. To solve the agent’s control problem, we build an order book model and optimize an expected utility function based on our price impact. We derive the equations satisfied by the optimal strategy and solve them numerically. Moreover, we show that our optimal tactic enables us to outperform significantly naive execution strategies.

Order Book Price Impact in the Chinese Soybean Futures Market

2020 ◽  
Author(s):  
Muzhao Jin ◽  
Fearghal Joseph Kearney ◽  
Youwei Li ◽  
Yung Chiang Yang
Keyword(s):  
Futures Market ◽  
Price Impact ◽  
Order Book ◽  
Book Price
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