Fragility of Financial Markets: The Italian Debt Not-So-Flash Crash

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.

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An Essay on Financial Information in the Era of Computerization

Journal of Information Technology ◽

10.1057/s41265-016-0027-1 ◽

2018 ◽

Vol 33 (1) ◽

pp. 9-18 ◽

Cited By ~ 4

Author(s):

Christophe Schinckus

Keyword(s):

Financial Markets ◽

Financial Economics ◽

Statistical Approach ◽

Technical Analysis ◽

Financial Information ◽

Fundamental Analysis ◽

Flash Crash ◽

Recent Emergence ◽

Concept Of Information ◽

Financial Prices

This article deals with the increasing computerization of the financial markets and the consequences of such process on our ability to collect information about financial prices. The concept of information is at the heart of financial economics simply because this notion is a precondition for all investments. Since financial prices characterize an agreement on a transaction between two counterparties, they understandably became a key informational indicator for decision. This article will analyse the increasing computerization of financial sphere by discussing the recent emergence of what is called a “flash crash” and its impact on the traditional ways of collecting information in finance (technical analysis, fundamental analysis and statistical approach). I argue that the growing computerization of financial markets generated a “hyper-reality” in which financial prices do not refer to “something” anymore implying a revision of our usual way of defining/using the notion of information.

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Understanding the Flash Crash – state of the art

Studies in Economics and Finance ◽

10.1108/sef-07-2018-0223 ◽

2019 ◽

Vol 36 (4) ◽

pp. 465-491 ◽

Cited By ~ 1

Author(s):

Gianluca Piero Maria Virgilio

Keyword(s):

Financial Markets ◽

Design Methodology ◽

State Of The Art ◽

Feedback Loops ◽

Policy Implications ◽

Micro Structure ◽

Content Type ◽

Flash Crash ◽

Current State ◽

Stop Loss

Purpose The purpose of this paper is to provide the current state of knowledge about the Flash Crash. It has been one of the remarkable events of the decade and its causes are still a matter of debate. Design/methodology/approach This paper reviews the literature since the early days to most recent findings, and critically compares the most important hypotheses about the possible causes of the crisis. Findings Among the causes of the Flash Crash, the literature has propsed the following: a large selling program triggering the sales wave, small but not negligible delays suffered by the exchange computers, the micro-structure of the financial markets, the price fall leading to margin cover and forced sales, some types of feedback loops leading to downward price spiral, stop-loss orders coupled with scarce liquidity that triggered price reduction. On its turn leading to further stop-loss activation, the use of Intermarket Sweep Orders, that is, orders that sacrificed search for the best price to speed of execution, and dumb algorithms. Originality/value The results of the previous section are condensed in a set of policy implications and recommendations.

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

International Journal of Disclosure and Governance ◽

10.1057/s41310-021-00111-7 ◽

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.

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Information Technology and Financial Markets

Information Systems for Global Financial Markets - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-61350-162-7.ch001 ◽

2011 ◽

pp. 1-18

Author(s):

Donald Crooks ◽

John Slayton ◽

John Burbridge

Keyword(s):

Information Technology ◽

Financial Crisis ◽

Financial Markets ◽

Information And Communication Technologies ◽

Communication Technologies ◽

Mortgage Loan ◽

Flash Crash ◽

The World ◽

Information And Communication ◽

The U.S

Much has been written about information technology and its role in reinventing financial markets. Today’s markets are truly global, and the interconnectedness is the result of information and communication technologies (ICT) providing the necessary infrastructure. A financial crisis in any part of the world can cause widespread disruptions due to this interconnectedness. Clearly, the Asian crisis in the late 1990s, the sub-prime mortgage loan issues in 2006 and 2007, and the problems occurring in Greece and the U.S. “Flash Crash” in 2010 were exacerbated by the ability of technology to allow financial markets to instantaneously respond in a negative fashion.

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Algorithmic Trading in Practice

10.1093/oxfordhb/9780199844371.013.12 ◽

2018 ◽

Cited By ~ 1

Author(s):

Peter Gomber ◽

Kai Zimmermann

Keyword(s):

Financial Markets ◽

Value Chain ◽

Trading Strategies ◽

Algorithmic Trading ◽

Securities Markets ◽

Computer Algorithms ◽

Flash Crash ◽

Time Savings ◽

Securities Trading ◽

The U.S

The use of computer algorithms in securities trading, or algorithmic trading, has become a central factor in modern financial markets. The desire for cost and time savings within the trading industry spurred buy side as well as sell side institutions to implement algorithmic services along the entire securities trading value chain. This chapter encompasses this algorithmic evolution, highlighting key cornerstones in it development discussing main trading strategies, and summarizing implications for overall securities markets quality. In addition, it touches on the contribution of algorithmic trading to the recent market turmoil, the U.S. Flash Crash, including the discussions of potential solutions for assuring market reliability and integrity.

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