The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity

2020 ◽  
Vol 53 ◽  
pp. 101194 ◽  
Author(s):  
Haijun Yang ◽  
Hengshun Ge ◽  
Ying Luo
Keyword(s):  
High Frequency ◽  
Market Liquidity ◽  
High Frequency Trading ◽  
Price Strategies

scholarly journals High-Frequency Trading Competition

2018 ◽  
Vol 54 (4) ◽  
pp. 1469-1497 ◽  
Author(s):  
Jonathan Brogaard ◽  
Corey Garriott
Keyword(s):  
High Frequency ◽  
Stock Exchange ◽  
Market Liquidity ◽  
High Frequency Trading ◽  
Toronto Stock Exchange ◽  
Bid Ask Spreads

Theory on high-frequency traders (HFTs) predicts that market liquidity for a security decreases in the number of HFTs trading the security. We test this prediction by studying a new Canadian stock exchange, Alpha, that experienced the entry of 11 HFTs over 4 years. We find that bid–ask spreads on Alpha converge to those at the Toronto Stock Exchange as more HFTs trade on Alpha. Effective and realized spreads for non-HFTs improve as HFTs enter the market. To explain the contrast with theory, which models the HFT as a price competitor, we provide evidence more consistent with HFTs fitting a quantity-competitor framework.

scholarly journals Aggressive and Defensive High‑Frequency Trading and its Impact on Liquidity of German Stock Market

2016 ◽  
Vol 64 (6) ◽  
pp. 1911-1918
Author(s):  
Juraj Hruška
Keyword(s):  
High Frequency ◽  
Stock Exchange ◽  
Low Frequency ◽  
Positive Influence ◽  
Market Liquidity ◽  
High Frequency Trading ◽  
Market Manipulation ◽  
Limit Orders ◽  
Market Risks ◽  
German Stock

Algorithmic trading and especially high frequency trading is the concern of the current research studies as well as legislative authorities. It is also the subject of criticism mostly from low frequency traders and long-term institutional investors. This is due to several cases of market manipulation and flash crashes in the previous years. Advocates of this trading mechanism claim that it has large positive influence on the market, such as liquidity growth by lowering spreads and others. This paper is focused on testing the relationship between market liquidity of shares traded on Frankfurt Stock Exchange and HFT activity on European stock markets. Author proposes own methodology for measuring dynamics in HFT activity, without knowledge of original market messages. Liquidity is measured by various from of price spreads. Econometrical methods for panel regression are used to determine these relations. Results of this paper will reveal the relevance of the HFT trader’s main argument about creating liquidity and hence reducing market risks related with high spreads and low number of limit orders.

Hidden and Fast Liquidity - Hidden Orders and High-Frequency Trading

e-Finanse ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 27-35
Author(s):  
Martins Carlos Jorge Lenczewski
Keyword(s):  
High Frequency ◽  
Current Knowledge ◽  
Market Liquidity ◽  
High Frequency Trading ◽  
Specific Topic ◽  
Literature Study ◽  
Actual Knowledge ◽  
Price Effects ◽  
The Us ◽  
Hidden Orders

AbstractThis work focuses on two of the more frequent practices in financial (especially capital) markets -the use of hidden orders and High-Frequency Trading (HFT). Although the use of each of them may reach 40% of the market turnover - even 60% for HFT, the actual knowledge on how they affect liquidity, prices, and market structure is still limited - especially if they are combined. The presence of both of these practices may look controversial, as it seems to be going in the opposite direction to what some of the goals that market regulators try to reach - transparency and increase of market liquidity. Additionally, their use suggests first, to give a clear advantage to some traders while not knowing the exact consequences to others. The aim of this paper is, by performing a literature study, to structure the current knowledge on a very specific topic in the area of market microstructure - the use of hidden orders and High-Frequency Trading. This paper tries to show the motivations, strategies, and eventual price effects behind hidden orders and High-Frequency Trading. It is also important to mention that this paper is based on scarce empirical research available (mainly for the US market) and as such, it is intended to encourage further analysis and research on this important topic.

The Impact of High-Frequency Trading on Australian Futures Market Liquidity and Efficiency

2020 ◽  
Vol 27 (4) ◽  
pp. 51-76
Author(s):  
Panha Heng ◽  
Scott J. Niblock ◽  
Jennifer L. Harrison ◽  
Hansi Hu
Keyword(s):  
High Frequency ◽  
Futures Market ◽  
Market Liquidity ◽  
High Frequency Trading ◽  
The Impact

scholarly journals High-frequency trading and networked markets

2021 ◽  
Vol 118 (26) ◽  
pp. e2015573118
Author(s):  
Federico Musciotto ◽  
Jyrki Piilo ◽  
Rosario N. Mantegna
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
Market Liquidity ◽  
High Frequency Trading ◽  
Complex Network Theory ◽  
Market Participants ◽  
Liquidity Provision ◽  
Regulatory Constraints ◽  
Great Heterogeneity ◽  
Trading Decisions

Financial markets have undergone a deep reorganization during the last 20 y. A mixture of technological innovation and regulatory constraints has promoted the diffusion of market fragmentation and high-frequency trading. The new stock market has changed the traditional ecology of market participants and market professionals, and financial markets have evolved into complex sociotechnical institutions characterized by a great heterogeneity in the time scales of market members’ interactions that cover more than eight orders of magnitude. We analyze three different datasets for two highly studied market venues recorded in 2004 to 2006, 2010 to 2011, and 2018. Using methods of complex network theory, we show that transactions between specific couples of market members are systematically and persistently overexpressed or underexpressed. Contemporary stock markets are therefore networked markets where liquidity provision of market members has statistically detectable preferences or avoidances with respect to some market members over time with a degree of persistence that can cover several months. We show a sizable increase in both the number and persistence of networked relationships between market members in most recent years and how technological and regulatory innovations affect the networked nature of the markets. Our study also shows that the portfolio of strategic trading decisions of high-frequency traders has evolved over the years, adding to the liquidity provision other market activities that consume market liquidity.

High-Frequency Financial Econometrics

2014 ◽  
Author(s):  
Yacine Aït-Sahalia ◽  
Jean Jacod
Keyword(s):  
High Frequency ◽  
Practical Importance ◽  
Financial Econometrics ◽  
Trading Strategies ◽  
Financial Data ◽  
Jump Processes ◽  
High Frequency Trading ◽  
Microstructure Noise ◽  
Econometric Methods ◽  
Mathematical Foundations

High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. The book covers the mathematical foundations of stochastic processes, describes the primary characteristics of high-frequency financial data, and presents the asymptotic concepts that their analysis relies on. It also deals with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As the book demonstrates, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. The book approaches high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.

High-Frequency Trading

2011 ◽  
Author(s):  
Peter Gomber ◽  
Björn Arndt ◽  
Marco Lutat ◽  
Tim Elko Uhle
Keyword(s):  
High Frequency ◽  
High Frequency Trading
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