INTRODUCTION II. REGULATING TRADING ENTITIES A. The Economics of Trading B. Self-Regulation and Its Challenges III. THE EVOLUTION OF FINANCIAL MARKET INTERMEDIATION A. The Paperwork Crisis of 1967 B. Stock Market Crash of 1987 C. Recent Financial Crisis of 2007 D. Learning from Crises IV. EMERGING TRADING STRATEGIES A. Black Box Trading: Algorithms B. HFT: The New Trading Frontier C. The Benefits of Innovation D. The Limitations of Innovation V. ALTERNATIVE TRADING VENUES A. Early Fragmentation in Trading Markets B. Modern Developments in Trading Venues 1. The Rise of Dark Pools a. "Lit" vs. Dark Venues b. The Allure of Dark Pools 2. The Perils in Dark Pools VI. REGULATION AND PERSISTENT CHALLENGES A. Early Regulatory Responses B. Prosecution of Predatory Tactics C. Speeding to The Next Crisis: HFT Strategies in Dark Pools 1. Front-Running 2. Hide Not Slide 3. Spoofing 4. Pinging VII. A MODEST PROPOSAL: FOCUSING ON SYSTEMS INTEGRITY A. Regulation SCI B. Responding to Innovation in Lit and Dark Markets VIII. CONCLUSION I. INTRODUCTION
Tales 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 window (8)--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. (13)
Using a high-frequency trading (HFT) strategy known as "spoofing," Sarao entered tens of millions of dollars of orders intended to drive down the price of certain futures contracts. (14) After submitting sell orders, he entered orders to buy the same contracts at artificially depressed prices. (15) Contemporaneously, he cancelled the original sell orders that drove the prices downward before any such orders closed. (16) In an effort to manipulate the market, he submitted orders intending to withdraw the same orders before an exchange or clearinghouse closed the trade. (17)
Sarao never intended to sell, but his sell orders influenced trading across international financial markets. (18) After several years of successfully implementing this strategy before and after the Flash Crash, Sarao generated $50 million in profits. (19) In November of 2016, Sarao pled guilty to one count of wire fraud and one count of "spoofing," a tactic that Sarao employed during the crisis to manipulate the market prices of listed securities.
While regulators continue to disentangle the events of the Flash Crash, the effect of this kind of disruption on markets is indisputably clear. The crash, characterized by high volatility, created a liquidity crisis, a panic among investors regarding the stability of the market and the accuracy of financial product prices. (20) In a period of several minutes, wild automated selling by algorithmic and automated computer trades consumed nearly one trillion U.S. dollars in value from U.S. equity and derivatives markets. (21)
The Flash Crash illustrates two noteworthy concerns. First, a revolution in innovation, in this case automated execution programs and algorithmic computer programs, characterizes modern financial markets. (22) The rapid erosion in liquidity that resulted at least in part from the implementation of innovative trading technology demonstrates the potential for emerging alternatives to disrupt markets. (23)
Coupled with the development of lightning fast, computer-based trading strategies, markets have witnessed marked growth in the number and diversity of trading venues. Fragmentation has intensified competition among trading platforms, exchanges and alternative trading venues in the market for clearing and settlement of securities, and derivatives trades. Electronic communication networks enable market participants to execute transactions at the "speed of light." A "race to zero" has emerged; market participants compete to decrease the time that elapses between the moment that a trader signals an interest to buy or sell a security, commodity or derivative and the moment when an exchange or clearinghouse confirms that the trade is settled. (24)
Second, contemporaneous with these changes, a transformation in the ecosystem of trading venues has engendered grave concerns about market stability. (25) This metamorphosis leaves markets vulnerable to manipulation and perhaps, more disconcertingly, to volatility. Simply stated financial markets are fragile, and when extreme volatility arises in markets, severe consequences for funding liquidity and market operations may follow. The risk of market disruption may lead to an economic downturn or recession and create spillover effects that may impact many segments of the economy. (26)
These concerns regarding market fragility are particularly disconcerting for a class of alternative trading systems (ATSs) colorfully described as "dark pools." The number and size of dark pools rises steadily each year. (27) To date, there are forty dark pools operating in the United States. (28) The increase in number of dark pools operating in financial markets parallels a shift in market trading volume away from conventional securities exchanges to dark pools.
In 2009, dark pools facilitated the execution of 7.2% of equity securities transactions. (29) By 2016, dark pools had captured over 40% of the equity securities trading volume--meaning these entities now facilitate the execution of almost half of listed securities transactions (NMS stocks). (30) In recent years, investigations have revealed that firms employing computer-based high frequency trading (HFT) strategies have gained access to dark pools and that these firms are now preying on investors executing transactions in dark pools. (31)
Because dark pool operators reveal limited--if any--details regarding the identity of participating traders, the substance of their transactions and even the size of hidden transactions their trading platforms are characterized by opacity. (32) Flash Crash investigations suggest that computer-driven or automated trading may significantly influence markets. Noting the potential dominance of dark pools and the opacity that characterizes these venues, commentators increasingly inquire whether it may be necessary to adapt or adopt regulation to respond to the use of innovation and evolving technology in emerging trading venues such as dark pools.
A contested debate has emerged regarding the benefits of regulating HFT trading and the use of HFT trading in dark pools. (33) The debate regarding regulation of dark markets has focused on important issues such as fairness, price discovery, and transparency. Regulators, commentators and scholars have, however, focused too little attention on the cross-market impact of high frequency trading in dark pools.
While a growing body of literature explores the contours of technology and innovation in financial markets, (34) this Article raises critical questions regarding potential concerns that arise as a result of increased competition among trading venues, the sizeable market share captured by ATSs and the noteworthy fragmentation that unregistered and underregulated trading venues engender. This Article contends that technologically enhanced trading in dark pools increases volatility, undermines fairness, and leaves markets vulnerable to catastrophic concerns.
This Article makes three critical contributions. First, this Article contends that innovation in trading transforms markets and trading strategies. Second, no current regulatory framework clearly establishes the approach for addressing the impact of these innovative changes in the context of unregulated or lightly...
Regulating Innovation: High Frequency Trading in Dark Pools.
|Author:||Johnson, Kristin N.|
|Position:||What Happens in the Dark: An Exploration of Dark Pools and High Frequency Trading|
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COPYRIGHT GALE, Cengage Learning. All rights reserved.
COPYRIGHT GALE, Cengage Learning. All rights reserved.