A Dysfunctional Role of High Frequency Trading in Electronic Markets

2011 ◽  
Author(s):  
Robert A. Jarrow ◽  
Philip Protter
Keyword(s):  
High Frequency ◽  
Electronic Markets ◽  
High Frequency Trading

A DYSFUNCTIONAL ROLE OF HIGH FREQUENCY TRADING IN ELECTRONIC MARKETS

2012 ◽  
Vol 15 (03) ◽  
pp. 1250022 ◽  
Author(s):  
ROBERT A. JARROW ◽  
PHILIP PROTTER
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
Electronic Markets ◽  
High Frequency Trading ◽  
Common Signal

This paper shows that high frequency trading may play a dysfunctional role in financial markets. Contrary to arbitrageurs who make financial markets more efficient by taking advantage of and thereby eliminating mispricings, high frequency traders can create a mispricing that they unknowingly exploit to the disadvantage of ordinary investors. This mispricing is generated by the collective and independent actions of high frequency traders, coordinated via the observation of a common signal.

scholarly journals DOES SPEED MATTER? THE ROLE OF HIGH‐FREQUENCY TRADING FOR ORDER BOOK RESILIENCY

2020 ◽  
Vol 43 (4) ◽  
pp. 933-964
Author(s):  
Benjamin Clapham ◽  
Martin Haferkorn ◽  
Kai Zimmermann
Keyword(s):  
High Frequency ◽  
High Frequency Trading ◽  
Order Book

scholarly journals Large Tick Assets: Implicit Spread and Optimal Tick Size

2015 ◽  
Vol 01 (01) ◽  
pp. 1550003 ◽  
Author(s):  
Khalil Dayri ◽  
Mathieu Rosenbaum
Keyword(s):  
High Frequency ◽  
High Frequency Trading ◽  
Microstructural Properties ◽  
Relevant Market ◽  
Tick Size ◽  
Effective Spread

In this work, we provide a framework linking microstructural properties of an asset to the tick value of the exchange. In particular, we bring to light a quantity, referred to as implicit spread, playing the role of spread for large tick assets, for which the effective spread is almost always equal to one tick. The relevance of this new parameter is shown both empirically and theoretically. This implicit spread allows us to quantify the tick sizes of large tick assets and to define a notion of optimal tick size. Moreover, our results open the possibility of forecasting the behavior of relevant market quantities after a change in the tick value and to give a way to modify it in order to reach an optimal tick size. Thus, we provide a crucial tool for regulators and trading platforms in the context of high frequency trading.

scholarly journals A material political economy: Automated Trading Desk and price prediction in high-frequency trading

2016 ◽  
Vol 47 (2) ◽  
pp. 172-194 ◽  
Author(s):  
Donald MacKenzie
Keyword(s):  
Political Economy ◽  
Financial Markets ◽  
High Frequency ◽  
Share Price ◽  
High Frequency Trading ◽  
Historical Study ◽  
Price Changes ◽  
Price Prediction ◽  
Political Economic

This article contains the first detailed historical study of one of the new high-frequency trading (HFT) firms that have transformed many of the world’s financial markets. The study, of Automated Trading Desk (ATD), one of the earliest and most important such firms, focuses on how ATD’s algorithms predicted share price changes. The article argues that political-economic struggles are integral to the existence of some of the ‘pockets’ of predictable structure in the otherwise random movements of prices, to the availability of the data that allow algorithms to identify these pockets, and to the capacity of algorithms to use these predictions to trade profitably. The article also examines the role of HFT algorithms such as ATD’s in the epochal, fiercely contested shift in US share trading from ‘fixed-role’ markets towards ‘all-to-all’ markets.

A Framework for Responsive Market Regulation

2018 ◽  
pp. 332-358
Author(s):  
Timothy Baikie ◽  
Tracey Stern ◽  
Susan Greenglass ◽  
Maureen Jensen
Keyword(s):  
Capital Markets ◽  
High Frequency ◽  
High Frequency Trading ◽  
Market Regulation ◽  
Business Decisions ◽  
Regulatory Climate ◽  
Recent Developments ◽  
The Impact ◽  
Regulatory Landscape

This chapter submits that a regulator’s raison d’être is not simply to react to market issues but to be proactive and to follow and to understand the changes and the business decisions in the market. Regulators must be able to change and foster a responsive regulatory climate that allows innovation to occur, while ensuring that core principles such as investor protection are preserved and that the impact of any change is monitored. To that end, the chapter highlights the role of the Ontario Securities Commission in the Canadian regulatory landscape, and details how it has addressed the multitude of challenges posed by recent developments in Canadian capital markets, including the growth in dark liquidity and the emergence of high frequency trading.

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.

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