Optimal Trading with Limit Orders on a Dynamic Limit Order Book

2014 ◽  
Author(s):  
Craig W. Holden
Keyword(s):  
Limit Order Book ◽  
Order Book ◽  
Limit Order ◽  
Optimal Trading ◽  
Limit Orders

OPTIMAL TRADING STRATEGIES WITH LIMIT ORDERS

2017 ◽  
Vol 20 (01) ◽  
pp. 1750005 ◽  
Author(s):  
ROSSELLA AGLIARDI ◽  
RAMAZAN GENÇAY
Keyword(s):  
Risk Attitude ◽  
Limit Order Book ◽  
Trading Strategies ◽  
Market Volatility ◽  
Order Book ◽  
Management Problem ◽  
Limit Order ◽  
Optimal Trading ◽  
Limit Orders ◽  
Realistic Modeling

A model is proposed to study the risk management problem of designing optimal trading strategies in a limit order book. The execution of limit orders is uncertain, which leads to a stochastic control problem. In contrast to previous literature, we allow the agents to choose both the quotes and the sizes of their submitted orders. Attention is paid to how the trading strategy is affected by an order book’s characteristics, market volatility and the trader’s risk attitude. We prescribe an optimal splitting of the order size for the trades with limit orders, while the existing literature offers a solution to this problem with market orders, and, at the same time, we provide guidelines to optimally place orders further behind the best price or to (re)position them more aggressively. Thus this paper is an attempt towards a more realistic modeling of optimal liquidation throughout limit 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.

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 How much market making does a market need?

2018 ◽  
Vol 55 (3) ◽  
pp. 667-681
Author(s):  
Vít Peržina ◽  
Jan M. Swart
Keyword(s):  
Equilibrium Distribution ◽  
Limit Order Book ◽  
Walrasian Equilibrium ◽  
Order Book ◽  
Limit Order ◽  
Demand And Supply ◽  
Market Makers ◽  
Limit Orders ◽  
Bid Price ◽  
Random Level

AbstractWe consider a simple model for the evolution of a limit order book in which limit orders of unit size arrive according to independent Poisson processes. The frequencies of buy limit orders below a given price level, respectively sell limit orders above a given level, are described by fixed demand and supply functions. Buy (respectively, sell) limit orders that arrive above (respectively, below) the current ask (respectively, bid) price are converted into market orders. There is no cancellation of limit orders. This model has been independently reinvented by several authors, including Stigler (1964), and Luckock (2003), who calculated the equilibrium distribution of the bid and ask prices. We extend the model by introducing market makers that simultaneously place both a buy and sell limit order at the current bid and ask price. We show that introducing market makers reduces the spread, which in the original model was unrealistically large. In particular, we calculate the exact rate at which market makers need to place orders in order to close the spread completely. If this rate is exceeded, we show that the price settles at a random level that, in general, does not correspond to the Walrasian equilibrium price.

The Information Content of Open Limit order Book in Price Discovery of KOSPI200 index Futures Market

2010 ◽  
Vol 18 (1) ◽  
pp. 1-42
Author(s):  
Woo Baik Lee ◽  
Jong Oh Kim ◽  
Min Cheol Woo
Keyword(s):  
Price Discovery ◽  
Empirical Finding ◽  
Correction Method ◽  
Futures Market ◽  
Limit Order Book ◽  
Order Book ◽  
Information Share ◽  
Limit Order ◽  
Index Futures ◽  
Limit Orders

This paper assesses the informational contents of open electronic limit order book in KOSPI 200 index futures market spanning sample period from December 2004 to November 2005 with a particular focus on the incremental information contained in the limit orders behind the best bid and offer. Using Vector Error Correction Method to estimate ‘Information share’ of quotes as suggested by Hasbrouck (1995), we find that the order book is significantly informative–its contribution to price discovery is approximately above 70%, while remaining is from cash price. Furthermore, we find the limit orders from step 2 to 5 is more informative than the best bid and offer in price discovery process, based on the estimation of information share. This empirical finding sharply contradicts the evidence suggested by previous literature that the best quotes contribute the most to price discovery and the contribution of order book the beyond the best bid and offer is marginally additional in cash market. Summarizing overall empirical evidence, limit order book in KOSPI 200 index futures market plays a differential role in contrast with stock markets.

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