Algorithmic trading

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This is of great importance to high-frequency traders, because they have to attempt to pinpoint the consistent and probable performance ranges of given financial instruments. These professionals are often dealing in versions of stock index funds like the E-mini S&Ps, because they seek consistency and risk-mitigation along with top performance. They must filter market data to work into their software programming so that there is the lowest latency and highest liquidity at the time for placing stop-losses and/or taking profits. With high volatility in these markets, this becomes a complex and potentially nerve-wracking endeavor, where a small mistake can lead to a large loss. Absolute frequency data play into the development of the trader's pre-programmed instructions.

1372:"Increasingly, people are looking at all forms of news and building their own indicators around it in a semi-structured way," as they constantly seek out new trading advantages said Rob Passarella, global director of strategy at Dow Jones Enterprise Media Group. His firm provides both a low latency news feed and news analytics for traders. Passarella also pointed to new academic research being conducted on the degree to which frequent Google searches on various stocks can serve as trading indicators, the potential impact of various phrases and words that may appear in Securities and Exchange Commission statements and the latest wave of online communities devoted to stock trading topics. 1196:

institutions connecting to stock exchanges and electronic communication networks (ECNs) to rapidly execute financial transactions. Most HFT firms depend on low latency execution of their trading strategies. Joel Hasbrouck and Gideon Saar (2013) measure latency based on three components: the time it takes for (1) information to reach the trader, (2) the trader's algorithms to analyze the information, and (3) the generated action to reach the exchange and get implemented. In a contemporary electronic market (circa 2009), low latency trade processing time was qualified as under 10 milliseconds, and ultra-low latency as under 1 millisecond.

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other factors. "True" arbitrage requires that there be no market risk involved. Where securities are traded on more than one exchange, arbitrage occurs by simultaneously buying in one and selling on the other. Such simultaneous execution, if perfect substitutes are involved, minimizes capital requirements, but in practice never creates a "self-financing" (free) position, as many sources incorrectly assume following the theory. As long as there is some difference in the market value and riskiness of the two legs, capital would have to be put up in order to carry the long-short arbitrage position.

4626: 547:(IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010." However, other researchers have reached a different conclusion. One 2010 study found that HFT did not significantly alter trading inventory during the Flash Crash. Some algorithmic trading ahead of 5156: 5146: 5136: 1441: 831: 5166: 4843: 1029:

short-term investment horizons, and high cancellation rates for orders. In the U.S., high-frequency trading (HFT) firms represent 2% of the approximately 20,000 firms operating today, but account for 73% of all equity trading volume. As of the first quarter in 2009, total assets under management for hedge funds with HFT strategies were US$ 141 billion, down about 21% from their high. The HFT strategy was first made successful by

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programmed instructions or learned patterns, on the micro-level, their automated and reactive behavior makes certain parts of the communication dynamic more predictable. However, on the macro-level, it has been shown that the overall emergent process becomes both more complex and less predictable. This phenomenon is not unique to the stock market, and has also been detected with editing bots on Knowledge.

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most important being volatility and liquidity of the stock. For example, for a highly liquid stock, matching a certain percentage of the overall orders of stock (called volume inline algorithms) is usually a good strategy, but for a highly illiquid stock, algorithms try to match every order that has a favorable price (called liquidity-seeking algorithms).

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The trader then executes a market order for the sale of the shares they wished to sell. Because the best bid price is the investor's artificial bid, a market maker fills the sale order at $ 20.10, allowing for a $ .10 higher sale price per share. The trader subsequently cancels their limit order on the purchase he never had the intention of completing.

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ordinary investors rely on to delay price quotes while the stuffing is occurring. HFT firms benefit from proprietary, higher-capacity feeds and the most capable, lowest latency infrastructure. Researchers showed high-frequency traders are able to profit by the artificially induced latencies and arbitrage opportunities that result from quote stuffing.

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is executed, the prices in the other legs may have worsened, locking in a guaranteed loss. Missing one of the legs of the trade (and subsequently having to open it at a worse price) is called 'execution risk' or more specifically 'leg-in and leg-out risk'. In the simplest example, any good sold in one market should sell for the same price in another.

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market to buy or sell shares at a more favorable price. This is done by creating limit orders outside the current bid or ask price to change the reported price to other market participants. The trader can subsequently place trades based on the artificial change in price, then canceling the limit orders before they are executed.

241:(HFT), which is characterized by high turnover and high order-to-trade ratios. HFT strategies utilize computers that make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. As a result, in February 2012, the 286:, which is defined by the New York Stock Exchange as an order to buy or sell 15 or more stocks valued at over US$ 1 million total. In practice, program trades were pre-programmed to automatically enter or exit trades based on various factors. In the 1980s, program trading became widely used in trading between the S&P 500 1623:

investors, mutual funds, etc. This institution dominates standard setting in the pretrade and trade areas of security transactions. In 2006–2007, several members got together and published a draft XML standard for expressing algorithmic order types. The standard is called FIX Algorithmic Trading Definition Language (

1612:") to understand a constantly proliferating flow of new algorithmic order types. The R&D and other costs to construct complex new algorithmic orders types, along with the execution infrastructure, and marketing costs to distribute them, are fairly substantial. What was needed was a way that marketers (the " 1152:

the stock of the acquiring company. Usually the market price of the target company is less than the price offered by the acquiring company. The spread between these two prices depends mainly on the probability and the timing of the takeover being completed, as well as the prevailing level of interest

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to minimize the exposure to market risk, or the risk that prices may change on one market before both transactions are complete. In practical terms, this is generally only possible with securities and financial products which can be traded electronically, and even then, when first leg(s) of the trade

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at any probabilistic or temporal state and a positive cash flow in at least one state; in simple terms, it is the possibility of a risk-free profit at zero cost. Example: One of the most popular arbitrage trading opportunities is played with the S&P futures and the S&P 500 stocks. During most

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cannot guarantee convergence of prices. This is especially true when the strategy is applied to individual stocks – these imperfect substitutes can in fact diverge indefinitely. In theory, the long-short nature of the strategy should make it work regardless of the stock market direction. In practice,

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One of the more ironic findings of academic research on algorithmic trading might be that individual trader introduce algorithms to make communication more simple and predictable, while markets end up more complex and more uncertain. Since trading algorithms follow local rules that either respond to

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Algorithmic and high-frequency trading were shown to have contributed to volatility during the May 6, 2010 Flash Crash, when the Dow Jones Industrial Average plunged about 600 points only to recover those losses within minutes. At the time, it was the second largest point swing, 1,010.14 points, and

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has been keeping a watchful eye on the development of black box trading. In its annual report the regulator remarked on the great benefits of efficiency that new technology is bringing to the market. But it also pointed out that 'greater reliance on sophisticated technology and modelling brings with

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Most of the algorithmic strategies are implemented using modern programming languages, although some still implement strategies designed in spreadsheets. Increasingly, the algorithms used by large brokerages and asset managers are written to the FIX Protocol's Algorithmic Trading Definition Language

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by competitors. This is due to the evolutionary nature of algorithmic trading strategies – they must be able to adapt and trade intelligently, regardless of market conditions, which involves being flexible enough to withstand a vast array of market scenarios. As a result, a significant proportion of

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Suppose a trader desires to sell shares of a company with a current bid of $ 20 and a current ask of $ 20.20. The trader would place a buy order at $ 20.10, still some distance from the ask so it will not be executed, and the $ 20.10 bid is reported as the National Best Bid and Offer best bid price.

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involves placing a limit order to sell (or offer) above the current market price or a buy limit order (or bid) below the current price on a regular and continuous basis to capture the bid-ask spread. Automated Trading Desk, which was bought by Citigroup in July 2007, has been an active market maker,

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Strategies designed to generate alpha are considered market timing strategies. These types of strategies are designed using a methodology that includes backtesting, forward testing and live testing. Market timing algorithms will typically use technical indicators such as moving averages but can also

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are alternative trading systems that are private in nature—and thus do not interact with public order flow—and seek instead to provide undisplayed liquidity to large blocks of securities. In dark pools, trading takes place anonymously, with most orders hidden or "iceberged". Gamers or "sharks" sniff

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is a mathematical methodology sometimes used for stock investing, but it can be applied to other processes. In general terms the idea is that both a stock's high and low prices are temporary, and that a stock's price tends to have an average price over time. An example of a mean-reverting process is

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In modern global financial markets, algorithmic trading plays a crucial role in achieving financial objectives. For nearly 30 years, traders, investment banks, investment funds, and other financial entities have utilized algorithms to refine and implement trading strategies. The use of algorithms in

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More fully automated markets such as NASDAQ, Direct Edge and BATS (formerly an acronym for Better Alternative Trading System) in the US, have gained market share from less automated markets such as the NYSE. Economies of scale in electronic trading have contributed to lowering commissions and trade

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Exchange(s) provide data to the system, which typically consists of the latest order book, traded volumes, and last traded price (LTP) of scrip. The server in turn receives the data simultaneously acting as a store for historical database. The data is analyzed at the application side, where trading

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and in September 2011 the project published its initial findings in the form of a three-chapter working paper available in three languages, along with 16 additional papers that provide supporting evidence. All of these findings are authored or co-authored by leading academics and practitioners, and

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The success of these strategies is usually measured by comparing the average price at which the entire order was executed with the average price achieved through a benchmark execution for the same duration. Usually, the volume-weighted average price is used as the benchmark. At times, the execution

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may, for example, find that the price of wheat is lower in agricultural regions than in cities, purchase the good, and transport it to another region to sell at a higher price. This type of price arbitrage is the most common, but this simple example ignores the cost of transport, storage, risk, and

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Technological advances in finance, particularly those relating to algorithmic trading, has increased financial speed, connectivity, reach, and complexity while simultaneously reducing its humanity. Computers running software based on complex algorithms have replaced humans in many functions in the

1226:), which allows firms receiving orders to specify exactly how their electronic orders should be expressed. Orders built using FIXatdl can then be transmitted from traders' systems via the FIX Protocol. Basic models can rely on as little as a linear regression, while more complex game-theoretic and 596:

that they track. Profits are transferred from passive index investors to active investors, some of whom are algorithmic traders specifically exploiting the index rebalance effect. The magnitude of these losses incurred by passive investors has been estimated at 21–28bp per year for the S&P 500

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launched a new system called TradElect that promises an average 10 millisecond turnaround time from placing an order to final confirmation and can process 3,000 orders per second. Since then, competitive exchanges have continued to reduce latency with turnaround times of 3 milliseconds available.

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Most strategies referred to as algorithmic trading (as well as algorithmic liquidity-seeking) fall into the cost-reduction category. The basic idea is to break down a large order into small orders and place them in the market over time. The choice of algorithm depends on various factors, with the

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When the current market price is less than the average price, the stock is considered attractive for purchase, with the expectation that the price will rise. When the current market price is above the average price, the market price is expected to fall. In other words, deviations from the average

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Quote stuffing is a tactic employed by malicious traders that involves quickly entering and withdrawing large quantities of orders in an attempt to flood the market, thereby gaining an advantage over slower market participants. The rapidly placed and canceled orders cause market data feeds that

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One strategy that some traders have employed, which has been proscribed yet likely continues, is called spoofing. It is the act of placing orders to give the impression of wanting to buy or sell shares, without ever having the intention of letting the order execute to temporarily manipulate the

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A subset of risk, merger, convertible, or distressed securities arbitrage that counts on a specific event, such as a contract signing, regulatory approval, judicial decision, etc., to change the price or rate relationship of two or more financial instruments and permit the arbitrageur to earn a

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then four transactions can be made to guarantee a risk-free profit. HFT allows similar arbitrages using models of greater complexity involving many more than 4 securities. The TABB Group estimates that annual aggregate profits of low latency arbitrage strategies currently exceed US$ 21 billion.

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There are four key categories of HFT strategies: market-making based on order flow, market-making based on tick data information, event arbitrage and statistical arbitrage. All portfolio-allocation decisions are made by computerized quantitative models. The success of computerized strategies is

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Technological advancements and algorithmic trading have facilitated increased transaction volumes, reduced costs, improved portfolio performance, and enhanced transparency in financial markets. According to the Foreign Exchange Activity in April 2019 report, foreign exchange markets had a daily

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In 2005, the Regulation National Market System was put in place by the SEC to strengthen the equity market. This changed the way firms traded with rules such as the Trade Through Rule, which mandates that market orders must be posted and executed electronically at the best available price, thus

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the algorithm is typically the first stage and involves simulating the hypothetical trades through an in-sample data period. Optimization is performed in order to determine the most optimal inputs. Steps taken to reduce the chance of over-optimization can include modifying the inputs +/- 10%,

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As noted above, high-frequency trading (HFT) is a form of algorithmic trading characterized by high turnover and high order-to-trade ratios. Although there is no single definition of HFT, among its key attributes are highly sophisticated algorithms, specialized order types, co-location, very

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is a trade association that publishes free, open standards in the securities trading area. The FIX language was originally created by Fidelity Investments, and the association Members include virtually all large and many midsized and smaller broker dealers, money center banks, institutional

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Network-induced latency, a synonym for delay, measured in one-way delay or round-trip time, is normally defined as how much time it takes for a data packet to travel from one point to another. Low latency trading refers to the algorithmic trading systems and network routes used by financial

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is basically a specialized scalper and also referred to as dealers. The volume a market maker trades is many times more than the average individual scalper and would make use of more sophisticated trading systems and technology. However, registered market makers are bound by exchange rules

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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,

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Algorithmic trading has caused a shift in the types of employees working in the financial industry. For example, many physicists have entered the financial industry as quantitative analysts. Some physicists have even begun to do research in economics as part of doctoral research. This

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describes a portfolio of related financial securities, in which the portfolio value remains unchanged due to small changes in the value of the underlying security. Such a portfolio typically contains options and their corresponding underlying securities such that positive and negative

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A third of all European Union and United States stock trades in 2006 were driven by automatic programs, or algorithms. As of 2009, studies suggested HFT firms accounted for 60–73% of all US equity trading volume, with that number falling to approximately 50% in 2012. In 2006, at the

507:, over 40% of all orders were entered by algorithmic traders, with 60% predicted for 2007. American markets and European markets generally have a higher proportion of algorithmic trades than other markets, and estimates for 2008 range as high as an 80% proportion in some markets. 962:

sell side traders, has become more prominent and controversial. These algorithms or techniques are commonly given names such as "Stealth" (developed by the Deutsche Bank), "Iceberg", "Dagger", " Monkey", "Guerrilla", "Sniper", "BASOR" (developed by Quod Financial) and "Sniffer".

1271:-ness," Mr. Williams said. "Traders have intuitive senses of how the world works. But with these systems you pour in a bunch of numbers, and something comes out the other end, and it's not always intuitive or clear why the black box latched onto certain data or relationships." 934:

A special class of these algorithms attempts to detect algorithmic or iceberg orders on the other side (i.e. if you are trying to buy, the algorithm will try to detect orders for the sell side). These algorithms are called sniffing algorithms. A typical example is "Stealth".

491:, a high-frequency trading firm, reported that during five years the firm as a whole was profitable on 1,277 out of 1,278 trading days, losing money just one day, demonstrating the benefits of trading millions of times, across a diverse set of instruments every trading day. 1543:

protocol, the connection to different destinations has become easier and the go-to market time has reduced, when it comes to connecting with a new destination. With the standard protocol in place, integration of third-party vendors for data feeds is not cumbersome anymore.

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A wide range of statistical arbitrage strategies have been developed whereby trading decisions are made on the basis of deviations from statistically significant relationships. Like market-making strategies, statistical arbitrage can be applied in all asset classes.

1592:. Some researchers also cite a "cultural divide" between employees of firms primarily engaged in algorithmic trading and traditional investment managers. Algorithmic trading has encouraged an increased focus on data and had decreased emphasis on sell-side research. 486:

that the 300 securities firms and hedge funds that then specialized in this type of trading took in profits in 2008, which the authors had then called "relatively small" and "surprisingly modest" when compared to the market's overall trading volume. In March 2014,

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Though its development may have been prompted by decreasing trade sizes caused by decimalization, algorithmic trading has reduced trade sizes further. Jobs once done by human traders are being switched to computers. The speeds of computer connections, measured in

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Live testing is the final stage of development and requires the developer to compare actual live trades with both the backtested and forward tested models. Metrics compared include percent profitable, profit factor, maximum drawdown and average gain per trade.

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This increased market liquidity led to institutional traders splitting up orders according to computer algorithms so they could execute orders at a better average price. These average price benchmarks are measured and calculated by computers by applying the

1382:"There is a real interest in moving the process of interpreting news from the humans to the machines" says Kirsti Suutari, global business manager of algorithmic trading at Reuters. "More of our customers are finding ways to use news content to make money." 418:

in 1996. In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.

1360:"Computers are now being used to generate news stories about company earnings results or economic statistics as they are released. And this almost instantaneous information forms a direct feed into other computers which trade on the news." 1501:

A traditional trading system consists primarily of two blocks – one that receives the market data while the other that sends the order request to the exchange. However, an algorithmic trading system can be broken down into three parts:

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As more electronic markets opened, other algorithmic trading strategies were introduced. These strategies are more easily implemented by computers, as they can react rapidly to price changes and observe several markets simultaneously.

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was introduced in 1984 as an upgraded version of DOT. Both systems allowed for the routing of orders electronically to the proper trading post. The "opening automated reporting system" (OARS) aided the specialist in determining the

1377:"Markets are by their very nature conversations, having grown out of coffee houses and taverns," he said. So the way conversations get created in a digital society will be used to convert news into trades, as well, Passarella said. 1407:, which had already developed its own trading algorithms, paid $ 680 million for Automated Trading Desk, a 19-year-old firm that trades about 200 million shares a day. Citigroup had previously bought Lava Trading and OnTrade Inc. 1423:

were subjected to anonymous peer-review. Released in 2012, the Foresight study acknowledged issues related to periodic illiquidity, new forms of manipulation and potential threats to market stability due to errant algorithms or

1203:. They profit by providing information, such as competing bids and offers, to their algorithms microseconds faster than their competitors. The revolutionary advance in speed has led to the need for firms to have a real-time, 1923:

O'Hara, Maureen; Lopez De Prado, Marcos; Easley, David (2011), "Easley, D., M. López de Prado, M. O'Hara: The Microstructure of the 'Flash Crash': Flow Toxicity, Liquidity Crashes and the Probability of Informed Trading",

2038: 1616:") could express algo orders electronically such that buy-side traders could just drop the new order types into their system and be ready to trade them without constant coding custom new order entry screens each time. 180:

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.

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has warned that companies could become the "playthings" of speculators because of automatic high-frequency trading. Lord Myners said the process risked destroying the relationship between an investor and a company.

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by rapidly pulling liquidity from the market. As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered. (See

3144: 902:) the bid-ask spread. This procedure allows for profit for so long as price moves are less than this spread and normally involves establishing and liquidating a position quickly, usually within minutes or less. 4180: 1207:

trading platform to benefit from implementing high-frequency strategies. Strategies are constantly altered to reflect the subtle changes in the market as well as to combat the threat of the strategy being

817:, etc.), commonly offer moving averages for periods such as 50 and 100 days. While reporting services provide the averages, identifying the high and low prices for the study period is still necessary. 1307:"Goldman spends tens of millions of dollars on this stuff. They have more people working in their technology area than people on the trading desk...The nature of the markets has changed dramatically." 245:(CFTC) formed a special working group that included academics and industry experts to advise the CFTC on how best to define HFT. Algorithmic trading and HFT have resulted in a dramatic change of the 1977: 625:

execution risk, persistent and large divergences, as well as a decline in volatility can make this strategy unprofitable for long periods of time (e.g. 2004-2007). It belongs to wider categories of

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financial industry. Finance is essentially becoming an industry where machines and humans share the dominant roles – transforming modern finance into what one scholar has called, "cyborg finance".

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that may need to spread out the execution of a larger order or perform trades too fast for human traders to react to. However, it is also available to private traders using simple retail tools.

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rates. The bet in a merger arbitrage is that such a spread will eventually be zero, if and when the takeover is completed. The risk is that the deal "breaks" and the spread massively widens.

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As an arbitrage consists of at least two trades, the metaphor is of putting on a pair of pants, one leg (trade) at a time. The risk that one trade (leg) fails to execute is thus 'leg risk'.

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Arbitrage is not simply the act of buying a product in one market and selling it in another for a higher price at some later time. The long and short transactions should ideally occur

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Forward testing the algorithm is the next stage and involves running the algorithm through an out of sample data set to ensure the algorithm performs within backtested expectations.

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among other benefits. However, improvements in productivity brought by algorithmic trading have been opposed by human brokers and traders facing stiff competition from computers.

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Mean reversion involves first identifying the trading range for a stock, and then computing the average price using analytical techniques as it relates to assets, earnings, etc.

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out large orders by "pinging" small market orders to buy and sell. When several small orders are filled the sharks may have discovered the presence of a large iceberged order.

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strategy enabling traders to profit from transient discrepancies in relative value of close substitutes. Unlike in the case of classic arbitrage, in case of pairs trading, the

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Many broker-dealers offered algorithmic trading strategies to their clients – differentiating them by behavior, options and branding. Examples include Chameleon (developed by

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While many experts laud the benefits of innovation in computerized algorithmic trading, other analysts have expressed concern with specific aspects of computerized trading.

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The algorithms do not simply trade on simple news stories but also interpret more difficult to understand news. Some firms are also attempting to automatically assign

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says that the resulting "poor investor returns" from trading ahead of mutual funds is "the elephant in the room" that "shockingly, people are not talking about".

975:'s Laboratory for Financial Engineering in 2006. "Everyone is building more sophisticated algorithms, and the more competition exists, the smaller the profits." 718:

trading days, these two will develop disparity in the pricing between the two of them. This happens when the price of the stocks which are mostly traded on the

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changed the minimum tick size from 1/16 of a dollar (US$ 0.0625) to US$ 0.01 per share in 2001, and may have encouraged algorithmic trading as it changed the

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orders in NYSE-listed securities into the market. This software has been removed from the company's systems. ... Clients were not negatively affected by the

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which gives a relation between the prices of a domestic bond, a bond denominated in a foreign currency, the spot price of the currency, and the price of a

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where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own

3697: 2560: 1400:, on March 1, 2008) claiming that their service had beaten other news services by two seconds in reporting an interest rate cut by the Bank of England. 4375: 4405:

Hilbert, M., & Darmon, D. (2020). Largescale Communication Is More Complex and Unpredictable with Automated Bots. Journal of Communication, 70(5)

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Sattarov, Otabek; Muminov, Azamjon; Lee, Cheol Won; Kang, Hyun Kyu; Oh, Ryumduck; Ahn, Junho; Oh, Hyung Jun; Jeon, Heung Seok (January 1, 2020).

1427:. However, the report was also criticized for adopting "standard pro-HFT arguments" and advisory panel members being linked to the HFT industry. 515:

markets are considered fairly easy to integrate into algorithmic trading, with about 40% of options trading done via trading algorithms in 2016.

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Lauricella, Tom, and McKay, Peter A. "Dow Takes a Harrowing 1,010.14-Point Trip," Online Wall Street Journal, May 7, 2010. Retrieved May 9, 2010

2707: 1872: 950:, POV, Display size, Liquidity seeker, and Stealth. Modern algorithms are often optimally constructed via either static or dynamic programming. 1890:

Futures Trading Commission Votes to Establish a New Subcommittee of the Technology Advisory Committee (TAC) to focus on High Frequency Trading

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Gradually, old-school, high latency architecture of algorithmic systems is being replaced by newer, state-of-the-art, high infrastructure,

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financial markets has grown substantially since the mid-1990s, although the exact contribution to daily trading volumes remains imprecise.

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It is over. The trading that existed down the centuries has died. We have an electronic market today. It is the present. It is the future.

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Algorithmic trades require communicating considerably more parameters than traditional market and limit orders. A trader on one end (the "

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Profitability projections by the TABB Group, a financial services industry research firm, for the US equities HFT industry were US$ 1.3

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components offset, resulting in the portfolio's value being relatively insensitive to changes in the value of the underlying security.

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Kumar, Sameer (March 14, 2015). "Technology Edge in Algo Trading: Traditional Vs Automated Trading System Architecture". Finbridge.

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Diaz, David; Theodoulidis, Babis (January 10, 2012). "Financial Markets Monitoring and Surveillance: A Quote Stuffing Case Study".

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Competition is developing among exchanges for the fastest processing times for completing trades. For example, in June 2007, the

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orders, and the software issue was limited to the routing of certain listed stocks to NYSE. Knight has traded out of its entire

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Maneesilp, K.; Prasatkaew, C. (November 1, 2014). "Price Pattern Detection Using Finite State Machine with Fuzzy Transitions".

2249: 1200: 320:. Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community. 3936: 1911: 1084:

largely driven by their ability to simultaneously process volumes of information, something ordinary human traders cannot do.

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making trading and investing cheaper for other market participants. HFT has been a subject of intense public focus since the

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Menkveld, Albert J.; Jovanovic, Boyan (2010), "Jovanovic, Boyan, and Albert J. Menkveld. Middlemen in Securities Markets",

1536:(CEP), which is the heart of decision making in algo-based trading systems, is used for order routing and risk management. 1462: 1048:

and the Commodity Futures Trading Commission stated that both algorithmic trading and HFT contributed to volatility in the

852: 758:(or, the asset does not have negligible costs of storage; as such, for example, this condition holds for grain but not for 709:: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the 527: 242: 4289: 2461: 1144:

would be an example of this. Merger arbitrage generally consists of buying the stock of a company that is the target of a

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Hilbert, M., & Darmon, D. (2020). How Complexity and Uncertainty Grew with Algorithmic Trading. Entropy, 22(5), 499.

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said in reports that an algorithmic trade entered by a mutual fund company triggered a wave of selling that led to the

4154: 2490: 332:(ECNs) in the 1990s, which allowed for trading of stock and currencies outside of traditional exchanges. In the U.S., 2140: 1488: 1368:(deciding if the news is good or bad) to news stories so that automated trading can work directly on the news story. 878: 511:

also have active algorithmic trading, measured at about 80% of orders in 2016 (up from about 25% of orders in 2006).

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A further encouragement for the adoption of algorithmic trading in the financial markets came in 2001 when a team of

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or the delay in getting quotes to traders, security and the possibility of a complete system breakdown leading to a

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Both strategies, often simply lumped together as "program trading", were blamed by many people (for example by the

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Preis, T.; Paul, W.; Schneider, J. J. (2008), "Fluctuation patterns in high-frequency financial asset returns",

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Trading stocks in fractions dates back to the 1700s. It's a legacy of the Spanish traders, whose currency (the

1584:

In the U.S., spending on computers and software in the financial industry increased to $ 26.4 billion in 2005.

1540: 1466: 1336:

the biggest one-day point decline, 998.5 points, on an intraday basis in Dow Jones Industrial Average history.

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Another set of HFT strategies in classical arbitrage strategy might involve several securities such as covered

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https://www.martinhilbert.net/large-scale-communication-is-more-complex-and-unpredictable-with-automated-bots/

4086:"HENDERSHOTT, TERRENCE, CHARLES M. JONES, AND ALBERT J. MENKVELD. Does Algorithmic Trading Improve Liquidity?" 3082: 2782: 2557: 5452: 1529: 577: 361: 116: 31: 4629: 1319:

This issue was related to Knight's installation of trading software and resulted in Knight sending numerous

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was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7; the

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Citigroup to expand electronic trading capabilities by buying Automated Trading Desk, accessed July 4, 2007

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on a stock portfolio by dynamically trading stock index futures according to a computer model based on the

2426:"Triennial Central Bank Survey of Foreign Exchange and Over-the-counter (OTC) Derivatives Markets in 2019" 5661: 5629: 5533: 5487: 5470: 5423: 4982: 4445: 4226:

Knight Capital Group Provides Update Regarding August 1st Disruption To Routing In NYSE-listed Securities

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requires each market maker to post at least one bid and one ask at some price level, so as to maintain a

357: 4419: 3222:"A Pre-Trade Algorithmic Trading Model under Given Volume Measures and Generic Price Dynamics (GVM-GPD)" 2605: 1764: 5991: 5446: 5440: 4693: 4325: 2517:

Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era

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and NASDAQ markets either get ahead or behind the S&P Futures which are traded in the CME market.

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Chasing the Same Signals: How Black-Box Trading Influences Stock Markets from Wall Street to Shanghai

4258: 2623: 1646: 4343: 4105: 3922: 3831: 3597: 2840:"Regulatory Issues Raised by the Impact of Technological Changes on Market Integrity and Efficiency" 2446: 2337: 1116:

on the currency. If the market prices are different enough from those implied in the model to cover

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experienced a technology issue in their automated trading system, causing a loss of $ 440 million.

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preventing brokerages from profiting from the price differences when matching buy and sell orders.

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High-frequency funds started to become especially popular in 2007 and 2008. Many HFT firms are

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TECHNICAL COMMITTEE OF THE INTERNATIONAL ORGANIZATION OF SECURITIES COMMISSIONS (July 2011),

2433: 1577: 1419: 1296: 1204: 1073: 626: 589: 504: 451: 337: 246: 4519:

Farmer, J. Done (November 1999). "Physicists attempt to scale the ivory towers of finance".

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https://www.martinhilbert.net/how-complexity-and-uncertainty-grew-with-algorithmic-trading/

1312: 1105: 1041: 985: 535: 211: 151: 4044: 3981: 2280:"Algorithmic trading & DMA : an introduction to direct access trading strategies" 931:

price is also compared with the price of the instrument at the time of placing the order.

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which must periodically "rebalance" or adjust their portfolio to match the new prices and

266:

Computerization of the order flow in financial markets began in the early 1970s, when the

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and in the complexity and uncertainty of the market macrodynamic, particularly in the way

8: 5880: 5825: 5749: 5539: 5368: 5341: 5169: 5075: 5055: 4882: 3767: 2079: 1227: 1209: 630: 483: 479: 4542: 4302: 4014: 3702: 3509: 2820: 2801: 2744: 2003: 1230:

or predictive models can also be used to initiate trading. More complex methods such as

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accounting for about 6% of total volume on both NASDAQ and the New York Stock Exchange.

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of the most recent prices (e.g., the last 20) is often used as a buy or sell indicator.

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position, which has resulted in a realized pre-tax loss of approximately $ 440 million.

1300: 1162: 1004: 891: 803: 759: 706: 565: 341: 218: 60: 3728:"Citigroup to expand electronic trading capabilities by buying Automated Trading Desk" 3101:"Recommending Cryptocurrency Trading Points with Deep Reinforcement Learning Approach" 2203: 2011: 1414:

project investigating the future of computer trading in the financial markets, led by

5784: 5769: 5521: 4803: 4779: 4763: 4577: 4114: 4060: 4050: 3962: 3897: 3893: 3806: 3802: 3671: 3646: 3635: 3613: 3531: 3447: 3414: 3122: 2407: 2387: 2366: 2304: 2229: 2192:"Minimal Intelligence Agents for Bargaining Behaviours in Market-Based Environments, 2095: 1958: 1929: 1811: 1061: 814: 313: 306: 146: 141: 121: 4030: 3366: 2257: 2019: 1213:

net revenue from firms is spent on the R&D of these autonomous trading systems.

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and provide liquidity to the market, which has lowered volatility and helped narrow

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turnover of US$ 6.6 trillion, a significant increase from US$ 5.1 trillion in 2016.

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https://www.sec.gov/Archives/edgar/data/1592386/000104746914002070/a2218589zs-1.htm

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An example of the importance of news reporting speed to algorithmic traders was an

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An asset with a known price in the future does not today trade at its future price

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Kirilenko, Andrei; Kyle, Albert S.; Samadi, Mehrdad; Tuzun, Tugkan (May 5, 2014),

2388:"The Expanded Implementation Shortfall: Understanding Transaction Cost Components" 713:. When used by academics, an arbitrage is a transaction that involves no negative 522:

Algorithmic trading and HFT have been the subject of much public debate since the

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Financial market news is now being formatted by firms such as Need To Know News,

1328: 1324: 1149: 1057: 1052:. Among the major U.S. high frequency trading firms are Chicago Trading Company, 488: 455: 399: 374: 283: 276: 234: 184: 156: 75: 65: 4202:

Cracking The Street's New Math, Algorithmic trades are sweeping the stock market

2764:"Report examines May's 'flash crash,' expresses concern over high-speed trading" 5915: 5910: 5810: 5795: 5556: 5551: 5516: 5315: 5282: 5228: 5220: 5010: 4990: 4758: 3433: 2501:

Laughlin, G. Insights into High Frequency Trading from the Virtu Financial IPO

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processing fees, and contributed to international mergers and consolidation of

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it a greater risk that systems failure can result in business interruption'."

705:

is the practice of taking advantage of a price difference between two or more

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The Flash Crash: The Impact of High Frequency Trading on an Electronic Market

2411: 1962: 646: 609: 442: 436: 80: 2425: 2403: 446:). These implementations adopted practices from the investing approaches of 5940: 5860: 5830: 5820: 5640: 5614: 5363: 5353: 5336: 5267: 5262: 5238: 5090: 5045: 4932: 4917: 4798: 3535: 3295: 2178: 1706: 1619: 1589: 1092: 1065: 1037: 959: 906: 895: 710: 651: 534:. The same reports found HFT strategies may have contributed to subsequent 345: 222: 188: 161: 70: 45: 3443: 2362: 5945: 5925: 5905: 5900: 5845: 5734: 5666: 4922: 4862: 4533: 3885: 3794: 3596:

Hendershott, Terrence, Charles M. Jones, and Albert J. Menkveld. (2010),

3243: 1994: 1562: 1558: 1387: 1287: 1077: 991: 751: 593: 581: 431: 230: 192: 166: 4550: 4498: 3117: 3100: 1926:

The Journal of Portfolio Management, Vol. 37, No. 2, pp. 118–128, Winter

5930: 5850: 5527: 5390: 4671: 996: 585: 548: 302: 196: 4181:"Enter algorithmic trading systems race or lose returns, report warns" 4084:

Hendershott, Terrence; Jones, Charles M.; Menkveld, Albert J. (2010),

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High-Speed Devices and Circuits with THz Applications by Jung Han Choi

3517: 3492:

Kenett, Dror Y.; Stanley, H. Eugene; Ben-Jacob, Eshel (July 2, 2013).

3400:"Forecasting Shares Trading Signals With Finite State Machine Variant" 482:

before expenses for 2014, significantly down on the maximum of US$ 21

5566: 5561: 5476: 5395: 4688: 4596: 3880:

Saar, Gideon; Hasbrouck, Joel (May 22, 2013). "Low-Latency Trading".

2783:"$ 4.1-billion trade set off Wall Street 'flash crash,' report finds" 1613: 1404: 1268: 1069: 740:

The same asset does not trade at the same price on all markets (the "

714: 663: 447: 226: 55: 5180: 4842: 4143: 3277: 3258: 3221: 2354:

An Introduction to Algorithmic Trading: Basic to Advanced Strategies

2226:

An Introduction to Algorithmic Trading: Basic to Advanced Strategies

1955:

The Rise of Computerized High Frequency Trading: Use and Controversy

1907: 1830: 1741: 1440: 958:

As of 2009, HFT, which comprises a broad set of buy-side as well as

830: 747:

Two assets with identical cash flows do not trade at the same price.

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Lin, Tom C.W., The New Investor, 60 UCLA 678 (2013), available at:

1601: 1145: 772: 282:

With the rise of fully electronic markets came the introduction of

271: 3234: 2821:"Special report: Globally, the flash crash is no flash in the pan" 2630:, vol. 383, no. June 23, 2007, p. 85, June 21, 2007 2477:"Opalesque Exclusive: High-frequency trading under the microscope" 5588: 3435:

2014 IEEE 11th International Conference on e-Business Engineering

3031:"High-Frequency Firms Tripled Trades in Stock Rout, Wedbush Says" 2874: 2300:

Inside the Black Box: The Simple Truth About Quantitative Trading

1624: 1223: 1053: 667: 569: 541:

List of largest daily changes in the Dow Jones Industrial Average

106: 3369:, The Wall Street Journal, August 19, 2008, p. c5. Available at 328:

The financial landscape was changed again with the emergence of

5331: 4049:, Trita-MAT. MA (8 ed.), Stockholm: KTH: KTH, p. 45, 3407:

Journal of Multidisciplinary Engineering Science and Technology

1410:

In late 2010, The UK Government Office for Science initiated a

911: 573: 378: 4640: 2462:"Fierce competition forces 'flash' HFT firms into new markets" 1922: 1829:

The New Financial Industry, Alabama Law Review, available at:

697: 597:

and 38–77bp per year for the Russell 2000. John Montgomery of

519:

markets are moving toward more access to algorithmic traders.

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Oladimeji, Ismaila W.; Folasade, Ismaila M. (April 1, 2016).

2530: 1873:"CFTC Panel Urges Broad Definition of High-Frequency Trading" 953: 694: 287: 202:

The term algorithmic trading is often used synonymously with

3083:"The Application of Pairs Trading to Energy Futures Markets" 2708:"Automatic Futures Trade Drove May Stock Crash, Report Says" 2162: 1242:

Algorithmic trading has been shown to substantially improve

679: 2141:"Agent-Human Interactions in the Continuous Double Auction" 943: 939: 910:

stipulating their minimum quote obligations. For instance,

736:

Arbitrage is possible when one of three conditions is met:

270:

introduced the "designated order turnaround" system (DOT).

217:

Examples of strategies used in algorithmic trading include

136: 4466:"LSE leads race for quicker trades" by Alistair MacDonald 1517:

strategies are fed from the user and can be viewed on the

559: 3386:

Artificial intelligence applied heavily to picking stocks

2642:"Algorithmic Trading Statistics (2024) - Analyzing Alpha" 2593:

A London Hedge Fund That Opts for Engineers, Not M.B.A.'s

971:"Now it's an arms race," said Andrew Lo, director of the 685: 392:

International Joint Conference on Artificial Intelligence

387: 4083: 2900: 2351:

Leshik, Edward A; Cralle, Jane, eds. (January 2, 2012).

1892:, February 9, 2012, Commodity Futures Trading Commission 3145:"The Insiders Guide to Trading the World Stock Markets" 2951:"The index premium and its hidden cost for index funds" 210:, some of which are based on formulas and results from 3491: 3098: 1604:") must enable their trading system (often called an " 3326:"Trading with the help of 'guerrillas' and 'snipers'" 2802:"U.S. probes computer algorithms after "flash crash"" 2726:"Lone $ 4.1 Billion Sale Led to 'Flash Crash' in May" 3468:"How To Build Robust Algorithmic Trading Strategies" 3278:"Hybrid IS-VWAP Dynamic Algorithmic Trading via LQR" 984:

include pattern recognition logic implemented using

691: 688: 682: 545:

International Organization of Securities Commissions

3494:"How High Frequency Trading Affects a Market Index" 3431: 2995:"The Weighting Game, and Other Puzzles of Indexing" 2870:"Ultra fast trading needs curbs -global regulators" 2194:

Hewlett-Packard Laboratories Technical Report 97-91

1952: 1525:(OMS), which in turn transmits it to the exchange. 676: 4000: 2745:"Single U.S. trade helped spark May's flash crash" 3665: 3397: 3259:"Styled Algorithmic Trading and the MV-MVP Style" 2161:Gjerstad, Steven; Dickhaut, John (January 1998), 1902: 1900: 1898: 1740:The New Investor, UCLA Law Review, available at: 1521:. Once the order is generated, it is sent to the 498:Algorithmic trading. Percentage of market volume. 5973: 4259:"City trusts computers to keep up with the news" 3788: 2913: 2160: 406:) could consistently out-perform human traders. 294:markets in a strategy known as index arbitrage. 4253: 4251: 3687: 3058:"Americans Want More Social Security, Not Less" 1751: 1749: 1588:interdisciplinary movement is sometimes called 4481:"Milliseconds are focus in algorithmic trades" 1895: 1295:Other issues include the technical problem of 1190: 551:rebalancing transfers profits from investors. 340:by permitting smaller differences between the 5196: 4656: 4344:"U.K. Foresight Study Slammed For HFT 'Bias'" 4312:Automated Trading Desk, accessed July 4, 2007 4042: 3879: 3598:"Does Algorithmic Trading Improve Liquidity?" 2988: 2986: 2039:"Wall Street Taking Another Look at Decimals" 921: 799:price are expected to revert to the average. 4381:. University of Applied Science Haaga-Helia. 4248: 3734:, International Herald Tribune, July 2, 2007 3651:: CS1 maint: multiple names: authors list ( 3354:"Soft Dollars and Other Trading Activities," 2944: 2942: 2861: 2558:The Real Story of Trading Software Espionage 2350: 2223: 2063:. CBS News. January 28, 2001. Archived from 1859:"Soft Dollars and Other Trading Activities," 1853: 1851: 1843:"Soft Dollars and Other Trading Activities," 1746: 5140:Alternative investment management companies 5117:Standards Board for Alternative Investments 4237: 3745: 3023: 2992: 2552: 2550: 2548: 2546: 2544: 2520:. Academic Press, December 3, 2013, p. 258. 2173:, vol. 22, no. 1, pp. 1–29, 2082:. In Lee, Cheng-Few; Lee, Alice C. (eds.). 2080:"Decimal Trading in the U.S. Stock Markets" 1870: 1469:. Unsourced material may be challenged and 1356:, to be read and traded on via algorithms. 859:. Unsourced material may be challenged and 732:Rational pricing § Arbitrage mechanics 725: 640: 5203: 5189: 5165: 5021:Taxation of private equity and hedge funds 4663: 4649: 4376:"Behind the scenes of algorithmic trading" 3547: 3545: 3381: 3379: 3356:§ 2:29 (Thomson West, 2015–2016 ed.). 2983: 2699: 2686: 1861:§ 2:31 (Thomson West, 2015–2016 ed.). 1845:§ 2:30 (Thomson West, 2015–2016 ed.). 1595: 1267:"The downside with these systems is their 1237: 1216: 954:Strategies that only pertain to dark pools 894:is liquidity provision by non-traditional 279:opening price (SOR; Smart Order Routing). 214:, and often rely on specialized software. 4532: 4373: 4276: 4274: 4272: 4104: 3621: 3525: 3233: 3116: 2993:Rekenthaler, John (February–March 2011). 2948: 2939: 2894: 2867: 2474: 1993: 1848: 1489:Learn how and when to remove this message 1017: 879:Learn how and when to remove this message 4320: 4318: 3567: 3565: 2812: 2799: 2793: 2761: 2736: 2624:"Algorithmic trading, Ahead of the tape" 2541: 1975: 1953:McGowan, Michael J. (November 8, 2010). 1099: 493: 323: 316:) for exacerbating or even starting the 4605:FIXatdl version 1.1 released March 2010 4178: 4043:Hult, Henrik; Kiessling, Jonas (2010), 3542: 3376: 3294: 3288: 3193: 2719: 2717: 2682: 2680: 2583:, The New York Times, December 20, 2012 2489:Virtu Financial Form S-1, available at 2385: 2277: 2250:"Algo Arms Race Has a Leader – For Now" 2228:. West Sussex, UK: Wiley. p. 169. 2036: 1803: 1234:have been used to create these models. 1046:U.S. Securities and Exchange Commission 560:Trading ahead of index fund rebalancing 524:U.S. Securities and Exchange Commission 5974: 4521:Computing in Science & Engineering 4518: 4390: 4388: 4369: 4367: 4365: 4269: 4046:Algorithmic trading with Markov chains 3967:: CS1 maint: archived copy as title ( 3681: 3359: 3256: 3142: 3055: 2818: 2800:Younglai, Rachelle (October 5, 2010). 2780: 2774: 2742: 2723: 2459: 2296: 2114: 1430: 1339: 898:, whereby traders attempt to earn (or 5210: 5184: 4721:fixed-income relative-value investing 4644: 4571: 4394: 4315: 3562: 3196:"Market Making in the Electronic Age" 3138: 3136: 2919: 2831: 2819:Spicer, Jonathan (October 15, 2010). 2781:Popper, Nathaniel (October 1, 2010). 2762:Goldfarb, Zachary (October 1, 2010). 2755: 2705: 2303:(1 ed.). John Wiley & Sons. 2224:Leshik, Edward; Cralle, Jane (2011). 2163:"Price Formation in Double Auctions, 1948: 1946: 1944: 1942: 1916: 1804:Kissell, Robert (September 4, 2020), 973:Massachusetts Institute of Technology 440:), Sniper and Guerilla (developed by 414:algorithm had been invented at HP by 390:researchers published a paper at the 348:' trading advantage, thus increasing 261: 4576:. Singapore: John Wiley & Sons. 4179:Skypala, Pauline (October 2, 2006). 3573:"OlsenInvest – Scientific Investing" 3388:by Charles Duhigg, November 23, 2006 3275: 3219: 2743:Spicer, Jonathan (October 1, 2010). 2714: 2677: 2581:Times Topics: High-Frequency Trading 2037:Vinzant, Carol (February 13, 2001). 1541:FIX (Financial Information Exchange) 1467:adding citations to reliable sources 1434: 857:adding citations to reliable sources 824: 592:of the underlying securities in the 528:Commodity Futures Trading Commission 243:Commodity Futures Trading Commission 4385: 4362: 3690:"HFT: Boon? Or Impending Disaster?" 2689:"How a Trading Algorithm Went Awry" 2687:Lauricella, Tom (October 2, 2010). 2595:by Heather Timmons, August 18, 2006 2256:, December 18, 2006, archived from 999:the inputs in large steps, running 301:was designed to create a synthetic 13: 4214:The Associated Press, July 2, 2007 4169:BBC News, Tuesday 3 November 2009. 4155:Black box traders are on the march 3688:James E. Hollis (September 2013). 3367:Watch Out for Sharks in Dark Pools 3257:Shen, Jackie; Yu, Yingjie (2014). 3133: 2724:Bowley, Graham (October 1, 2010). 2077: 1939: 1394:(appearances included page W15 of 1128: 809:Stock reporting services (such as 19:For trading using algorithms, see 14: 6008: 4611: 4167:Myners' super-fast shares warning 4144:https://ssrn.com/abstract=2227498 3169:"Rules | The Nasdaq Stock Market" 3004:. pp. 52–56 . Archived from 2920:Amery, Paul (November 11, 2010). 2386:Kissell, Robert (June 30, 2006). 2115:Bowley, Graham (April 25, 2011). 1957:. Duke University School of Law. 1908:https://doi.org/10.3390/e22050499 1831:https://ssrn.com/abstract=2417988 1742:https://ssrn.com/abstract=2227498 1249: 1175: 1007:and commission is accounted for. 779: 330:electronic communication networks 237:. Many fall into the category of 5459:Electronic communication network 5164: 5155: 5154: 5145: 5144: 5135: 5134: 4841: 4624: 4590: 4565: 4512: 4491: 4473: 4460: 4430: 4412: 4399: 4336: 4296: 4115:10.1111/j.1540-6261.2010.01624.x 3623:10.1111/j.1540-6261.2010.01624.x 3614:10.1111/j.1540-6261.2010.01624.x 3335:, March 19, 2007, archived from 2061:"Wall Street: Adios, Fractions!" 1439: 1087: 978: 938:Some examples of algorithms are 829: 672: 604: 584:, the most popular of which are 4670: 4219: 4207: 4195: 4172: 4160: 4148: 4136: 4077: 4036: 3994: 3975: 3929: 3873: 3847: 3838: 3782: 3760: 3720: 3659: 3589: 3485: 3460: 3425: 3391: 3346: 3318: 3269: 3250: 3213: 3187: 3161: 3092: 3075: 3049: 2706:Mehta, Nina (October 1, 2010). 2660: 2634: 2616: 2598: 2586: 2574: 2523: 2514:Morton Glantz, Robert Kissell. 2508: 2495: 2483: 2468: 2453: 2418: 2379: 2344: 2297:Narang, R.K. (August 7, 2009). 2290: 2271: 2242: 2217: 2184: 2154: 2133: 2108: 2071: 2053: 2030: 1969: 1715: 1712:) was in increments of eighths. 1699: 1534:complex event processing engine 473: 206:. These encompass a variety of 51:Development finance institution 4630:How algorithms shape our world 4468:The Wall Street Journal Europe 3982:FIXatdl – An Emerging Standard 3300:"Hurrying into the Next Panic" 3056:Siedle, Ted (March 25, 2013). 2670:The Wall Street Journal Europe 2148:IBM T.J.Watson Research Center 2086:. Springer. pp. 719–722. 1883: 1864: 1835: 1823: 1797: 1779: 1734: 1565:, have become very important. 1199:Low-latency traders depend on 578:individual retirement accounts 102:Bull (stock market speculator) 1: 5453:Multilateral trading facility 4157:The Telegraph, 27 August 2006 3553:Rise of the (Market) Machines 2970:10.1016/j.jempfin.2010.10.002 2202:, August 1997, archived from 2012:10.1016/S0370-1573(02)00634-8 1871:Silla Brush (June 20, 2012). 1728: 554: 543:.) A July 2011 report by the 434:), Stealth (developed by the 362:volume-weighted average price 32:Financial market participants 5876:Returns-based style analysis 5672:Post-modern portfolio theory 5578:Security characteristic line 4995:security characteristic line 4326:"Future of computer trading" 2958:Journal of Empirical Finance 2673:, p. 21, April 18, 2007 2475:Opalesque (August 4, 2009). 2254:NYU Stern School of Business 2117:"Preserving a Market Symbol" 2092:10.1007/978-3-030-91231-4_17 1278:Financial Services Authority 918:for each stock represented. 657: 599:Bridgeway Capital Management 7: 5630:Efficient-market hypothesis 5534:Capital asset pricing model 5471:Straight-through processing 4983:Capital asset pricing model 4702:Capital structure arbitrage 4374:Darbellay, Raphaël (2021). 3768:"Quote Stuffing Definition" 3035:Bloomberg/Financial Advisor 2667:"MTS to mull bond access", 2171:S. Gjerstad and J. Dickhaut 2165:Games and Economic Behavior 1807:Algorithmic Trading Methods 1672:Electronic trading platform 1642:Algorithmic tacit collusion 1630: 1610:execution management system 1258: 1191:Low latency trading systems 1156: 820: 744:" is temporarily violated). 580:in the US, are invested in 358:time-weighted average price 10: 6013: 5987:Electronic trading systems 5447:Alternative Trading System 4785:Commodity trading advisors 4308:December 29, 2018, at the 4023:10.1209/0295-5075/82/68005 3991:, FIXGlobal, December 2009 2868:Huw Jones (July 7, 2011). 1652:Alternative trading system 1547: 1539:With the emergence of the 1201:ultra-low latency networks 1179: 1160: 1021: 922:Transaction cost reduction 729: 256: 225:, inter-market spreading, 18: 16:Method of executing orders 5722: 5597: 5496: 5416: 5324: 5291: 5252: 5218: 5130: 5122:Managed Funds Association 5104: 5066:High-net-worth individual 5038: 4946: 4900: 4891: 4850: 4839: 4817: 4772: 4739: 4687: 4678: 4623: 4618: 4438:"InformationWeek Authors" 3373:retrieved August 19, 2008 2949:Petajisto, Antti (2011). 2848:IOSCO Technical Committee 1978:"Critical Market Crashes" 1647:Alpha generation platform 1425:excessive message traffic 616:is a long-short, ideally 5511:Arbitrage pricing theory 4959:Arbitrage pricing theory 4601:August 17, 2013, at the 2460:FT.com (April 3, 2014). 1692: 1667:Complex event processing 1232:Markov chain Monte Carlo 1031:Renaissance Technologies 948:Implementation shortfall 726:Conditions for arbitrage 641:Delta-neutral strategies 509:Foreign exchange markets 297:At about the same time, 204:automated trading system 21:automated trading system 5790:Initial public offering 5651:Modern portfolio theory 5546:Dividend discount model 5429:List of stock exchanges 5071:Institutional investors 4964:Assets under management 4789:managed futures account 4231:August 4, 2012, at the 3557:The Wall Street Journal 3143:Willis, Andrew (2001). 2693:The Wall Street Journal 2505:Retrieved May 22, 2015. 2404:10.3905/jot.2006.644083 2278:Johnson, Barry (2010). 2084:Encyclopedia of Finance 1657:Artificial intelligence 1606:order management system 1596:Communication standards 1523:order management system 1397:The Wall Street Journal 1238:Issues and developments 1217:Strategy implementation 1110:foreign exchange market 1001:Monte Carlo simulations 756:risk-free interest rate 360:or more usually by the 318:1987 stock market crash 268:New York Stock Exchange 5678:Random walk hypothesis 5096:Sovereign wealth funds 4868:High-frequency trading 4717:Fixed income arbitrage 4420:"Business and finance" 3987:March 5, 2020, at the 3917:Cite journal requires 3826:Cite journal requires 3472:AlgorithmicTrading.net 3194:Borelli, Mark (2001). 3157:on September 24, 2021. 2606:"Business and finance" 2441:Cite journal requires 2392:The Journal of Trading 2179:10.1006/game.1997.0576 1757:"Business and finance" 1682:Quantitative investing 1384: 1379: 1374: 1362: 1333: 1309: 1293: 1283: 1273: 1024:High-frequency trading 1018:High-frequency trading 499: 416:Dave Cliff (professor) 371: 309:option pricing model. 239:high-frequency trading 5816:Market capitalization 5625:Dollar cost averaging 4938:Structured securities 4754:Distressed securities 4726:Statistical arbitrage 4712:Equity market neutral 4707:Convertible arbitrage 4572:Brown, Brian (2010). 3855:"Low Latency Trading" 3585:on February 25, 2012. 3444:10.1109/ICEBE.2014.31 3276:Shen, Jackie (2017). 3220:Shen, Jackie (2013). 2563:July 7, 2011, at the 2428:. September 16, 2019. 2363:10.1002/9781119206033 2357:(1 ed.). Wiley. 2206:on September 24, 2015 1578:London Stock Exchange 1420:London Stock Exchange 1380: 1375: 1370: 1358: 1317: 1305: 1286:UK Treasury minister 1284: 1274: 1265: 1100:Statistical arbitrage 986:finite-state machines 792:stochastic equation. 730:Further information: 627:statistical arbitrage 590:market capitalization 505:London Stock Exchange 497: 452:statistical arbitrage 367: 338:market microstructure 324:Refinement and growth 247:market microstructure 183:It is widely used by 5636:Fundamental analysis 5620:Contrarian investing 5583:Security market line 5488:Liquidity aggregator 5465:Direct market access 5376:Quantitative analyst 5056:Financial endowments 5001:Fundamental analysis 4749:Shareholder activism 4731:Volatility arbitrage 4470:, June 19, 2007, p.3 4191:on October 30, 2007. 3886:10.2139/ssrn.1695460 3795:10.2139/ssrn.2193636 3752:Event Arb Definition 3732:The Associated Press 3438:. pp. 126–130. 3244:10.2139/ssrn.2327835 1810:, Elsevier Science, 1530:low-latency networks 1463:improve this section 1313:Knight Capital Group 1106:interest rate parity 1070:Two Sigma Securities 853:improve this section 594:stock or other index 342:bid and offer prices 212:mathematical finance 152:Financial regulation 5982:Algorithmic trading 5881:Reverse stock split 5826:Market manipulation 5750:Dual-listed company 5610:Algorithmic trading 5540:Capital market line 5342:Inter-dealer broker 5170:List of hedge funds 5160:Hedge fund managers 5076:Insurance companies 5061:Fund of hedge funds 4969:Black–Scholes model 4883:Proprietary trading 4858:Algorithmic trading 4825:Fund of hedge funds 4551:10.1109/5992.906615 4543:1999CSE.....1f..26D 4448:on October 22, 2007 4332:. October 23, 2012. 4303:Siemon's Case Study 4185:The Financial Times 4015:2008EL.....8268005P 3757:, September 4, 2010 3510:2013NatSR...3E2110K 3175:. November 23, 2020 3118:10.3390/app10041506 3002:Morningstar Advisor 2882:on January 28, 2016 2569:AdvancedTrading.com 2043:The Washington Post 2004:2003PhR...378....1S 1787:"| Aite Group" 1571:financial exchanges 1431:System architecture 1340:Recent developments 1228:pattern recognition 631:convergence trading 299:portfolio insurance 177:Algorithmic trading 56:Insurance companies 5921:Stock market index 5760:Efficient frontier 5699:Technical analysis 5657:Momentum investing 5479:(private exchange) 5369:Proprietary trader 5311:Shares outstanding 5301:Authorised capital 5026:Technical analysis 4350:. October 30, 2012 4093:Journal of Finance 3602:Journal of Finance 3498:Scientific Reports 3342:on October 7, 2009 3304:The New York Times 2730:The New York Times 2646:analyzingalpha.com 2122:The New York Times 1687:Technical analysis 1311:On August 1, 2012 1210:reverse engineered 1163:Layering (finance) 804:standard deviation 790:Ornstein-Uhlenbeck 568:, such as private 566:retirement savings 500: 262:Early developments 219:systematic trading 208:trading strategies 5992:Financial markets 5969: 5968: 5770:Flight-to-quality 5522:Buffett indicator 5212:Financial markets 5178: 5177: 5034: 5033: 4837: 4836: 4804:Long/short equity 4780:Convergence trade 4764:Special situation 4639: 4638: 4583:978-0-470-82488-7 4292:on July 16, 2011. 4056:978-91-7415-741-3 3698:Cutter Associates 3518:10.1038/srep02110 3453:978-1-4799-6563-2 3298:(July 29, 2009). 3037:. August 12, 2011 2922:"Know Your Enemy" 2787:Los Angeles Times 2535:www.aitegroup.com 2372:978-0-470-68954-7 2310:978-0-470-52914-0 2286:. 4Myeloma Press. 2235:978-0-470-68954-7 2101:978-3-030-91231-4 2067:on June 17, 2024. 2049:on June 17, 2024. 1976:Sornette (2003), 1817:978-0-12-815630-8 1791:www.aitegroup.com 1499: 1498: 1491: 1042:bid–offer spreads 889: 888: 881: 344:, decreasing the 174: 173: 147:Financial planner 142:Financial analyst 137:Banks and banking 122:Corporate finance 6004: 5886:Share repurchase 5598:Trading theories 5483:Crossing network 5441:Over-the-counter 5278:Restricted stock 5234:Secondary market 5205: 5198: 5191: 5182: 5181: 5168: 5167: 5158: 5157: 5148: 5147: 5138: 5137: 5081:Investment banks 4928:Foreign exchange 4898: 4897: 4845: 4685: 4684: 4665: 4658: 4651: 4642: 4641: 4634:TED (conference) 4628: 4627: 4616: 4615: 4606: 4594: 4588: 4587: 4569: 4563: 4562: 4536: 4534:adap-org/9912002 4516: 4510: 4509: 4507: 4505: 4499:"Moving markets" 4495: 4489: 4488: 4477: 4471: 4464: 4458: 4457: 4455: 4453: 4444:. 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Archived from 2034: 2028: 2027: 2022:, archived from 1997: 1995:cond-mat/0301543 1973: 1967: 1966: 1950: 1937: 1936: 1920: 1914: 1904: 1893: 1887: 1881: 1880: 1868: 1862: 1857:Lemke and Lins, 1855: 1846: 1841:Lemke and Lins, 1839: 1833: 1827: 1821: 1820: 1801: 1795: 1794: 1783: 1777: 1776: 1774: 1772: 1767:on June 22, 2008 1763:. Archived from 1753: 1744: 1738: 1722: 1719: 1713: 1703: 1637:2010 Flash Crash 1494: 1487: 1483: 1480: 1474: 1443: 1435: 1418:, ex-CEO of the 1416:Dame Clara Furse 1244:market liquidity 1138:Merger arbitrage 1118:transaction cost 1114:forward contract 1050:2010 Flash Crash 916:two-sided market 884: 877: 873: 870: 864: 833: 825: 742:law of one price 704: 703: 700: 699: 696: 693: 690: 687: 684: 681: 678: 622:law of one price 532:2010 Flash Crash 382: 350:market liquidity 185:investment banks 127:Personal finance 112:Financial market 66:Investment funds 61:Investment banks 28: 27: 6012: 6011: 6007: 6006: 6005: 6003: 6002: 6001: 5972: 5971: 5970: 5965: 5956:Voting interest 5866:Public offering 5801:Mandatory offer 5775:Government bond 5755:DuPont analysis 5718: 5714:Value investing 5709:Value averaging 5704:Trend following 5689:Style investing 5684:Sector rotation 5599: 5593: 5572:Net asset value 5498:Stock valuation 5492: 5412: 5320: 5287: 5273:Preferred stock 5248: 5214: 5209: 5179: 5174: 5126: 5112:Fund governance 5100: 5030: 4954:Absolute return 4942: 4893: 4887: 4878:Program trading 4873:Prime brokerage 4846: 4833: 4813: 4809:Trend following 4794:Dedicated short 4768: 4735: 4692: 4680: 4674: 4669: 4625: 4619:External videos 4614: 4609: 4603:Wayback Machine 4595: 4591: 4584: 4570: 4566: 4517: 4513: 4503: 4501: 4497: 4496: 4492: 4487:. 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Investopedia 3759: 3744: 3719: 3680: 3658: 3588: 3561: 3541: 3484: 3459: 3452: 3424: 3390: 3375: 3358: 3345: 3317: 3287: 3268: 3249: 3212: 3200:heinonline.org 3186: 3160: 3132: 3091: 3074: 3048: 3022: 2982: 2964:(2): 271–288. 2938: 2912: 2893: 2860: 2830: 2811: 2792: 2773: 2754: 2735: 2713: 2698: 2676: 2659: 2648:. May 31, 2021 2633: 2615: 2597: 2585: 2573: 2540: 2522: 2507: 2494: 2482: 2467: 2452: 2443:|journal= 2417: 2378: 2371: 2343: 2334:|website= 2309: 2289: 2270: 2241: 2234: 2216: 2183: 2153: 2132: 2107: 2100: 2070: 2052: 2029: 2026:on May 3, 2010 1968: 1938: 1915: 1894: 1882: 1863: 1847: 1834: 1822: 1816: 1796: 1778: 1745: 1732: 1730: 1727: 1724: 1723: 1714: 1697: 1696: 1694: 1691: 1690: 1689: 1684: 1679: 1677:Mirror trading 1674: 1669: 1664: 1662:Best execution 1659: 1654: 1649: 1644: 1639: 1632: 1629: 1597: 1594: 1549: 1546: 1514: 1513: 1510: 1507: 1497: 1496: 1447: 1445: 1438: 1432: 1429: 1403:In July 2007, 1341: 1338: 1260: 1257: 1251: 1250:Cyborg finance 1248: 1239: 1236: 1218: 1215: 1192: 1189: 1182:Quote stuffing 1180:Main article: 1177: 1176:Quote stuffing 1174: 1161:Main article: 1158: 1155: 1142:risk arbitrage 1130: 1127: 1101: 1098: 1089: 1086: 1022:Main article: 1019: 1016: 980: 977: 955: 952: 923: 920: 887: 886: 837: 835: 828: 822: 819: 811:Yahoo! Finance 785:Mean reversion 781: 780:Mean reversion 778: 768:simultaneously 764: 763: 748: 745: 727: 724: 659: 656: 642: 639: 635:relative value 618:market-neutral 606: 603: 561: 558: 556: 553: 475: 472: 460:mean reversion 366: 334:decimalization 325: 322: 263: 260: 258: 255: 172: 171: 170: 169: 164: 159: 154: 149: 144: 139: 134: 132:Public finance 129: 124: 119: 114: 109: 104: 99: 97:Angel investor 91: 90: 86: 85: 84: 83: 78: 73: 68: 63: 58: 53: 48: 40: 39: 35: 34: 15: 9: 6: 4: 3: 2: 6009: 5998: 5997:Share trading 5995: 5993: 5990: 5988: 5985: 5983: 5980: 5979: 5977: 5962: 5959: 5957: 5954: 5952: 5949: 5947: 5944: 5942: 5939: 5937: 5934: 5932: 5929: 5927: 5924: 5922: 5919: 5917: 5914: 5912: 5909: 5907: 5904: 5902: 5899: 5897: 5894: 5892: 5891:Short selling 5889: 5887: 5884: 5882: 5879: 5877: 5874: 5872: 5869: 5867: 5864: 5862: 5859: 5857: 5854: 5852: 5849: 5847: 5844: 5842: 5839: 5837: 5834: 5832: 5829: 5827: 5824: 5822: 5819: 5817: 5814: 5812: 5809: 5807: 5804: 5802: 5799: 5797: 5794: 5791: 5788: 5786: 5783: 5781: 5780:Greenspan put 5778: 5776: 5773: 5771: 5768: 5766: 5765:Financial law 5763: 5761: 5758: 5756: 5753: 5751: 5748: 5746: 5743: 5741: 5740:Cross listing 5738: 5736: 5733: 5731: 5728: 5727: 5725: 5723:Related terms 5721: 5715: 5712: 5710: 5707: 5705: 5702: 5700: 5697: 5695: 5694:Swing trading 5692: 5690: 5687: 5685: 5682: 5679: 5676: 5673: 5670: 5668: 5665: 5663: 5662:Mosaic theory 5660: 5658: 5655: 5652: 5649: 5647: 5646:Market timing 5644: 5642: 5639: 5637: 5634: 5631: 5628: 5626: 5623: 5621: 5618: 5616: 5613: 5611: 5608: 5607: 5605: 5603: 5596: 5590: 5587: 5584: 5581: 5579: 5576: 5573: 5570: 5568: 5565: 5563: 5560: 5558: 5555: 5553: 5550: 5547: 5544: 5541: 5538: 5535: 5532: 5529: 5526: 5523: 5520: 5518: 5515: 5512: 5509: 5507: 5504: 5503: 5501: 5499: 5495: 5489: 5486: 5484: 5481: 5478: 5475: 5472: 5469: 5466: 5463: 5460: 5457: 5454: 5451: 5448: 5445: 5442: 5439: 5435: 5434:Trading hours 5432: 5430: 5427: 5426: 5425: 5422: 5421: 5419: 5415: 5409: 5406: 5402: 5399: 5398: 5397: 5394: 5392: 5389: 5387: 5384: 5382: 5379: 5377: 5374: 5370: 5367: 5365: 5362: 5361: 5360: 5357: 5355: 5352: 5350: 5349:Broker-dealer 5347: 5343: 5340: 5338: 5335: 5334: 5333: 5330: 5329: 5327: 5323: 5317: 5314: 5312: 5309: 5307: 5306:Issued shares 5304: 5302: 5299: 5298: 5296: 5294: 5293:Share capital 5290: 5284: 5281: 5279: 5276: 5274: 5271: 5269: 5266: 5264: 5261: 5260: 5258: 5256: 5251: 5245: 5244:Fourth market 5242: 5240: 5237: 5235: 5232: 5230: 5227: 5226: 5224: 5222: 5217: 5213: 5206: 5201: 5199: 5194: 5192: 5187: 5186: 5183: 5171: 5163: 5161: 5153: 5151: 5143: 5141: 5133: 5132: 5129: 5123: 5120: 5118: 5115: 5113: 5110: 5109: 5107: 5103: 5097: 5094: 5092: 5091:Pension funds 5089: 5087: 5084: 5082: 5079: 5077: 5074: 5072: 5069: 5067: 5064: 5062: 5059: 5057: 5054: 5052: 5049: 5047: 5046:Vulture funds 5044: 5043: 5041: 5037: 5027: 5024: 5022: 5019: 5017: 5014: 5012: 5009: 5007: 5004: 5002: 4999: 4996: 4992: 4988: 4984: 4981: 4978: 4977:delta neutral 4974: 4970: 4967: 4965: 4962: 4960: 4957: 4955: 4952: 4951: 4949: 4945: 4939: 4936: 4934: 4933:Money markets 4931: 4929: 4926: 4924: 4921: 4919: 4916: 4914: 4911: 4909: 4906: 4905: 4903: 4899: 4896: 4890: 4884: 4881: 4879: 4876: 4874: 4871: 4869: 4866: 4864: 4861: 4859: 4856: 4855: 4853: 4849: 4844: 4830: 4829:Multi-manager 4826: 4823: 4822: 4820: 4816: 4810: 4807: 4805: 4802: 4800: 4797: 4795: 4792: 4790: 4786: 4783: 4781: 4778: 4777: 4775: 4771: 4765: 4762: 4760: 4757: 4755: 4752: 4750: 4747: 4746: 4744: 4742: 4738: 4732: 4729: 4727: 4724: 4722: 4718: 4715: 4713: 4710: 4708: 4705: 4703: 4700: 4699: 4697: 4695: 4690: 4686: 4683: 4677: 4673: 4666: 4661: 4659: 4654: 4652: 4647: 4646: 4643: 4635: 4631: 4622: 4617: 4604: 4600: 4597: 4593: 4585: 4579: 4575: 4568: 4560: 4556: 4552: 4548: 4544: 4540: 4535: 4530: 4526: 4522: 4515: 4500: 4494: 4486: 4482: 4476: 4469: 4463: 4447: 4443: 4439: 4433: 4425: 4424:The Economist 4421: 4415: 4408: 4402: 4391: 4389: 4377: 4370: 4368: 4366: 4349: 4348:Markets Media 4345: 4339: 4331: 4327: 4321: 4319: 4311: 4307: 4304: 4299: 4291: 4287: 4283: 4277: 4275: 4273: 4264: 4260: 4254: 4252: 4244: 4240: 4234: 4230: 4227: 4222: 4215: 4210: 4203: 4198: 4190: 4186: 4182: 4175: 4168: 4163: 4156: 4151: 4145: 4139: 4128: 4124: 4120: 4116: 4112: 4107: 4102: 4098: 4094: 4087: 4080: 4066: 4062: 4058: 4052: 4048: 4047: 4039: 4032: 4028: 4024: 4020: 4016: 4012: 4008: 4004: 3997: 3990: 3986: 3983: 3978: 3970: 3964: 3945: 3938: 3932: 3924: 3911: 3903: 3899: 3895: 3891: 3887: 3883: 3876: 3860: 3856: 3850: 3841: 3833: 3820: 3812: 3808: 3804: 3800: 3796: 3792: 3785: 3769: 3763: 3756: 3753: 3748: 3733: 3729: 3723: 3704: 3700: 3699: 3691: 3684: 3677: 3673: 3669: 3668:working paper 3662: 3654: 3648: 3641: 3637: 3633: 3629: 3624: 3619: 3615: 3611: 3607: 3603: 3599: 3592: 3581: 3574: 3568: 3566: 3558: 3554: 3548: 3546: 3537: 3533: 3528: 3523: 3519: 3515: 3511: 3507: 3503: 3499: 3495: 3488: 3473: 3469: 3463: 3455: 3449: 3445: 3441: 3437: 3436: 3428: 3420: 3416: 3412: 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A19 3305: 3301: 3297: 3296:Wilmott, Paul 3291: 3283: 3279: 3272: 3264: 3260: 3253: 3245: 3241: 3236: 3231: 3227: 3223: 3216: 3201: 3197: 3190: 3174: 3170: 3164: 3153: 3146: 3139: 3137: 3128: 3124: 3119: 3114: 3110: 3106: 3102: 3095: 3084: 3078: 3063: 3059: 3052: 3036: 3032: 3026: 3007: 3003: 2996: 2989: 2987: 2971: 2967: 2963: 2959: 2952: 2945: 2943: 2927: 2923: 2916: 2906: 2905: 2897: 2881: 2877: 2876: 2871: 2864: 2850: 2849: 2841: 2834: 2826: 2822: 2815: 2807: 2803: 2796: 2788: 2784: 2777: 2769: 2765: 2758: 2750: 2746: 2739: 2731: 2727: 2720: 2718: 2709: 2702: 2694: 2690: 2683: 2681: 2672: 2671: 2663: 2647: 2643: 2637: 2629: 2628:The Economist 2625: 2619: 2611: 2610:The Economist 2607: 2601: 2594: 2589: 2582: 2577: 2570: 2566: 2562: 2559: 2553: 2551: 2549: 2547: 2545: 2536: 2532: 2526: 2519: 2518: 2511: 2504: 2498: 2492: 2486: 2478: 2471: 2463: 2456: 2448: 2435: 2427: 2421: 2413: 2409: 2405: 2401: 2397: 2393: 2389: 2382: 2374: 2368: 2364: 2360: 2356: 2355: 2347: 2339: 2327: 2312: 2306: 2302: 2301: 2293: 2285: 2281: 2274: 2259: 2255: 2251: 2245: 2237: 2231: 2227: 2220: 2205: 2201: 2197: 2195: 2187: 2180: 2176: 2172: 2168: 2167:, 22(1):1–29" 2166: 2157: 2150:, August 2001 2149: 2142: 2136: 2128: 2124: 2123: 2118: 2111: 2103: 2097: 2093: 2089: 2085: 2081: 2074: 2066: 2062: 2056: 2048: 2044: 2040: 2033: 2025: 2021: 2017: 2013: 2009: 2005: 2001: 1996: 1991: 1987: 1983: 1979: 1972: 1964: 1960: 1956: 1949: 1947: 1945: 1943: 1935: 1931: 1927: 1919: 1913: 1909: 1903: 1901: 1899: 1891: 1886: 1878: 1877:Bloomberg.com 1874: 1867: 1860: 1854: 1852: 1844: 1838: 1832: 1826: 1819: 1813: 1809: 1808: 1800: 1792: 1788: 1782: 1766: 1762: 1761:The Economist 1758: 1752: 1750: 1743: 1737: 1733: 1718: 1711: 1710: 1702: 1698: 1688: 1685: 1683: 1680: 1678: 1675: 1673: 1670: 1668: 1665: 1663: 1660: 1658: 1655: 1653: 1650: 1648: 1645: 1643: 1640: 1638: 1635: 1634: 1628: 1626: 1621: 1617: 1615: 1611: 1607: 1603: 1593: 1591: 1585: 1582: 1579: 1574: 1572: 1566: 1564: 1560: 1554: 1545: 1542: 1537: 1535: 1531: 1526: 1524: 1520: 1511: 1508: 1505: 1504: 1503: 1493: 1490: 1482: 1472: 1468: 1464: 1458: 1457: 1453: 1448:This section 1446: 1442: 1437: 1436: 1428: 1426: 1421: 1417: 1413: 1408: 1406: 1401: 1399: 1398: 1393: 1389: 1383: 1378: 1373: 1369: 1367: 1361: 1357: 1355: 1351: 1347: 1337: 1332: 1330: 1326: 1322: 1316: 1314: 1308: 1304: 1302: 1298: 1292: 1289: 1282: 1279: 1272: 1270: 1264: 1256: 1247: 1245: 1235: 1233: 1229: 1225: 1214: 1211: 1206: 1202: 1197: 1188: 1183: 1173: 1169: 1164: 1154: 1151: 1147: 1143: 1139: 1135: 1126: 1122: 1119: 1115: 1111: 1107: 1097: 1094: 1093:Market making 1088:Market making 1085: 1081: 1079: 1075: 1074:IMC Financial 1071: 1067: 1063: 1059: 1055: 1051: 1047: 1043: 1039: 1038:market makers 1034: 1032: 1025: 1015: 1011: 1008: 1006: 1003:and ensuring 1002: 998: 993: 989: 987: 979:Market timing 976: 974: 969: 966: 961: 960:market making 951: 949: 945: 941: 936: 932: 928: 919: 917: 913: 908: 903: 901: 897: 896:market makers 893: 883: 880: 872: 862: 858: 854: 848: 847: 843: 838:This section 836: 832: 827: 826: 818: 816: 812: 807: 805: 800: 796: 793: 791: 786: 777: 774: 769: 761: 757: 753: 749: 746: 743: 739: 738: 737: 733: 723: 721: 716: 712: 711:market prices 708: 702: 669: 665: 655: 653: 648: 647:delta-neutral 638: 636: 632: 628: 623: 619: 615: 611: 610:Pairs trading 605:Pairs trading 602: 600: 595: 591: 587: 583: 579: 575: 571: 567: 552: 550: 546: 542: 537: 533: 529: 525: 520: 518: 514: 510: 506: 496: 492: 490: 485: 481: 471: 467: 463: 461: 457: 453: 449: 445: 444: 443:Credit Suisse 439: 438: 437:Deutsche Bank 433: 428: 424: 420: 417: 413: 409: 405: 401: 397: 393: 389: 383: 380: 376: 370: 365: 363: 359: 353: 351: 347: 346:market-makers 343: 339: 335: 331: 321: 319: 315: 310: 308: 307:Black–Scholes 304: 300: 295: 293: 289: 285: 280: 278: 273: 269: 254: 253:is provided. 252: 248: 244: 240: 236: 232: 228: 224: 223:market making 220: 215: 213: 209: 205: 200: 198: 194: 190: 189:pension funds 186: 181: 178: 168: 165: 163: 160: 158: 155: 153: 150: 148: 145: 143: 140: 138: 135: 133: 130: 128: 125: 123: 120: 118: 115: 113: 110: 108: 105: 103: 100: 98: 95: 94: 93: 92: 88: 87: 82: 79: 77: 76:Prime brokers 74: 72: 71:Pension funds 69: 67: 64: 62: 59: 57: 54: 52: 49: 47: 46:Credit unions 44: 43: 42: 41: 38:Organisations 37: 36: 33: 30: 29: 26: 22: 5941:Tender offer 5861:Public float 5831:Market trend 5821:Market depth 5641:Growth stock 5615:Buy and hold 5609: 5524:(Cap-to-GDP) 5364:Floor trader 5354:Market maker 5337:Floor broker 5325:Participants 5268:Golden share 5263:Common stock 5239:Third market 4923:Fixed income 4857: 4799:Global macro 4741:Event-driven 4592: 4573: 4567: 4527:(6): 26–39. 4524: 4520: 4514: 4502:. Retrieved 4493: 4484: 4475: 4462: 4450:. Retrieved 4446:the original 4441: 4432: 4423: 4414: 4401: 4352:. Retrieved 4347: 4338: 4329: 4298: 4290:the original 4285: 4262: 4239: 4221: 4209: 4197: 4189:the original 4184: 4174: 4162: 4150: 4138: 4127:the original 4096: 4092: 4079: 4068:, retrieved 4045: 4038: 4009:(6): 68005, 4006: 4002: 3996: 3977: 3951:. Retrieved 3944:the original 3931: 3910:cite journal 3875: 3863:. Retrieved 3859:the original 3849: 3840: 3819:cite journal 3784: 3772:. Retrieved 3762: 3754: 3747: 3736:, retrieved 3731: 3722: 3710:. Retrieved 3703:the original 3696: 3683: 3667: 3661: 3605: 3601: 3591: 3580:the original 3556: 3501: 3497: 3487: 3475:. Retrieved 3471: 3462: 3434: 3427: 3410: 3406: 3393: 3365:Rob Curren, 3361: 3353: 3348: 3337:the original 3332: 3320: 3308:. Retrieved 3303: 3290: 3281: 3271: 3262: 3252: 3225: 3215: 3203:. Retrieved 3199: 3189: 3177:. Retrieved 3172: 3163: 3152:the original 3108: 3104: 3094: 3077: 3065:. Retrieved 3061: 3051: 3039:. 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