Academic journal article Journal of Corporation Law

Regulating Innovation: High Frequency Trading in Dark Pools

Academic journal article Journal of Corporation Law

Regulating Innovation: High Frequency Trading in Dark Pools

Article excerpt

I. Introduction.835

II. Regulating Trading Entities.839

A. The Economics of Trading.839

B. Self-Regulation and Its Challenges.841

III. The Evolution of Financial Market Intermediation.845

A. The Paperwork Crisis of 1967.846

B. Stock Market Crash of1987.848

C. Recent Financial Crisis of2007.850

D. Learning from Crises.853

IV. Emerging trading Strategies.854

A. Black Box Trading: Algorithms.855

B. HFT: The New Trading Frontier.856

C. The Benefits of Innovation.858

D. The Limitations of Innovation.858

V. Alternative Trading Venues.861

A. Early Fragmentation in Trading Markets.862

B. Modern Developments in Trading Venues.863

1. The Rise of Dark Pools.864

a. "Lit" vs. Dark Venues.864

b. The Allure of Dark Pools.865

2. The Perils in Dark Pools.866

VI. Regulation and Persistent Challenges.868

A. Early Regulatory Responses.869

B. Prosecution of Predatory Tactics.873

C. Speeding to The Next Crisis: HFT Strategies in Dark Pools.876

1. Front-Running.876

2. Hide Not Slide.877

3. Spoofing.878

4. Pinging.879

VII. A Modest Proposal: Focusing on Systems Integrity.880

A. Regulation SCI.881

B. Responding to Innovation in Lit and Dark Markets.884

VIII. Conclusion.886


Talcs of high speed trading increasingly captivate scholars, commentators, market participants, and regulators who are thoughtful about the influence of technological innovation in financial markets.1 These flashy stories of fast-paced automated trading tactics have, in many instances, overshadowed the problematic perils associated with computer-based trading.

On the afternoon of May 6,2010, prices of securities and derivatives fell almost 1,000 points in minutes-the deepest single event dip in more than one hundred years in U.S. financial markets.2 While markets quickly recovered, records reflected that the shock affected almost 8,000 exchange traded funds (ETFs) and individual equity securities.3 With markets already roiling that day due to unsettling news about the European debt crisis, U.S. equity markets experienced a "Flash Crash," characterized by rapid and dramatic financial product price fluctuations.4

Traders executed more than 20,000 trades involving 300 different stocks, ETFs, and options traded at prices that diverged significantly from their pre-crash value.5 Shares of Sotheby's (the famous British auction house) increased from $34 to $99,999.99.6 The prices for other financial products declined by 5%, 10%, or even 15% before recovering most, if not all, of their losses.7 The series of events related to the crash occurred in just twenty minutes-an extraordinarily short window8-causing dramatic automated selling by algorithmic trading groups that led to nearly one billion dollars in losses for U.S. equity markets.9

Following the Flash Crash, the Federal Bureau of Investigations and financial market regulators spent years deconstructing the events that disrupted markets.10 Reports regarding the triggering events are at best muddled; explanations directly contradict market accounts.11 High frequency trading practices, however, appeared to be a common factor in almost all explanations of the Crash.

Initially, the Securities Exchange Commission (SEC) and the Commodities Future Trading Commission (CFTC) concluded that an automated algorithm blindly deployed trade orders for a single institutional investor (Waddell & Reed) rapidly executing the sale of 75,000 E-Mini S&P 500 future contracts (valued at approximately $4.1 billion) and triggering the ephemeral crash.12 Several years later, in 2015, the Department of Justice and the CFTC investigations revealed that a rogue London-based futures trader-Navinder Singh Sarao-had manipulated the E-Mini S&P 500 by using an algorithm to flood the Chicago Mercantile Exchange (CME) with sell orders for E-Mini S&P 500 stocks. …

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