scholarly journals Prudential supervisory disclosure (PSD) with supervisory technology (SupTech): lessons from a FinTech crisis

2021 ◽  
Author(s):  
Stefan Zeranski ◽  
Ibrahim E. Sancak
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
Market Value ◽  
Financial Supervision ◽  
Algorithmic Trading ◽  
Rapid Decline ◽  
Flash Crash ◽  
Market Participants ◽  
History Of ◽  
Financial Supervisors

AbstractThe U.S. financial markets faced an unprecedented rapid decline and recovery on May 6, 2010, known as the May 6 flash crash. Roughly one trillion $ market value in less than thirty minutes vanished with the biggest one-day point decline in the history of the DJIA at the time. Since the market events took place in electronic markets, and algorithmic trading and high-frequency trading, parts of FinTech, played significant roles, we handle the May 6 flash crash from the FinTech, SupTech, and financial supervision perspectives. With the flashback method, we analyzed the reactions of market participants, media, and two financial supervisors, the SEC, and the CFTC, to the market crash. We find that the technological imbalance between financial markets or institutions and their supervisors drove the markets in uncertainty, hence in a fear and panic environment. Since the imbalance has not diminished yet, the same risks still exist. As a remedy, we introduce a new concept and model with a well-functioning SupTech system to cope with the May 6 type FinTech crises.

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.

scholarly journals What is a 'Real' Transaction? Infrastructures, relations and Spoofing in High-Frequency Trading

2016 ◽  
Author(s):  
Juan Pablo Pardo Guerra
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
High Frequency Trading ◽  
Market Behavior ◽  
Digital Platforms ◽  
Market Participants

Although an old and rare practice, spoofing has re-emerged as a subject ofintense debate within modern financial markets. An activity entailing thefraudulent creation of orders to buy and sell securities with the purposeof manipulating the market, spoofing highlights the multiple and complexmoral valences of contemporary, automated, finance. In this paper, I studyspoofing as an opportunity to understand markets and their relations ofexchange. In particular, by extending Weberian metaphors of markets asmoral and organizational communities, I examine how the courts and marketparticipants distinguish the ‘false’ transactions of spoofing from the‘real’ exchanges of 'normal' market behavior. Combining Marilyn Strathern’stheoretical discussion of the anthropological relation with recentliteratures on infrastructures and markets, I argue that the perceivedreality of transactions is a product of how novel forms of economicknowledge are able to make sense of ‘taken for granted’ behavioral patternswithin digital platforms of market action. The intent that constitutes‘real’ trades is therefore a product of how market participants, economicexperts and the courts interpret the operational underbelly of markets andthe relations that they produce.

High-Frequency Trading and Conflict in the Financial Markets

2017 ◽  
Vol 32 (3) ◽  
pp. 270-282 ◽  
Author(s):  
Ricky Cooper ◽  
Jonathan Seddon ◽  
Ben Van Vliet
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
High Frequency Trading ◽  
Market Makers ◽  
Market Participants ◽  
Software Vendor ◽  
Traditional Market ◽  
Recent Developments ◽  
The Way

The last few decades has seen an ever-increasing growth in the way activities are productized and associated with a financial cost. This phenomenon, termed financialization, spans all areas including government, finance, health and manufacturing. Recent developments within finance over that past decade have radically altered the way trading occurs. This paper analyses high-frequency trading (HFT) as a necessary component of the infrastructure that makes financialization possible. Through interviews with HFT firms, a software vendor, regulators and banks, the effects of HFT on market efficiency, and its impact on costs to long-term investors are explored. This paper contributes to the literature by exploring the conflict that exists between HFT and traditional market makers in today's fragmented markets. This paper argues that society should be unconcerned with this conflict and should instead focus on the effects these participants have on the long-term investors, for whom the markets ultimately exist. In order to facilitate the best outcomes, regulation should be simple, aimed at keeping participants’ behavior stable, and the interactions among them transparent and straightforward. Financialization and HFT are inextricably linked, and society is best served by ensuring that the creative energy of these market participants is directed on providing liquidity and removing inefficiencies.

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.

Optimal Algorithmic Trading Strategy with the Price Appreciation Cost

2014 ◽  
Vol 631-632 ◽  
pp. 62-65
Author(s):  
Ru Zhen Yan ◽  
Ping Li ◽  
Yong Zeng
Keyword(s):  
Financial Markets ◽  
Transaction Cost ◽  
High Frequency ◽  
Opportunity Cost ◽  
Trading Strategy ◽  
Price Impact ◽  
Algorithmic Trading ◽  
Optimal Trading ◽  
Price Appreciation ◽  
The Cost

Financial markets has witnessed an explosion of algorithmic trading strategy which can help traders especially involved in high-frequency trading efficiently reduce invisible transaction cost. The VWAP strategy usually used by traders can only decrease the cost of price impact by breaking block order into small pieces. However, the behavior of such order splitting may result in inevitable opportunity cost as well as price appreciation. This paper establishes a new algorithmic trading strategy to minimize total transaction costs including price impact, opportunity cost and price appreciation. The results show that the total transaction cost of this optimal trading strategy is lower than VWAP strategy.

FinTech and Stock Market Behaviors

2019 ◽  
pp. 170-205
Author(s):  
Taner Sekmen ◽  
Mercan Hatipoglu
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
High Frequency ◽  
Stock Return ◽  
Garch Models ◽  
Algorithmic Trading ◽  
Risk Return ◽  
The Past ◽  
Volatility Asymmetry ◽  
Technological Developments

This chapter examines the effects of high-frequency trading (HFT) and algorithmic trading (AT) activities, which represent important technological developments in financial markets in the past two decades, on Borsa Istanbul in terms of volatility. To clarify stock market behaviors in terms of volatility, asymmetry, and risk return after the BISTECH transition, the GJR-GARCH-in-Mean and I-GARCH models were used. The dataset consists of the daily stock return series of the main and sub-sector indexes of Borsa Istanbul, covering the period from October 24, 2012 to June 1, 2018. Although there are mixed results for the sub-indexes, it is observed that in the post-BISTECH period, volatility increases significantly in the BIST 100 and BIST 30 indexes, where AT and HFT activities are used more frequently. In particular, the duration of volatility returns to average after shock increases about seven times for BIST 100 and about eight times for the BIST 30 in the post-BISTECH period. Overall, the results indicate that AC and HFT activities may have disruptive effects on financial markets.

scholarly journals Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents

2013 ◽  
Vol 27 (2) ◽  
pp. 51-72 ◽  
Author(s):  
Andrei A Kirilenko ◽  
Andrew W Lo
Keyword(s):  
Financial Markets ◽  
Financial Stability ◽  
Financial Regulation ◽  
Economic Incentives ◽  
Unintended Consequences ◽  
Algorithmic Trading ◽  
Market Participants ◽  
Financial Regulatory ◽  
Financial Technology ◽  
Key Innovations

Financial markets have undergone a remarkable transformation over the past two decades due to advances in technology. These advances include faster and cheaper computers, greater connectivity among market participants, and perhaps most important of all, more sophisticated trading algorithms. The benefits of such financial technology are evident: lower transactions costs, faster executions, and greater volume of trades. However, like any technology, trading technology has unintended consequences. In this paper, we review key innovations in trading technology starting with portfolio optimization in the 1950s and ending with high-frequency trading in the late 2000s, as well as opportunities, challenges, and economic incentives that accompanied these developments. We also discuss potential threats to financial stability created or facilitated by algorithmic trading and propose “Financial Regulation 2.0,” a set of design principles for bringing the current financial regulatory framework into the Digital Age.

A Taxonomy of Financial Market Manipulations: Establishing Trust and Market Integrity in the Financialized Economy through Automated Fraud Detection

2017 ◽  
Vol 32 (3) ◽  
pp. 251-269 ◽  
Author(s):  
Michael Siering ◽  
Benjamin Clapham ◽  
Oliver Engel ◽  
Peter Gomber
Keyword(s):  
Financial Markets ◽  
Financial Market ◽  
High Frequency ◽  
Fraud Detection ◽  
Vast Number ◽  
Market Surveillance ◽  
Market Abuse ◽  
Market Participants ◽  
Speculative Trading

Financial market manipulations represent a major threat to trust and market integrity in capital markets. Manipulations contribute to mispricing, market imperfections and an increase in transaction costs for market participants and in costs of capital for issuers. Manipulations are facilitated by increased transaction velocity, speculative trading and abusive usage of new trading technologies, i.e., they are directly linked to financial sector changes that drive financialization. Research at the intersection of financialization and IS might support regulatory authorities and market operators in improving market surveillance and helping to detect fraudulent activities. However, confusing terminology is prevalent on financial markets with respect to different manipulation techniques and their characteristics, which hampers efficient fraud detection. Furthermore, recognizing manipulations is challenging given the large number of information sources and the vast number of trades occurring not least because of high-frequency traders. Therefore, automated market surveillance tools require a comprehensive taxonomy of financial market manipulations as a basis for appropriate configuration. Based on a cluster analysis of SEC litigation releases, a review of the latest market abuse regulation and academic studies, we develop a taxonomy of manipulations that structures and details existing manipulation techniques and reveals how these techniques differ along several dimensions. In a case study, we show how the taxonomy can be utilized to guide the development of appropriate decision support systems for fraud detection.

A Case Study in Regulatory Arbitrage and Information Asymmetry

2018 ◽  
pp. 28-60
Author(s):  
Haim Bodek
Keyword(s):  
Information Asymmetry ◽  
High Frequency ◽  
Algorithmic Trading ◽  
Regulatory Arbitrage ◽  
The Public ◽  
Market Participants ◽  
Order Types ◽  
Exchange Markets ◽  
Special Order

While much of the public debate surrounding high frequency trading (HFT) and algorithmic trading has centred on speed, less has been said about the circumvention of regulation via special order types—complex and often non-transparent ways for high frequency traders to interact with exchange markets and other trading venues, allowing them to achieve a favourable execution position at the expense of other market participants. This chapter documents the special order types used by high frequency traders, the absence of adequate disclosure by exchanges, and the problematic interaction between order types designed to accommodate HFT strategies and the order types typically employed by public investors and agency brokers.

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.

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