The May 6, 2010, flash crash, [1] [2] [3] also known as the crash of 2:45 or simply the flash crash, was a United States trillion-dollar [4] flash crash (a type of stock market crash) which started at 2:32 p.m. EDT and lasted for approximately 36 minutes. [5]
Stock indices, such as the S&P 500, Dow Jones Industrial Average and Nasdaq Composite, collapsed and rebounded very rapidly. [5] The Dow Jones Industrial Average had its second biggest intraday point decline (from the opening) up to that point, [5] plunging 998.5 points (about 9%), most within minutes, only to recover a large part of the loss. [6] [7] It was also the second-largest intraday point swing (difference between intraday high and intraday low) up to that point, at 1,010.14 points. [5] [6] [8] [9] The prices of stocks, stock index futures, options and exchange-traded funds (ETFs) were volatile, thus trading volume spiked. [5] : 3 A CFTC 2014 report described it as one of the most turbulent periods in the history of financial markets. [5]
New regulations put in place following the 2010 flash crash [10] proved to be inadequate to protect investors in the August 24, 2015, flash crash — "when the price of many ETFs appeared to come unhinged from their underlying value" [10] — and ETFs were subsequently put under greater scrutiny by regulators and investors. [10]
On April 21, 2015, nearly five years after the incident, the U.S. Department of Justice laid 22 criminal counts, including fraud and market manipulation against Navinder Singh Sarao, a British Indian financial trader. Among the charges included was the use of spoofing algorithms; just prior to the flash crash, he placed orders for thousands of E-mini S&P 500 stock index futures contracts which he planned on canceling later. [11] These orders amounting to about "$200 million worth of bets that the market would fall" were "replaced or modified 19,000 times" before they were canceled. [11] Spoofing, layering, and front running are now banned. [4]
The Commodity Futures Trading Commission (CFTC) investigation concluded that Sarao "was at least significantly responsible for the order imbalances" in the derivatives market which affected stock markets and exacerbated the flash crash. [11] Sarao began his alleged market manipulation in 2009 with commercially available trading software whose code he modified "so he could rapidly place and cancel orders automatically". [11] Traders Magazine journalist, John Bates, argued that blaming a 36-year-old small-time trader who worked from his parents' modest stucco house in suburban west London [11] for sparking a trillion-dollar stock market crash is "a little bit like blaming lightning for starting a fire" and that the investigation was lengthened because regulators used "bicycles to try and catch Ferraris". Furthermore, he concluded that by April 2015, traders can still manipulate and impact markets in spite of regulators and banks' new, improved monitoring of automated trade systems. [4]
In May 2014, a CFTC report concluded that high-frequency traders "did not cause the Flash Crash, but contributed to it by demanding immediacy ahead of other market participants". [5]
Some recent peer-reviewed research shows that flash crashes are not isolated occurrences, but have occurred quite often. Gao and Mizrach studied US equities over the period of 1993–2011. They show that breakdowns in market quality (such as flash crashes) have occurred in every year they examined and that, apart from the financial crisis, such problems have declined since the introduction of Reg NMS. They also show that 2010, while infamous for the flash crash, was not a year with an inordinate number of breakdowns in market quality. [12]
On May 6, 2010, U.S. stock markets opened and the Dow was down, and trended that way for most of the day on worries about the debt crisis in Greece. At 2:42 p.m., with the Dow down more than 300 points for the day, the equity market began to fall rapidly, dropping an additional 600 points in 5 minutes for a loss of nearly 1,000 points for the day by 2:47 p.m. Twenty minutes later, by 3:07 p.m., the market had regained most of the 600-point drop. [13] : 1 At the time of the flash crash, in May 2010, high-frequency traders were taking advantage of unintended consequences of the consolidation of the U.S. financial regulations into Regulation NMS, [4] [14] designed to modernize and strengthen the United States National Market System for equity securities. [15] : 641 The Reg NMS, promulgated and described by the United States Securities and Exchange Commission, was intended to assure that investors received the best price executions for their orders by encouraging competition in the marketplace, but created attractive new opportunities for high-frequency-traders. Activities such as spoofing, layering and front running were banned by 2015. [16] This rule was designed to give investors the best possible price when dealing in stocks, even if that price was not on the exchange that received the order. [17] : 171
At first, while the regulatory agencies and the United States Congress announced investigations into the crash, [18] no specific reason for the 600-point plunge was identified. Investigators focused on a number of possible causes, including a confluence of computer-automated trades, or possibly an error by human traders. By the first weekend, regulators had discounted the possibility of trader error and focused on automated trades conducted on exchanges other than the NYSE. However, CME Group, a large futures exchange, stated that, insofar as stock index futures traded on CME Group were concerned, its investigation found no evidence for this, or that high-frequency trading played a role, and in fact concluded that automated trading had contributed to market stability during the period of the crash. [19] Others speculate that an intermarket sweep order may have played a role in triggering the crash. [20]
Several plausible theories were put forward to explain the plunge.
On September 30, 2010, after almost five months of investigations led by Gregg E. Berman, [41] [42] the U.S. Securities and Exchange Commission (SEC) and the Commodity Futures Trading Commission (CFTC) issued a joint report titled "Findings Regarding the Market Events of May 6, 2010" identifying the sequence of events leading to the flash crash. [43]
The joint 2010 report "portrayed a market so fragmented and fragile that a single large trade could send stocks into a sudden spiral", [25] and detailed how a large mutual fund firm selling an unusually large number of E-Mini S&P contracts first exhausted available buyers, and then how high-frequency traders (HFT) started aggressively selling, accelerating the effect of the mutual fund's selling and contributing to the sharp price declines that day. [44] [25]
The SEC and CFTC joint 2010 report itself says that "May 6 started as an unusually turbulent day for the markets" and that by the early afternoon "broadly negative market sentiment was already affecting an increase in the price volatility of some individual securities". At 2:32 p.m. (EDT), against a "backdrop of unusually high volatility and thinning liquidity" that day, a large fundamental trader (known to be Waddell & Reed Financial Inc. [25] ) "initiated a sell program to sell a total of 75,000 E-Mini S&P contracts (valued at approximately $4.1 billion) as a hedge to an existing equity position". The report says that this was an unusually large position and that the computer algorithm the trader used to trade the position was set to "target an execution rate set to 9% of the trading volume calculated over the previous minute, but without regard to price or time". [43]
As the large seller's trades were executed in the futures market, buyers included high-frequency trading firms—trading firms that specialize in high-speed trading and rarely hold on to any given position for very long—and within minutes these high-frequency trading firms started trying to sell the long futures contracts they had just picked up from the mutual fund. [25] The Wall Street Journal quoted the joint report, "'HFTs [then] began to quickly buy and then resell contracts to each other—generating a 'hot-potato' volume effect as the same positions were passed rapidly back and forth.'" [25] The combined sales by the large seller and high-frequency firms quickly drove "the E-Mini price down 3% in just four minutes". [25]
From the SEC/CFTC report: [43]
The combined selling pressure from the sell algorithm, HFTs, and other traders drove the price of the E-Mini S&P 500 down approximately 3% in just four minutes from the beginning of 2:41 p.m. through the end of 2:44 p.m. During this same time cross-market arbitrageurs who did buy the E-Mini S&P 500, simultaneously sold equivalent amounts in the equities markets, driving the price of SPY (an exchange-traded fund which represents the S&P 500 index) also down approximately 3%. Still lacking sufficient demand from fundamental buyers or cross-market arbitrageurs, HFTs began to quickly buy and then resell contracts to each other—generating a “hot-potato” volume effect as the same positions were rapidly passed back and forth. Between 2:45:13 and 2:45:27, HFTs traded over 27,000 contracts, which accounted for about 49 percent of the total trading volume, while buying only about 200 additional contracts net.
As prices in the futures market fell, there was a spillover into the equities markets. The computer systems used by most high-frequency trading firms to keep track of market activity decided to pause trading, and those firms then scaled back their trading or withdrew from the markets altogether. [45]
The New York Times then noted, "Automatic computerized traders on the stock market shut down as they detected the sharp rise in buying and selling". [27] As computerized high-frequency traders exited the stock market, the resulting lack of liquidity "caused shares of some prominent companies like Procter & Gamble and Accenture to trade down as low as a penny or as high as $100,000". [27] These extreme prices also resulted from "market internalizers", [46] [47] [48] firms that usually trade with customer orders from their own inventory instead of sending those orders to exchanges, "routing 'most, if not all,' retail orders to the public markets—a flood of unusual selling pressure that sucked up more dwindling liquidity". [28]
While some firms exited the market, firms that remained in the market exacerbated price declines because they "'escalated their aggressive selling' during the downdraft". [25] High-frequency firms during the crisis, like other firms, were net sellers, contributing to the crash. [26] [27] [28]
The joint report continued: "At 2:45:28 p.m., trading on the E-Mini was paused for five seconds when the Chicago Mercantile Exchange ('CME') Stop Logic Functionality was triggered in order to prevent a cascade of further price declines. In that short period of time, sell-side pressure in the E-Mini was partly alleviated and buy-side interest increased. When trading resumed at 2:45:33 p.m., prices stabilized and shortly thereafter, the E-Mini began to recover, followed by the SPY". [43] After a short while, as market participants had "time to react and verify the integrity of their data and systems, buy-side and sell-side interest returned and an orderly price discovery process began to function", and by 3:00 p.m., most stocks "had reverted back to trading at prices reflecting true consensus values". [43]
A few hours after the release of the 104-page SEC/CFTC 2010 report, a number of critics stated that blaming a single order (from Waddell & Reed) for triggering the event was disingenuous. Most prominent of all, the CME issued, within 24 hours, a rare press release in which it argued against the SEC/CFTC explanation: [49]
Futures and options markets are hedging and risk transfer markets. The report references a series of bona fide hedging transactions, totaling 75,000 contracts, entered into by an institutional asset manager to hedge a portion of the risk in its $75 billion investment portfolio in response to global economic events and the fundamentally deteriorating market conditions that day. The 75,000 contracts represented 1.3% of the total E-Mini S&P 500 volume of 5.7 million contracts on May 6 and less than 9% of the volume during the time period in which the orders were executed. The prevailing market sentiment was evident well before these orders were placed, and the orders, as well as the manner in which they were entered, were both legitimate and consistent with market practices. These hedging orders were entered in relatively small quantities and in a manner designed to dynamically adapt to market liquidity by participating in a target percentage of 9% of the volume executed in the market. As a result of the significant volumes traded in the market, the hedge was completed in approximately twenty minutes, with more than half of the participant's volume executed as the market rallied—not as the market declined. Additionally, the aggregate size of this participant's orders was not known to other market participants. Additionally, the most precipitous period of market decline in the E-Mini S&P 500 futures on May 6 occurred during the 3½ minute period immediately preceding the market bottom that was established at 13:45:28. During that period, the participant hedging its portfolio represented less than 5% of the total volume of sales in the market.
David Leinweber, director of the Center for Innovative Financial Technology at Lawrence Berkeley National Laboratory, was invited by The Journal of Portfolio Management to write an editorial, in which he openly criticized the government's technological capabilities and inability to study today's markets. Leinweber wrote: [50]
The heads of the SEC and CFTC often point out that they are running an IT museum. They have photographic evidence to prove it—the highest-tech background that The New York Times (on September 21, 2010) could find for a photo of Gregg Berman, the SEC’s point man on the flash, was a corner with five PCs, a Bloomberg, a printer, a fax, and three TVs on the wall with several large clocks. A better measure of the inadequacy of the current mélange of IT antiquities is that the SEC/CFTC report on the May 6 crash was released on September 30, 2010. Taking nearly five months to analyze the wildest ever five minutes of market data is unacceptable. CFTC Chair Gensler specifically blamed the delay on the “enormous” effort to collect and analyze data. What an enormous mess it is.
Nanex, a leading firm specialized in the analysis of high-frequency data, also pointed out to several inconsistencies in the CFTC study: [51]
Based on interviews and our own independent matching of the 6,438 W&R executions to the 147,577 CME executions during that time, we know for certain that the algorithm used by W&R never took nor required liquidity. It always posted sell orders above the market and waited for a buyer; it never crossed the bid/ask spread. That means that none of the 6,438 trades were executed by hitting a bid. [...] [S]tatements from page 36 of Kirilenko's paper [5] cast serious doubt on the credibility of their analysis. [...] It is widely believed that the "sell program" refers to the algo selling the W&R contracts. However, based on the statements above, this cannot be true. The sell program must be referring to a different algo, or Kirilenko's analysis is fundamentally flawed, because the paper incorrectly identifies trades that hit the bid as executions by the W&R algo.
!["Order flow toxicity" (measured as CDF [VPIN]) was at historically high levels one hour prior to the flash crash Flash Crash.jpg](http://upload.wikimedia.org/wikipedia/commons/thumb/0/00/Flash_Crash.jpg/220px-Flash_Crash.jpg)
| External videos | |
|---|---|
 Video of the S&P500 futures during the flash crash |
As of July 2011, only one theory on the causes of the flash crash was published by a Journal Citation Reports indexed, peer-reviewed scientific journal. [52] It was reported in 2011 that one hour before its collapse in 2010, the stock market registered the highest reading of "toxic order imbalance" in previous history. [52] The authors of this 2011 paper apply widely accepted market microstructure models to understand the behavior of prices in the minutes and hours prior to the crash. According to this paper, "order flow toxicity" can be measured as the probability that informed traders (e.g., hedge funds) adversely select uninformed traders (e.g., market makers). For that purpose, they developed the Volume-Synchronized Probability of Informed Trading (VPIN) Flow Toxicity metric, which delivered a real-time estimate of the conditions under which liquidity is being provided. If the order imbalance becomes too toxic, market makers are forced out of the market. As they withdraw, liquidity disappears, which increases even more the concentration of toxic flow in the overall volume, which triggers a feedback mechanism that forces even more market makers out. This cascading effect has caused hundreds of liquidity-induced crashes in the past, the flash crash being one (major) example of it.
However, independent studies published in 2013 strongly disputed the claim that one hour before its collapse in 2010, the stock market registered the highest reading of "toxic order imbalance" in previous history. [54] [55] [56] In particular, in 2011 Andersen and Bondarenko conducted a comprehensive investigation of the two main versions of VPIN used by its creators, one based on the standard tick-rule (or TR-VPIN) [52] [57] [58] and the other based on Bulk Volume Classification (or BVC-VPIN). [59] They find that the value of TR-VPIN (BVC-VPIN) one hour before the crash "was surpassed on 71 (189) preceding days, constituting 11.7% (31.2%) of the pre-crash sample". Similarly, the value of TR-VPIN (BVC-VPIN) at the start of the crash was "topped on 26 (49) preceding days, or 4.3% (8.1%) of the pre-crash sample". [55]
Note that the source of increasing "order flow toxicity" on May 6, 2010, is not determined in Easley, Lopez de Prado, and O'Hara's 2011 publication. [52] Whether a dominant source of toxic order flow on May 6, 2010, was from firms representing public investors or whether a dominant source was intermediary or other proprietary traders could have a significant effect on regulatory proposals put forward to prevent another flash crash. According to Bloomberg, the VPIN metric is the subject of a pending patent application filed by the paper's three authors, Maureen O'Hara and David Easley of Cornell University, and Marcos Lopez de Prado, of Tudor Investment Corporation. [60]
A study of VPIN [61] by scientists from the Lawrence Berkeley National Laboratory cited the 2011 conclusions of Easley, Lopez de Prado and O'Hara for VPIN on S&P 500 futures [52] but provided no independent confirmation for the claim that VPIN reached its historical high one hour before the crash:
The Chief Economist of the Commodity Futures Trading Commission and several academic economists published a working paper containing a review and empirical analysis of trade data from the Flash Crash. [62] The authors examined the characteristics and activities of buyers and sellers in the Flash Crash and determined that a large seller, a mutual fund firm, exhausted available fundamental buyers and then triggered a cascade of selling by intermediaries, particularly high-frequency trading firms. Like the SEC/CFTC report described earlier, the authors call this cascade of selling "hot potato trading", [53] as high-frequency firms rapidly acquired and then liquidated positions among themselves at steadily declining prices.
The authors conclude:
Based on our analysis, we believe that High Frequency Traders exhibit trading patterns inconsistent with the traditional definition of market making. Specifically, High Frequency Traders aggressively trade in the direction of price changes. This activity comprises a large percentage of total trading volume, but does not result in a significant accumulation of inventory. As a result, whether under normal market conditions or during periods of high volatility, High Frequency Traders are not willing to accumulate large positions or absorb large losses. Moreover, their contribution to higher trading volumes may be mistaken for liquidity by Fundamental Traders. Finally, when rebalancing their positions, High Frequency Traders may compete for liquidity and amplify price volatility. Consequently, we believe, that irrespective of technology, markets can become fragile when imbalances arise as a result of large traders seeking to buy or sell quantities larger than intermediaries are willing to temporarily hold, and simultaneously long-term suppliers of liquidity are not forthcoming even if significant price concessions are offered.
Recent research on dynamical complex networks published in Nature Physics (2013) suggests that the 2010 Flash Crash may be an example of the "avoided transition" phenomenon in network systems with critical behavior. [63]
In April 2015, Navinder Singh Sarao, an autistic [64] [65] London-based point-and-click trader, [66] was arrested for his alleged role in the flash crash. According to criminal charges brought by the United States Department of Justice, Sarao allegedly used an automated program to generate large sell orders, pushing down prices, which he then canceled to buy at the lower market prices. The Commodity Futures Trading Commission filed civil charges against Sarao. [67] [68] In August 2015, Sarao was released on a £50,000 bail with a full extradition hearing scheduled for September with the US Department of Justice. Sarao and his company, Nav Sarao Futures Limited, allegedly made more than $40 million in profit from trading from 2009 to 2015. [69]
During extradition proceedings he was represented by Richard Egan [70] of Tuckers Solicitors. [71]
As of 2017 Sarao's lawyers claim that all of his assets were stolen or otherwise lost in bad investments. Sarao was released on bail, banned from trading and placed under the care of his father. [72]
Sarao pleaded guilty to one count of electronic fraud and one count of spoofing. [73] In January 2020, he was given a sentence of one year's home confinement, with no jail time. The sentence was relatively lenient, as a result of prosecutors' emphasis on how much Sarao had cooperated with them, that he was not motivated by greed and his diagnosis of Asperger syndrome. [74] [75] [76] [77]
A stock market anomaly, the major market indexes dropped by over 9% (including a roughly 7% decline in a roughly 15-minute span at approximately 2:45 p.m., on May 6, 2010) [78] [79] before a partial rebound. [9] Temporarily, $1 trillion in market value disappeared. [80] While stock markets do crash, immediate rebounds are unprecedented. The stocks of eight major companies in the S&P 500 fell to one cent per share for a short time, including Accenture, CenterPoint Energy and Exelon; while other stocks, including Sotheby's, Apple Inc. and Hewlett-Packard, increased in value to over $100,000 in price. [8] [81] [82] Procter & Gamble in particular dropped nearly 37% before rebounding, within minutes, back to near its original levels.
Stocks continued to rebound in the following days, helped by a bailout package in Europe to help save the euro. The S&P 500 erased all losses within a week, but selling soon took over again and the indices reached lower depths within two weeks.
The NASDAQ released their timeline of the anomalies during U.S. Congressional House Subcommittee on Capital Markets and Government-Sponsored Enterprises [83] hearings on the flash crash. [2] NASDAQ's timeline indicates that NYSE Arca may have played an early role and that the Chicago Board Options Exchange sent a message saying that NYSE Arca was "out of NBBO" (National best bid and offer). The Chicago Board Options Exchange, NASDAQ, NASDAQ OMX BX and BATS Exchange all declared self-help against NYSE Arca. [2]
SEC Chairwoman Mary Schapiro testified that "stub quotes" may have played a role in certain stocks that traded for 1 cent a share. [84] According to Schapiro: [85]
The absurd result of valuable stocks being executed for a penny likely was attributable to the use of a practice called "stub quoting." When a market order is submitted for a stock, if available liquidity has already been taken out, the market order will seek the next available liquidity, regardless of price. When a market maker’s liquidity has been exhausted, or if it is unwilling to provide liquidity, it may at that time submit what is called a stub quote—for example, an offer to buy a given stock at a penny. A stub quote is essentially a place holder quote because that quote would never—it is thought—be reached. When a market order is seeking liquidity and the only liquidity available is a penny-priced stub quote, the market order, by its terms, will execute against the stub quote. In this respect, automated trading systems will follow their coded logic regardless of outcome, while human involvement likely would have prevented these orders from executing at absurd prices. As noted below, we are reviewing the practice of displaying stub quotes that are never intended to be executed.
Officials announced that new trading curbs, also known as circuit breakers, would be tested during a six-month trial period ending on December 10, 2010. These circuit breakers would halt trading for five minutes on any S&P 500 stock that rises or falls more than 10 percent in a five-minute period. [86] [87] The circuit breakers would only be installed to the 404 New York Stock Exchange listed S&P 500 stocks. The first circuit breakers were installed to only 5 of the S&P 500 companies on Friday, June 11, to experiment with the circuit breakers. The five stocks were EOG Resources, Genuine Parts, Harley Davidson, Ryder System and Zimmer Holdings. By Monday, June 14, 44 had them. By Tuesday, June 15, the number had grown to 223, and by Wednesday, June 16, all 404 companies had circuit breakers installed. [88] On June 16, 2010, trading in the Washington Post Company's shares were halted for five minutes after it became the first stock to trigger the new circuit breakers. Three erroneous NYSE Arca trades were said to have been the cause of the share price jump. [89]
On May 6, the markets only broke trades that were more than 60 percent away from the reference price in a process that was not transparent to market participants. A list of 'winners' and 'losers' created by this arbitrary measure has never been made public. By establishing clear and transparent standards for breaking erroneous trades, the new rules should help provide certainty in advance as to which trades will be broken, and allow market participants to better manage their risks. [90]
In a 2011 article that appeared on the Wall Street Journal on the eve of the anniversary of the 2010 "flash crash", it was reported that high-frequency traders were then less active in the stock market. Another article in the journal said trades by high-frequency traders had decreased to 53% of stock-market trading volume, from 61% in 2009. [91] Former Delaware senator Edward E. Kaufman and Michigan senator Carl Levin published a 2011 op-ed in The New York Times a year after the Flash Crash, sharply critical of what they perceived to be the SEC's apparent lack of action to prevent a recurrence. [92]
In 2011 high-frequency traders moved away from the stock market as there had been lower volatility and volume. The combined average daily trading volume in the New York Stock Exchange and Nasdaq Stock Market in the first four months of 2011 fell 15% from 2010, to an average of 6.3 billion shares a day. Trading activities declined throughout 2011, with April's daily average of 5.8 billion shares marking the lowest month since May 2008. Sharp movements in stock prices, which were frequent during the period from 2008 to the first half of 2010, were in a decline in the Chicago Board Options Exchange volatility index, the VIX, which fell to its lowest level in April 2011 since July 2007. [93]
These volumes of trading activity in 2011, to some degree, were regarded as more natural levels than during the financial crisis and its aftermath. Some argued that those lofty levels of trading activity were never an accurate picture of demand among investors. It was a reflection of computer-driven traders passing securities back and forth between day-trading hedge funds. The flash crash exposed this phantom liquidity. In 2011 high-frequency trading firms became increasingly active in markets like futures and currencies, where volatility remains high. [93]
In 2011 trades by high-frequency traders accounted for 28% of the total volume in the futures markets, which included currencies and commodities, an increase from 22% in 2009. However, the growth of computerized and high-frequency trading in commodities and currencies coincided with a series of "flash crashes" in those markets. The role of human market makers, who match buyers and sellers and provide liquidity to the market, was more and more played by computer programs. If those program traders pulled back from the market, then big "buy" or "sell" orders could have led to sudden, big swings. It would have increased the probability of surprise distortions, as in the equity markets, according to a professional investor.[ citation needed ] In February 2011, the sugar market took a dive of 6% in just one second. On March 1, 2011, cocoa futures prices dropped 13% in less than a minute on the Intercontinental Exchange. Cocoa plunged $450 to a low of $3,217 a metric ton before rebounding quickly. The U.S. dollar tumbled against the yen on March 16, 2011, falling 5% in minutes, one of its biggest moves ever. According to a former cocoa trader: "The electronic platform is too fast; it doesn't slow things down like humans would." [91]
In July 2012, the SEC launched an initiative to create a new market surveillance tool known as the Consolidated Audit Trail (CAT). [94] By April 2015, despite support for the CAT from SEC Chair Mary Jo White and members of Congress, work to finish the project continued to face delays. [95]
The Nasdaq Stock Market is an American stock exchange based in New York City. It is the most active stock trading venue in the U.S. by volume, and ranked second on the list of stock exchanges by market capitalization of shares traded, behind the New York Stock Exchange. The exchange platform is owned by Nasdaq, Inc., which also owns the Nasdaq Nordic stock market network and several U.S.-based stock and options exchanges. Although it trades stock of healthcare, financial, media, entertainment, retail, hospitality, and food businesses, it focuses more on technology stocks. The exchange is made up of both American and foreign firms, with China and Israel being the largest foreign sources.
A commodity market is a market that trades in the primary economic sector rather than manufactured products, such as cocoa, fruit and sugar. Hard commodities are mined, such as gold and oil. Futures contracts are the oldest way of investing in commodities. Commodity markets can include physical trading and derivatives trading using spot prices, forwards, futures, and options on futures. Farmers have used a simple form of derivative trading in the commodities market for centuries for price risk management.
Day trading is a form of speculation in securities in which a trader buys and sells a financial instrument within the same trading day, so that all positions are closed before the market closes for the trading day to avoid unmanageable risks and negative price gaps between one day's close and the next day's price at the open. Traders who trade in this capacity are generally classified as speculators. Day trading contrasts with the long-term trades underlying buy-and-hold and value investing strategies. Day trading may require fast trade execution, sometimes as fast as milli-seconds in scalping, therefore direct-access day trading software is often needed.
An exchange-traded fund (ETF) is a type of investment fund that is also an exchange-traded product, i.e., it is traded on stock exchanges. ETFs own financial assets such as stocks, bonds, currencies, debts, futures contracts, and/or commodities such as gold bars. Many ETFs provide some level of diversification compared to owning an individual stock.
E-mini S&P, often abbreviated to "E-mini" and designated by the commodity ticker symbol ES, is a stock market index futures contract traded on the Chicago Mercantile Exchange. The notional value of one contract is 50 times the value of the S&P 500 stock index; thus, for example, on June 20, 2018, the S&P 500 cash index closed at 2,767.32, making each E-mini contract a $138,366 bet.
Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.
Open outcry is a method of communication between professionals on a stock exchange or futures exchange, typically on a trading floor. It involves shouting and the use of hand signals to transfer information primarily about buy and sell orders. The part of the trading floor where this takes place is called a pit.
Direct market access (DMA) in financial markets is the electronic trading infrastructure that gives investors wishing to trade in financial instruments a way to interact with the order book of an exchange. Normally, trading on the order book is restricted to broker-dealers and market making firms that are members of the exchange. Using DMA, investment companies and other private traders use the information technology infrastructure of sell side firms such as investment banks and the market access that those firms possess, but control the way a trading transaction is managed themselves rather than passing the order over to the broker's own in-house traders for execution. Today, DMA is often combined with algorithmic trading giving access to many different trading strategies. Certain forms of DMA, most notably "sponsored access", have raised substantial regulatory concerns because of the possibility of a malfunction by an investor to cause widespread market disruption.
An automated trading system (ATS), a subset of algorithmic trading, uses a computer program to create buy and sell orders and automatically submits the orders to a market center or exchange. The computer program will automatically generate orders based on predefined set of rules using a trading strategy which is based on technical analysis, advanced statistical and mathematical computations or input from other electronic sources.
In finance, a dark pool is a private forum for trading securities, derivatives, and other financial instruments. Liquidity on these markets is called dark pool liquidity. The bulk of dark pool trades represent large trades by financial institutions that are offered away from public exchanges like the New York Stock Exchange and the NASDAQ, so that such trades remain confidential and outside the purview of the general investing public. The fragmentation of electronic trading platforms has allowed dark pools to be created, and they are normally accessed through crossing networks or directly among market participants via private contractual arrangements. Generally, dark pools are not available to the public, but in some cases, they may be accessed indirectly by retail investors and traders via retail brokers.
High-frequency trading (HFT) is a type of algorithmic trading in finance characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools. While there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, co-location, and very short-term investment horizons in trading securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second.
Flash trading, otherwise known as a flash order, is a marketable order sent to a market center that is not quoting the industry's best price or that cannot fill that order in its entirety. The order is then flashed to recipients of the venue's proprietary data feed to see if any of those firms wants to take the other side of the order.
In modern finance, a flash crash is a very rapid, deep, and volatile fall in security prices occurring within a very short time period followed by a quick recovery. Flash crashes are frequently blamed by media on trades executed by black-box trading, combined with high-frequency trading, whose speed and interconnectedness can result in the loss and recovery of billions of dollars in a matter of minutes and seconds, but in reality occur because almost all participants have pulled their liquidity and temporarily paused their trading in the face of a sudden increase in risk.
Virtu Financial is an American company that provides financial services, trading products and market making services. Virtu provides product suite including offerings in execution, liquidity sourcing, analytics, broker-neutral, multi-dealer platforms in workflow technology and two-sided quotations and trades in equities, commodities, currencies, options, fixed income, and other securities on over 230 exchanges, markets, and dark pools. Virtu uses proprietary technology to trade large volumes of securities. The company went public on the Nasdaq in 2015.
Investors Exchange (IEX) is a stock exchange in the United States. It was founded in 2012 in order to mitigate the effects of high-frequency trading. IEX was launched as a national securities exchange in September 2016. On October 24, 2017, it received regulatory approval from the U.S. Securities and Exchange Commission (SEC) to list companies. IEX listed its first public company, Interactive Brokers, on October 5, 2018. The exchange said that companies would be able to list for free for the first five years, before a flat annual rate of $50,000. On September 23, 2019, it announced it was leaving its listing business.
Bradley Toshio Katsuyama is a Canadian financial services executive. He is the CEO and co-founder of the IEX, the Investors Exchange. He left RBC in 2012 to co-found IEX under the premise that it would be a fairer stock trading venue than other exchanges.
In finance, quote stuffing refers to a form of market manipulation employed by high-frequency traders (HFT) that involves quickly entering and withdrawing a large number of orders in an attempt to flood the market. This can create confusion in the market and trading opportunities for high-speed algorithmic traders. The term is relatively new to the financial market lexicon and was coined by Nanex in studies on HFT behavior during the 2010 Flash Crash.
Spoofing is a disruptive algorithmic trading activity employed by traders to outpace other market participants and to manipulate markets. Spoofers feign interest in trading futures, stocks, and other products in financial markets creating an illusion of the demand and supply of the traded asset. In an order driven market, spoofers post a relatively large number of limit orders on one side of the limit order book to make other market participants believe that there is pressure to sell or to buy the asset.
For three hours on August 22, 2013, trading was halted on the Nasdaq Stock Market. Trading on the exchange stopped at 12:14 pm and resumed at 3:25 pm, with 35 minutes left of trading for the day. One week after the trading halt NASDAQ OMX credited the freeze to an overloading of the Securities Information Processor (SIP) caused by reconnection issues with the New York Stock Exchange Arca. The freeze received substantial media coverage and generated discussions on the security of increasingly technologically advanced stock exchanges. The event coined the term "flash freeze" following the earlier "flash crash" on May 6, 2010.
Jump Trading LLC is a proprietary trading firm with a focus on algorithmic and high-frequency trading strategies. The firm has over 700 employees in Chicago, New York, Austin, London, Tel Aviv, Singapore, Shanghai, Bristol, Gurgaon, Gandhinagar, Sydney, Amsterdam, Hong Kong, and Paris and is active in futures, options, cryptocurrency, and equities markets worldwide.