MiFID II: Regulating High Frequency Trading, Other Forms of Algorithmic Trading and Direct Electronic Market Access

2017 ◽  
Author(s):  
Danny Busch
Keyword(s):  
High Frequency ◽  
Market Access ◽  
High Frequency Trading ◽  
Algorithmic Trading ◽  
Electronic Market

High-Frequency Trading and its Role in Fragmented Markets

2017 ◽  
Vol 32 (3) ◽  
pp. 283-296 ◽  
Author(s):  
Martin Haferkorn
Keyword(s):  
Market Efficiency ◽  
High Frequency ◽  
Efficient Market Hypothesis ◽  
High Frequency Trading ◽  
Electronic Market ◽  
Coordination Costs ◽  
Major Transformation ◽  
Securities Trading ◽  
Term Analysis

Securities trading underwent a major transformation within the last decade. This transformation was mainly driven by the regulatory induced fragmentation and by the increase of high-frequency trading (HFT). On the basis of the electronic market hypothesis, which poses that coordination costs decline when markets become automated, and the efficient market hypothesis in its semi-strong form, we study the effect of HFT on market efficiency in the European fragmented market landscape. In doing so, we further incorporate the realm of financialization, which criticizes the increase in transaction speed. By conducting a long-term analysis of CAC 40 securities, we find that HFT increases market efficiency by leveling midpoints between Euronext Paris and Bats Chi-X Europe. On the basis of a crosscountry event study, we analyze the effect of the German HFT Act. We observe that the midpoint dispersion of blue chip securities between the two leading venues Deutsche Boerse and Bats Chi-X Europe increased. We conclude that HFT increases market efficiency in the European market landscape by transmitting information between distant markets.

scholarly journals The Flash Crash: High-Frequency Trading in an Electronic Market

2017 ◽  
Vol 72 (3) ◽  
pp. 967-998 ◽  
Author(s):  
ANDREI KIRILENKO ◽  
ALBERT S. KYLE ◽  
MEHRDAD SAMADI ◽  
TUGKAN TUZUN
Keyword(s):  
High Frequency ◽  
High Frequency Trading ◽  
Electronic Market ◽  
Flash Crash

The Regulatory, Technology and Market ‘Dark Arts Trilogy’ of High Frequency Trading: A Research Agenda

2017 ◽  
Vol 32 (2) ◽  
pp. 111-126 ◽  
Author(s):  
Wendy L. Currie ◽  
Jonathan J. M. Seddon
Keyword(s):  
Information Systems ◽  
Financial Markets ◽  
Empirical Data ◽  
High Frequency ◽  
Research Agenda ◽  
High Frequency Trading ◽  
Algorithmic Trading ◽  
Flash Crash ◽  
Financial Trading ◽  
Dow Jones Industrial Average

Computerization has transformed financial markets with high frequency trading displacing human activity with proprietary algorithms to lower latency, reduce intermediary costs, enhance liquidity and increase transaction speed. Following the “Flash Crash” of 2010 which saw the Dow Jones Industrial Average plunge 1000 points within minutes, high frequency trading has come under the radar of multi-jurisdictional regulators. Combining a review of the extant literature on high frequency trading with empirical data from interviews with financial traders, computer experts and regulators, we develop concepts of regulatory adaptation, technology asymmetry and market ambiguity to illustrate the ‘dark art’ of high frequency trading. Findings show high frequency trading is a multi-faceted, complex and secretive practice. It is implicated in market events, but correlation does not imply causation, as isolating causal mechanisms from interconnected automated financial trading is highly challenging for regulators who seek to monitor algorithmic trading across multiple jurisdictions. This article provides information systems researchers with a set of conceptual tools for analysing high frequency trading.

Part III Trading, 17 Algorithmic Trading and High-Frequency Trading (HFT)

2017 ◽  
Author(s):  
Conac Pierre-Henri
Keyword(s):  
High Frequency ◽  
High Frequency Trading ◽  
Algorithmic Trading ◽  
Technical Approach ◽  
Great Cost ◽  
Scarce Resources ◽  
Flash Crash ◽  
Market Abuse ◽  
Front Running ◽  
Do So

This chapter analyses the MiFID II rules on algorithmic trading (AT), including high-frequency trading (HFT). The author argues that AT raises serious issues of volatility and systemic risk, and HFT issues of systematic front-running of investors. However, opinions are divided on the benefits and risks of these techniques, especially HFT. MiFID II takes a technical approach mostly focused on prevention of a repeat of the 2010 ‘Flash Crash’ with provisions on market abuse. The ESMA 2012 Guidelines remain the most effective regulation to frame the development of HFT, able to tackle market developments with relative speed. However, with implementation of the directive still far away, prosecution of market abuse among HFT traders by legislators and supervisors could lead to a de facto ban of HFT in some Member States. However, the author argues that supervisors would need to allocate scarce resources to it, at great cost, and only the most motivated supervisors will do so.

The Flash Crash: The Impact of High Frequency Trading on an Electronic Market

2011 ◽  
Author(s):  
Andrei A. Kirilenko ◽  
Albert S. Kyle ◽  
Mehrdad Samadi ◽  
Tugkan Tuzun
Keyword(s):  
High Frequency ◽  
High Frequency Trading ◽  
Electronic Market ◽  
Flash Crash ◽  
The Impact

scholarly journals On studying algorithms ethnographically: Making sense of objects of ignorance

Organization ◽  
2018 ◽  
Vol 26 (4) ◽  
pp. 598-617 ◽  
Author(s):  
Ann-Christina Lange ◽  
Marc Lenglet ◽  
Robert Seyfert
Keyword(s):  
Decision Making ◽  
High Frequency ◽  
Organizational Politics ◽  
High Frequency Trading ◽  
Algorithmic Trading ◽  
Michel Serres ◽  
Making Sense ◽  
Dynamic Relationship ◽  
Organizational Ethnography ◽  
Automated Decision Making

In this article, we make sense of financial algorithms as new objects of concern for organizational ethnography. We conceive of algorithms as ‘objects of ignorance’ jeopardizing traditional ethnography from the perspective of its categories and methods. We investigate the organizational politics taking place within high-frequency trading – a sub-field of algorithmic trading where automated decision-making without human direction has reached a peak, and show that financial algorithms raise particular epistemic and methodological challenges for practitioners and ethnographers alike. Consequently, we develop a typology for various interpretations of algorithms as ethnographic objects, accounting for their structural ignorance and shedding light on a continuum of the changing human-machine/trader-algorithm relation. To this end, we use the concepts of ‘quasi-object’ and ‘quasi-subject’ as developed by Michel Serres, and make the point that in order to study financial algorithms ethnographically, we need to think anew the dynamic relationship they embody, and acknowledge their constitutive heterogeneity.

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