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.

1383:"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. 1207:

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.

4637: 558:(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 5167: 5157: 5147: 1452: 842: 5177: 4854: 1040:

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.

252:(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 297:, 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 1634:

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 (

1623:") 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 " 1163:

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

1237:), 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 607:

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

518:, 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. 973:

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".

1282:-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." 945:

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".

502:, 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. 1554:

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.

1603:. 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. 497:

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

1393:"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." 429:

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.

1371:"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." 1512:

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

1388:"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. 1418:, 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. 1434:

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

1214:. 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, 1934:

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",

2049: 1627:") 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. 191:

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

3155: 913:) 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. 4191: 1218:

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

828:, 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. 1318:"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." 256:(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 1988: 636:

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".

986:'s Laboratory for Financial Engineering in 2006. "Everyone is building more sophisticated algorithms, and the more competition exists, the smaller the profits." 729:

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

3708: 2571: 1411:, 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. 4386: 4416:

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).

1438:. However, the report was also criticized for adopting "standard pro-HFT arguments" and advisory panel members being linked to the HFT industry. 526:

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

2718: 1883: 961:, POV, Display size, Liquidity seeker, and Stealth. Modern algorithms are often optimally constructed via either static or dynamic programming. 1901:

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".

2260: 1211: 331:. Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community. 3947: 1922: 1095:

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",

1547:(CEP), which is the heart of decision making in algo-based trading systems, is used for order routing and risk management. 1473: 1059:

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

863: 769:(or, the asset does not have negligible costs of storage; as such, for example, this condition holds for grain but not for 720:: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the 538: 253: 4300: 2472: 1155:

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

4165: 2501: 343:(ECNs) in the 1990s, which allowed for trading of stock and currencies outside of traditional exchanges. In the U.S., 2151: 1499: 1379:(deciding if the news is good or bad) to news stories so that automated trading can work directly on the news story. 889: 522:

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

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

1551: 1477: 1347:

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

1115:

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/

4097:"HENDERSHOTT, TERRENCE, CHARLES M. JONES, AND ALBERT J. MENKVELD. Does Algorithmic Trading Improve Liquidity?" 3093: 2793: 2568: 5463: 1540: 588: 372: 127: 42: 4640: 1330:

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

2437:"Triennial Central Bank Survey of Foreign Exchange and Over-the-counter (OTC) Derivatives Markets in 2019" 5672: 5640: 5544: 5498: 5481: 5434: 4993: 4456: 4237:

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

368: 4430: 3233:"A Pre-Trade Algorithmic Trading Model under Given Volume Measures and Generic Price Dynamics (GVM-GPD)" 2616: 1775: 6002: 5457: 5451: 4704: 4336: 2528:

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

4269: 2634: 1657: 4354: 4116: 3933: 3842: 3608: 2851:"Regulatory Issues Raised by the Impact of Technological Changes on Market Integrity and Efficiency" 2457: 2348: 1127:

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),

2444: 1588: 1430: 1307: 1215: 1084: 637: 600: 515: 462: 348: 257: 4530:

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/

1323: 1116: 1052: 996: 546: 222: 162: 4055: 3992: 2291:"Algorithmic trading & DMA : an introduction to direct access trading strategies" 942:

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

277:

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: 5891: 5836: 5760: 5550: 5379: 5352: 5180: 5086: 5066: 4893: 3778: 2090: 1238: 1220: 641: 494: 490: 4553: 4313: 4025: 3713: 3520: 2831: 2812: 2755: 2014: 1241:

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.

1311: 1173: 1015: 902: 814: 770: 717: 576: 352: 229: 71: 3739:"Citigroup to expand electronic trading capabilities by buying Automated Trading Desk" 3112:"Recommending Cryptocurrency Trading Points with Deep Reinforcement Learning Approach" 2214: 2022: 1425:

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

5795: 5780: 5532: 4814: 4790: 4774: 4588: 4125: 4071: 4061: 3973: 3908: 3904: 3817: 3813: 3682: 3657: 3646: 3624: 3542: 3458: 3425: 3133: 2418: 2398: 2377: 2315: 2240: 2203:"Minimal Intelligence Agents for Bargaining Behaviours in Market-Based Environments, 2106: 1969: 1940: 1822: 1072: 825: 324: 317: 157: 152: 132: 4041: 3377: 2268: 2030: 1224:

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

2410: 2369: 2185: 2098: 2018: 1647: 1581: 1426: 1397:

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),

2399:"The Expanded Implementation Shortfall: Understanding Transaction Cost Components" 724:. When used by academics, an arbitrage is a transaction that involves no negative 533:

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,

1339: 1335: 1160: 1068: 1063:. Among the major U.S. high frequency trading firms are Chicago Trading Company, 499: 466: 410: 385: 294: 287: 245: 195: 167: 86: 76: 4213:

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

2775:"Report examines May's 'flash crash,' expresses concern over high-speed trading" 5926: 5921: 5821: 5806: 5567: 5562: 5527: 5326: 5293: 5239: 5231: 5021: 5001: 4769: 3444: 2512:

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'."

716:

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

2422: 1973: 657: 620: 453: 447: 91: 2436: 2414: 457:). These implementations adopted practices from the investing approaches of 5951: 5871: 5841: 5831: 5651: 5625: 5374: 5364: 5347: 5278: 5273: 5249: 5101: 5056: 4943: 4928: 4809: 3546: 3306: 2189: 1717: 1630: 1600: 1103: 1076: 1048: 970: 917: 906: 721: 662: 545:. The same reports found HFT strategies may have contributed to subsequent 356: 233: 199: 172: 81: 56: 3454: 2373: 5956: 5936: 5916: 5911: 5856: 5745: 5677: 4933: 4873: 4544: 3896: 3805: 3607:

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

3254: 2005: 1573: 1569: 1398: 1298: 1088: 1002: 762: 604: 592: 442: 241: 203: 177: 4561: 4509: 3128: 3111: 1937:

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

5941: 5861: 5538: 5401: 4682: 1007: 596: 559: 313: 207: 4192:"Enter algorithmic trading systems race or lose returns, report warns" 4095:

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

3855:

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

3528: 3503:

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

3411:"Forecasting Shares Trading Signals With Finite State Machine Variant" 493:

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

5577: 5572: 5487: 5406: 4699: 4607: 3891:

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

2794:"$ 4.1-billion trade set off Wall Street 'flash crash,' report finds" 1624: 1415: 1279: 1080: 751:

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

725: 674: 458: 237: 66: 5191: 4853: 4154: 3288: 3269: 3232: 2365:

An Introduction to Algorithmic Trading: Basic to Advanced Strategies

2237:

An Introduction to Algorithmic Trading: Basic to Advanced Strategies

1966:

The Rise of Computerized High Frequency Trading: Use and Controversy

1918: 1841: 1752: 1451: 969:

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

841: 758:

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:

1612: 1156: 783: 293:

With the rise of fully electronic markets came the introduction of

282: 3245: 2832:"Special report: Globally, the flash crash is no flash in the pan" 2641:, vol. 383, no. June 23, 2007, p. 85, June 21, 2007 2488:"Opalesque Exclusive: High-frequency trading under the microscope" 5599: 3446:

2014 IEEE 11th International Conference on e-Business Engineering

3042:"High-Frequency Firms Tripled Trades in Stock Rout, Wedbush Says" 2885: 2311:

Inside the Black Box: The Simple Truth About Quantitative Trading

1635: 1234: 1064: 678: 580: 552:

List of largest daily changes in the Dow Jones Industrial Average

117: 3380:, The Wall Street Journal, August 19, 2008, p. c5. Available at 339:

The financial landscape was changed again with the emergence of

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Journal of Multidisciplinary Engineering Science and Technology

1421:

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

922: 584: 389: 4651: 2473:"Fierce competition forces 'flash' HFT firms into new markets" 1933: 1840:

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

708: 608:

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

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markets are moving toward more access to algorithmic traders.

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

2541: 1884:"CFTC Panel Urges Broad Definition of High-Frequency Trading" 964: 705: 298: 213:

The term algorithmic trading is often used synonymously with

3094:"The Application of Pairs Trading to Energy Futures Markets" 2719:"Automatic Futures Trade Drove May Stock Crash, Report Says" 2173: 1253:

Algorithmic trading has been shown to substantially improve

690: 2152:"Agent-Human Interactions in the Continuous Double Auction" 954: 950: 921:

stipulating their minimum quote obligations. For instance,

747:

Arbitrage is possible when one of three conditions is met:

281:

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

228:

Examples of strategies used in algorithmic trading include

147: 4477:"LSE leads race for quicker trades" by Alistair MacDonald 1528:

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

570: 3397:

Artificial intelligence applied heavily to picking stocks

2653:"Algorithmic Trading Statistics (2024) - Analyzing Alpha" 2604:

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

982:"Now it's an arms race," said Andrew Lo, director of the 696: 403:

International Joint Conference on Artificial Intelligence

398: 4094: 2911: 2362:

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

1903:, February 9, 2012, Commodity Futures Trading Commission 3156:"The Insiders Guide to Trading the World Stock Markets" 2962:"The index premium and its hidden cost for index funds" 221:, some of which are based on formulas and results from 3502: 3109: 1615:") must enable their trading system (often called an " 3337:"Trading with the help of 'guerrillas' and 'snipers'" 2813:"U.S. probes computer algorithms after "flash crash"" 2737:"Lone $ 4.1 Billion Sale Led to 'Flash Crash' in May" 3479:"How To Build Robust Algorithmic Trading Strategies" 3289:"Hybrid IS-VWAP Dynamic Algorithmic Trading via LQR" 995:

include pattern recognition logic implemented using

702: 699: 693: 556:

International Organization of Securities Commissions

3505:"How High Frequency Trading Affects a Market Index" 3442: 3006:"The Weighting Game, and Other Puzzles of Indexing" 2881:"Ultra fast trading needs curbs -global regulators" 2205:

Hewlett-Packard Laboratories Technical Report 97-91

1963: 1536:(OMS), which in turn transmits it to the exchange. 687: 4011: 2756:"Single U.S. trade helped spark May's flash crash" 3676: 3408: 3270:"Styled Algorithmic Trading and the MV-MVP Style" 2172:Gjerstad, Steven; Dickhaut, John (January 1998), 1913: 1911: 1909: 1751:The New Investor, UCLA Law Review, available at: 1532:. Once the order is generated, it is sent to the 509:Algorithmic trading. Percentage of market volume. 5984: 4270:"City trusts computers to keep up with the news" 3799: 2924: 2171: 417:) could consistently out-perform human traders. 305:markets in a strategy known as index arbitrage. 4264: 4262: 3698: 3069:"Americans Want More Social Security, Not Less" 1762: 1760: 1599:interdisciplinary movement is sometimes called 4492:"Milliseconds are focus in algorithmic trades" 1906: 1306:Other issues include the technical problem of 1201: 562:rebalancing transfers profits from investors. 351:by permitting smaller differences between the 5207: 4667: 4355:"U.K. Foresight Study Slammed For HFT 'Bias'" 4323:Automated Trading Desk, accessed July 4, 2007 4053: 3890: 3609:"Does Algorithmic Trading Improve Liquidity?" 2999: 2997: 2050:"Wall Street Taking Another Look at Decimals" 932: 810:price are expected to revert to the average. 4392:. University of Applied Science Haaga-Helia. 4259: 3745:, International Herald Tribune, July 2, 2007 3662:: CS1 maint: multiple names: authors list ( 3365:"Soft Dollars and Other Trading Activities," 2955: 2953: 2872: 2569:The Real Story of Trading Software Espionage 2361: 2234: 2074:. CBS News. January 28, 2001. Archived from 1870:"Soft Dollars and Other Trading Activities," 1864: 1862: 1854:"Soft Dollars and Other Trading Activities," 1757: 5151:Alternative investment management companies 5128:Standards Board for Alternative Investments 4248: 3756: 3034: 3003: 2563: 2561: 2559: 2557: 2555: 2531:. Academic Press, December 3, 2013, p. 258. 2184:, vol. 22, no. 1, pp. 1–29, 2093:. In Lee, Cheng-Few; Lee, Alice C. (eds.). 2091:"Decimal Trading in the U.S. Stock Markets" 1881: 1480:. Unsourced material may be challenged and 1367:, to be read and traded on via algorithms. 870:. Unsourced material may be challenged and 743:Rational pricing § Arbitrage mechanics 736: 651: 5214: 5200: 5176: 5032:Taxation of private equity and hedge funds 4674: 4660: 4387:"Behind the scenes of algorithmic trading" 3558: 3556: 3392: 3390: 3367:§ 2:29 (Thomson West, 2015–2016 ed.). 2994: 2710: 2697: 1872:§ 2:31 (Thomson West, 2015–2016 ed.). 1856:§ 2:30 (Thomson West, 2015–2016 ed.). 1606: 1278:"The downside with these systems is their 1248: 1227: 965:Strategies that only pertain to dark pools 905:is liquidity provision by non-traditional 290:opening price (SOR; Smart Order Routing). 225:, and often rely on specialized software. 4543: 4384: 4287: 4285: 4283: 4115: 3632: 3536: 3244: 3127: 3004:Rekenthaler, John (February–March 2011). 2959: 2950: 2905: 2878: 2485: 2004: 1859: 1500:Learn how and when to remove this message 1028: 890:Learn how and when to remove this message 4331: 4329: 3578: 3576: 2823: 2810: 2804: 2772: 2747: 2635:"Algorithmic trading, Ahead of the tape" 2552: 1986: 1964:McGowan, Michael J. (November 8, 2010). 1110: 504: 334: 327:) for exacerbating or even starting the 4616:FIXatdl version 1.1 released March 2010 4189: 4054:Hult, Henrik; Kiessling, Jonas (2010), 3553: 3387: 3305: 3299: 3204: 2730: 2728: 2693: 2691: 2594:, The New York Times, December 20, 2012 2500:Virtu Financial Form S-1, available at 2396: 2288: 2261:"Algo Arms Race Has a Leader – For Now" 2239:. West Sussex, UK: Wiley. p. 169. 2047: 1814: 1245:have been used to create these models. 1057:U.S. Securities and Exchange Commission 571:Trading ahead of index fund rebalancing 535:U.S. Securities and Exchange Commission 14: 5985: 4532:Computing in Science & Engineering 4529: 4401: 4399: 4380: 4378: 4376: 4280: 4057:Algorithmic trading with Markov chains 3978:: CS1 maint: archived copy as title ( 3692: 3370: 3267: 3153: 3066: 2829: 2811:Younglai, Rachelle (October 5, 2010). 2791: 2785: 2753: 2734: 2470: 2307: 2125: 1441: 1350: 909:, whereby traders attempt to earn (or 5221: 5195: 4732:fixed-income relative-value investing 4655: 4582: 4405: 4326: 3573: 3207:"Market Making in the Electronic Age" 3149: 3147: 2930: 2842: 2830:Spicer, Jonathan (October 15, 2010). 2792:Popper, Nathaniel (October 1, 2010). 2773:Goldfarb, Zachary (October 1, 2010). 2766: 2716: 2314:(1 ed.). John Wiley & Sons. 2235:Leshik, Edward; Cralle, Jane (2011). 2174:"Price Formation in Double Auctions, 1959: 1957: 1955: 1953: 1927: 1815:Kissell, Robert (September 4, 2020), 984:Massachusetts Institute of Technology 451:), Sniper and Guerilla (developed by 425:algorithm had been invented at HP by 401:researchers published a paper at the 359:' trading advantage, thus increasing 272: 4587:. Singapore: John Wiley & Sons. 4190:Skypala, Pauline (October 2, 2006). 3584:"OlsenInvest – Scientific Investing" 3399:by Charles Duhigg, November 23, 2006 3286: 3230: 2754:Spicer, Jonathan (October 1, 2010). 2725: 2688: 2592:Times Topics: High-Frequency Trading 2048:Vinzant, Carol (February 13, 2001). 1552:FIX (Financial Information Exchange) 1478:adding citations to reliable sources 1445: 868:adding citations to reliable sources 835: 603:of the underlying securities in the 539:Commodity Futures Trading Commission 254:Commodity Futures Trading Commission 4396: 4373: 3701:"HFT: Boon? Or Impending Disaster?" 2700:"How a Trading Algorithm Went Awry" 2698:Lauricella, Tom (October 2, 2010). 2606:by Heather Timmons, August 18, 2006 2267:, December 18, 2006, archived from 1010:the inputs in large steps, running 312:was designed to create a synthetic 24: 4225:The Associated Press, July 2, 2007 4180:BBC News, Tuesday 3 November 2009. 4166:Black box traders are on the march 3699:James E. Hollis (September 2013). 3378:Watch Out for Sharks in Dark Pools 3268:Shen, Jackie; Yu, Yingjie (2014). 3144: 2735:Bowley, Graham (October 1, 2010). 2088: 1950: 1405:(appearances included page W15 of 1139: 820:Stock reporting services (such as 30:For trading using algorithms, see 25: 6019: 4622: 4178:Myners' super-fast shares warning 4155:https://ssrn.com/abstract=2227498 3180:"Rules | The Nasdaq Stock Market" 3015:. pp. 52–56 . Archived from 2931:Amery, Paul (November 11, 2010). 2397:Kissell, Robert (June 30, 2006). 2126:Bowley, Graham (April 25, 2011). 1968:. Duke University School of Law. 1919:https://doi.org/10.3390/e22050499 1842:https://ssrn.com/abstract=2417988 1753:https://ssrn.com/abstract=2227498 1260: 1186: 1018:and commission is accounted for. 790: 341:electronic communication networks 248:. Many fall into the category of 5470:Electronic communication network 5175: 5166: 5165: 5156: 5155: 5146: 5145: 4852: 4635: 4601: 4576: 4523: 4502: 4484: 4471: 4441: 4423: 4410: 4347: 4307: 4126:10.1111/j.1540-6261.2010.01624.x 3634:10.1111/j.1540-6261.2010.01624.x 3625:10.1111/j.1540-6261.2010.01624.x 3346:, March 19, 2007, archived from 2072:"Wall Street: Adios, Fractions!" 1450: 1098: 989: 949:Some examples of algorithms are 840: 683: 615: 595:, the most popular of which are 4681: 4230: 4218: 4206: 4183: 4171: 4159: 4147: 4088: 4047: 4005: 3986: 3940: 3884: 3858: 3849: 3793: 3771: 3731: 3670: 3600: 3496: 3471: 3436: 3402: 3357: 3329: 3280: 3261: 3224: 3198: 3172: 3103: 3086: 3060: 2717:Mehta, Nina (October 1, 2010). 2671: 2645: 2627: 2609: 2597: 2585: 2534: 2525:Morton Glantz, Robert Kissell. 2519: 2506: 2494: 2479: 2464: 2429: 2390: 2355: 2308:Narang, R.K. (August 7, 2009). 2301: 2282: 2253: 2228: 2195: 2165: 2144: 2119: 2082: 2064: 2041: 1980: 1726: 1723:) was in increments of eighths. 1710: 1545:complex event processing engine 484: 217:. These encompass a variety of 62:Development finance institution 4641:How algorithms shape our world 4479:The Wall Street Journal Europe 3993:FIXatdl – An Emerging Standard 3311:"Hurrying into the Next Panic" 3067:Siedle, Ted (March 25, 2013). 2681:The Wall Street Journal Europe 2159:IBM T.J.Watson Research Center 2097:. Springer. pp. 719–722. 1894: 1875: 1846: 1834: 1808: 1790: 1745: 1576:, have become very important. 1210:Low-latency traders depend on 589:individual retirement accounts 113:Bull (stock market speculator) 13: 1: 5464:Multilateral trading facility 4168:The Telegraph, 27 August 2006 3564:Rise of the (Market) Machines 2981:10.1016/j.jempfin.2010.10.002 2213:, August 1997, archived from 2023:10.1016/S0370-1573(02)00634-8 1882:Silla Brush (June 20, 2012). 1739: 565: 554:.) A July 2011 report by the 445:), Stealth (developed by the 373:volume-weighted average price 43:Financial market participants 5887:Returns-based style analysis 5683:Post-modern portfolio theory 5589:Security characteristic line 5006:security characteristic line 4337:"Future of computer trading" 2969:Journal of Empirical Finance 2684:, p. 21, April 18, 2007 2486:Opalesque (August 4, 2009). 2265:NYU Stern School of Business 2128:"Preserving a Market Symbol" 2103:10.1007/978-3-030-91231-4_17 1289:Financial Services Authority 929:for each stock represented. 668: 610:Bridgeway Capital Management 7: 5641:Efficient-market hypothesis 5545:Capital asset pricing model 5482:Straight-through processing 4994:Capital asset pricing model 4713:Capital structure arbitrage 4385:Darbellay, Raphaël (2021). 3779:"Quote Stuffing Definition" 3046:Bloomberg/Financial Advisor 2678:"MTS to mull bond access", 2182:S. Gjerstad and J. Dickhaut 2176:Games and Economic Behavior 1818:Algorithmic Trading Methods 1683:Electronic trading platform 1653:Algorithmic tacit collusion 1641: 1621:execution management system 1269: 1202:Low latency trading systems 1167: 831: 755:" is temporarily violated). 591:in the US, are invested in 369:time-weighted average price 10: 6024: 5998:Electronic trading systems 5458:Alternative Trading System 4796:Commodity trading advisors 4319:December 29, 2018, at the 4034:10.1209/0295-5075/82/68005 4002:, FIXGlobal, December 2009 2879:Huw Jones (July 7, 2011). 1663:Alternative trading system 1558: 1550:With the emergence of the 1212:ultra-low latency networks 1190: 1171: 1032: 933:Transaction cost reduction 740: 267: 236:, inter-market spreading, 29: 27:Method of executing orders 5733: 5608: 5507: 5427: 5335: 5302: 5263: 5229: 5141: 5133:Managed Funds Association 5115: 5077:High-net-worth individual 5049: 4957: 4911: 4902: 4861: 4850: 4828: 4783: 4750: 4698: 4689: 4634: 4629: 4449:"InformationWeek Authors" 3384:retrieved August 19, 2008 2960:Petajisto, Antti (2011). 2859:IOSCO Technical Committee 1989:"Critical Market Crashes" 1658:Alpha generation platform 1436:excessive message traffic 627:is a long-short, ideally 5522:Arbitrage pricing theory 4970:Arbitrage pricing theory 4612:August 17, 2013, at the 2471:FT.com (April 3, 2014). 1703: 1678:Complex event processing 1243:Markov chain Monte Carlo 1042:Renaissance Technologies 959:Implementation shortfall 737:Conditions for arbitrage 652:Delta-neutral strategies 520:Foreign exchange markets 308:At about the same time, 215:automated trading system 32:automated trading system 5801:Initial public offering 5662:Modern portfolio theory 5557:Dividend discount model 5440:List of stock exchanges 5082:Institutional investors 4975:Assets under management 4800:managed futures account 4242:August 4, 2012, at the 3568:The Wall Street Journal 3154:Willis, Andrew (2001). 2704:The Wall Street Journal 2516:Retrieved May 22, 2015. 2415:10.3905/jot.2006.644083 2289:Johnson, Barry (2010). 2095:Encyclopedia of Finance 1668:Artificial intelligence 1617:order management system 1607:Communication standards 1534:order management system 1408:The Wall Street Journal 1249:Issues and developments 1228:Strategy implementation 1121:foreign exchange market 1012:Monte Carlo simulations 767:risk-free interest rate 371:or more usually by the 329:1987 stock market crash 279:New York Stock Exchange 5689:Random walk hypothesis 5107:Sovereign wealth funds 4879:High-frequency trading 4728:Fixed income arbitrage 4431:"Business and finance" 3998:March 5, 2020, at the 3928:Cite journal requires 3837:Cite journal requires 3483:AlgorithmicTrading.net 3205:Borelli, Mark (2001). 3168:on September 24, 2021. 2617:"Business and finance" 2452:Cite journal requires 2403:The Journal of Trading 2190:10.1006/game.1997.0576 1768:"Business and finance" 1693:Quantitative investing 1395: 1390: 1385: 1373: 1344: 1320: 1304: 1294: 1284: 1035:High-frequency trading 1029:High-frequency trading 510: 427:Dave Cliff (professor) 382: 320:option pricing model. 250:high-frequency trading 5827:Market capitalization 5636:Dollar cost averaging 4949:Structured securities 4765:Distressed securities 4737:Statistical arbitrage 4723:Equity market neutral 4718:Convertible arbitrage 4583:Brown, Brian (2010). 3866:"Low Latency Trading" 3596:on February 25, 2012. 3455:10.1109/ICEBE.2014.31 3287:Shen, Jackie (2017). 3231:Shen, Jackie (2013). 2574:July 7, 2011, at the 2439:. September 16, 2019. 2374:10.1002/9781119206033 2368:(1 ed.). Wiley. 2217:on September 24, 2015 1589:London Stock Exchange 1431:London Stock Exchange 1391: 1386: 1381: 1369: 1328: 1316: 1297:UK Treasury minister 1295: 1285: 1276: 1111:Statistical arbitrage 997:finite-state machines 803:stochastic equation. 741:Further information: 638:statistical arbitrage 601:market capitalization 516:London Stock Exchange 508: 463:statistical arbitrage 378: 349:market microstructure 335:Refinement and growth 258:market microstructure 194:It is widely used by 5647:Fundamental analysis 5631:Contrarian investing 5594:Security market line 5499:Liquidity aggregator 5476:Direct market access 5387:Quantitative analyst 5067:Financial endowments 5012:Fundamental analysis 4760:Shareholder activism 4742:Volatility arbitrage 4481:, June 19, 2007, p.3 4202:on October 30, 2007. 3897:10.2139/ssrn.1695460 3806:10.2139/ssrn.2193636 3763:Event Arb Definition 3743:The Associated Press 3449:. pp. 126–130. 3255:10.2139/ssrn.2327835 1821:, Elsevier Science, 1541:low-latency networks 1474:improve this section 1324:Knight Capital Group 1117:interest rate parity 1081:Two Sigma Securities 864:improve this section 605:stock or other index 353:bid and offer prices 223:mathematical finance 163:Financial regulation 5993:Algorithmic trading 5892:Reverse stock split 5837:Market manipulation 5761:Dual-listed company 5621:Algorithmic trading 5551:Capital market line 5353:Inter-dealer broker 5181:List of hedge funds 5171:Hedge fund managers 5087:Insurance companies 5072:Fund of hedge funds 4980:Black–Scholes model 4894:Proprietary trading 4869:Algorithmic trading 4836:Fund of hedge funds 4562:10.1109/5992.906615 4554:1999CSE.....1f..26D 4459:on October 22, 2007 4343:. October 23, 2012. 4314:Siemon's Case Study 4196:The Financial Times 4026:2008EL.....8268005P 3768:, September 4, 2010 3521:2013NatSR...3E2110K 3186:. November 23, 2020 3129:10.3390/app10041506 3013:Morningstar Advisor 2893:on January 28, 2016 2580:AdvancedTrading.com 2054:The Washington Post 2015:2003PhR...378....1S 1798:"| Aite Group" 1582:financial exchanges 1442:System architecture 1351:Recent developments 1239:pattern recognition 642:convergence trading 310:portfolio insurance 188:Algorithmic trading 67:Insurance companies 5932:Stock market index 5771:Efficient frontier 5710:Technical analysis 5668:Momentum investing 5490:(private exchange) 5380:Proprietary trader 5322:Shares outstanding 5312:Authorised capital 5037:Technical analysis 4361:. October 30, 2012 4104:Journal of Finance 3613:Journal of Finance 3509:Scientific Reports 3353:on October 7, 2009 3315:The New York Times 2741:The New York Times 2657:analyzingalpha.com 2133:The New York Times 1698:Technical analysis 1322:On August 1, 2012 1221:reverse engineered 1174:Layering (finance) 815:standard deviation 801:Ornstein-Uhlenbeck 579:, such as private 577:retirement savings 511: 273:Early developments 230:systematic trading 219:trading strategies 6003:Financial markets 5980: 5979: 5781:Flight-to-quality 5533:Buffett indicator 5223:Financial markets 5189: 5188: 5045: 5044: 4848: 4847: 4815:Long/short equity 4791:Convergence trade 4775:Special situation 4650: 4649: 4594:978-0-470-82488-7 4303:on July 16, 2011. 4067:978-91-7415-741-3 3709:Cutter Associates 3529:10.1038/srep02110 3464:978-1-4799-6563-2 3309:(July 29, 2009). 3048:. August 12, 2011 2933:"Know Your Enemy" 2798:Los Angeles Times 2546:www.aitegroup.com 2383:978-0-470-68954-7 2321:978-0-470-52914-0 2297:. 4Myeloma Press. 2246:978-0-470-68954-7 2112:978-3-030-91231-4 2078:on June 17, 2024. 2060:on June 17, 2024. 1987:Sornette (2003), 1828:978-0-12-815630-8 1802:www.aitegroup.com 1510: 1509: 1502: 1053:bid–offer spreads 900: 899: 892: 355:, decreasing the 185: 184: 158:Financial planner 153:Financial analyst 148:Banks and banking 133:Corporate finance 16:(Redirected from 6015: 5897:Share repurchase 5609:Trading theories 5494:Crossing network 5452:Over-the-counter 5289:Restricted stock 5245:Secondary market 5216: 5209: 5202: 5193: 5192: 5179: 5178: 5169: 5168: 5159: 5158: 5149: 5148: 5092:Investment banks 4939:Foreign exchange 4909: 4908: 4856: 4696: 4695: 4676: 4669: 4662: 4653: 4652: 4645:TED (conference) 4639: 4638: 4627: 4626: 4617: 4605: 4599: 4598: 4580: 4574: 4573: 4547: 4545:adap-org/9912002 4527: 4521: 4520: 4518: 4516: 4510:"Moving markets" 4506: 4500: 4499: 4488: 4482: 4475: 4469: 4468: 4466: 4464: 4455:. 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Archived from 3588: 3580: 3571: 3562:Geoffrey Rogow, 3560: 3551: 3550: 3540: 3500: 3494: 3493: 3491: 3489: 3475: 3469: 3468: 3440: 3434: 3433: 3415: 3406: 3400: 3394: 3385: 3374: 3368: 3363:Lemke and Lins, 3361: 3355: 3354: 3352: 3341: 3333: 3327: 3326: 3324: 3322: 3303: 3297: 3296: 3284: 3278: 3277: 3265: 3259: 3258: 3248: 3228: 3222: 3221: 3219: 3217: 3202: 3196: 3195: 3193: 3191: 3176: 3170: 3169: 3167: 3161:. Archived from 3160: 3151: 3142: 3141: 3131: 3116:Applied Sciences 3107: 3101: 3100: 3098: 3090: 3084: 3083: 3081: 3079: 3064: 3058: 3057: 3055: 3053: 3038: 3032: 3031: 3029: 3027: 3022:on July 29, 2013 3021: 3010: 3001: 2992: 2991: 2989: 2987: 2966: 2957: 2948: 2947: 2945: 2943: 2937:IndexUniverse.eu 2928: 2922: 2921: 2920: 2909: 2903: 2902: 2900: 2898: 2889:. Archived from 2876: 2870: 2869: 2868: 2866: 2855: 2846: 2840: 2839: 2827: 2821: 2820: 2808: 2802: 2801: 2789: 2783: 2782: 2770: 2764: 2763: 2751: 2745: 2744: 2732: 2723: 2722: 2721:. 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Archived from 2045: 2039: 2038: 2033:, archived from 2008: 2006:cond-mat/0301543 1984: 1978: 1977: 1961: 1948: 1947: 1931: 1925: 1915: 1904: 1898: 1892: 1891: 1879: 1873: 1868:Lemke and Lins, 1866: 1857: 1852:Lemke and Lins, 1850: 1844: 1838: 1832: 1831: 1812: 1806: 1805: 1794: 1788: 1787: 1785: 1783: 1778:on June 22, 2008 1774:. 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May 11, 2007. 4490: 4489: 4485: 4476: 4472: 4462: 4460: 4453:InformationWeek 4447: 4446: 4442: 4429: 4428: 4424: 4415: 4411: 4404: 4397: 4389: 4383: 4374: 4364: 4362: 4353: 4352: 4348: 4335: 4334: 4327: 4321:Wayback Machine 4312: 4308: 4291: 4290: 4281: 4274:Financial Times 4268: 4267: 4260: 4253: 4249: 4244:Wayback Machine 4235: 4231: 4223: 4219: 4211: 4207: 4188: 4184: 4176: 4172: 4164: 4160: 4152: 4148: 4140: 4117:10.1.1.105.7253 4099: 4093: 4089: 4080: 4078: 4068: 4052: 4048: 4010: 4006: 4000:Wayback Machine 3991: 3987: 3971: 3970: 3963: 3961: 3957: 3950: 3948:"Archived copy" 3946: 3945: 3941: 3929: 3927: 3918: 3917: 3889: 3885: 3875: 3873: 3872:on June 2, 2016 3864: 3863: 3859: 3854: 3850: 3838: 3836: 3827: 3826: 3798: 3794: 3784: 3782: 3777: 3776: 3772: 3761: 3757: 3748: 3746: 3737: 3736: 3732: 3722: 3720: 3719:on July 1, 2015 3716: 3703: 3697: 3693: 3675: 3671: 3655: 3654: 3605: 3601: 3593: 3586: 3582: 3581: 3574: 3570:, June 19, 2009 3561: 3554: 3501: 3497: 3487: 3485: 3477: 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Investopedia 3770: 3755: 3730: 3691: 3669: 3599: 3572: 3552: 3495: 3470: 3463: 3435: 3401: 3386: 3369: 3356: 3328: 3298: 3279: 3260: 3223: 3211:heinonline.org 3197: 3171: 3143: 3102: 3085: 3059: 3033: 2993: 2975:(2): 271–288. 2949: 2923: 2904: 2871: 2841: 2822: 2803: 2784: 2765: 2746: 2724: 2709: 2687: 2670: 2659:. May 31, 2021 2644: 2626: 2608: 2596: 2584: 2551: 2533: 2518: 2505: 2493: 2478: 2463: 2454:|journal= 2428: 2389: 2382: 2354: 2345:|website= 2320: 2300: 2281: 2252: 2245: 2227: 2194: 2164: 2143: 2118: 2111: 2081: 2063: 2040: 2037:on May 3, 2010 1979: 1949: 1926: 1905: 1893: 1874: 1858: 1845: 1833: 1827: 1807: 1789: 1756: 1743: 1741: 1738: 1735: 1734: 1725: 1708: 1707: 1705: 1702: 1701: 1700: 1695: 1690: 1688:Mirror trading 1685: 1680: 1675: 1673:Best execution 1670: 1665: 1660: 1655: 1650: 1643: 1640: 1608: 1605: 1560: 1557: 1525: 1524: 1521: 1518: 1508: 1507: 1458: 1456: 1449: 1443: 1440: 1414:In July 2007, 1352: 1349: 1271: 1268: 1262: 1261:Cyborg finance 1259: 1250: 1247: 1229: 1226: 1203: 1200: 1193:Quote stuffing 1191:Main article: 1188: 1187:Quote stuffing 1185: 1172:Main article: 1169: 1166: 1153:risk arbitrage 1141: 1138: 1112: 1109: 1100: 1097: 1033:Main article: 1030: 1027: 991: 988: 966: 963: 934: 931: 898: 897: 848: 846: 839: 833: 830: 822:Yahoo! Finance 796:Mean reversion 792: 791:Mean reversion 789: 779:simultaneously 775: 774: 759: 756: 738: 735: 670: 667: 653: 650: 646:relative value 629:market-neutral 617: 614: 572: 569: 567: 564: 486: 483: 471:mean reversion 377: 345:decimalization 336: 333: 274: 271: 269: 266: 183: 182: 181: 180: 175: 170: 165: 160: 155: 150: 145: 143:Public finance 140: 135: 130: 125: 120: 115: 110: 108:Angel investor 102: 101: 97: 96: 95: 94: 89: 84: 79: 74: 69: 64: 59: 51: 50: 46: 45: 26: 18:Trading system 9: 6: 4: 3: 2: 6020: 6009: 6008:Share trading 6006: 6004: 6001: 5999: 5996: 5994: 5991: 5990: 5988: 5973: 5970: 5968: 5965: 5963: 5960: 5958: 5955: 5953: 5950: 5948: 5945: 5943: 5940: 5938: 5935: 5933: 5930: 5928: 5925: 5923: 5920: 5918: 5915: 5913: 5910: 5908: 5905: 5903: 5902:Short selling 5900: 5898: 5895: 5893: 5890: 5888: 5885: 5883: 5880: 5878: 5875: 5873: 5870: 5868: 5865: 5863: 5860: 5858: 5855: 5853: 5850: 5848: 5845: 5843: 5840: 5838: 5835: 5833: 5830: 5828: 5825: 5823: 5820: 5818: 5815: 5813: 5810: 5808: 5805: 5802: 5799: 5797: 5794: 5792: 5791:Greenspan put 5789: 5787: 5784: 5782: 5779: 5777: 5776:Financial law 5774: 5772: 5769: 5767: 5764: 5762: 5759: 5757: 5754: 5752: 5751:Cross listing 5749: 5747: 5744: 5742: 5739: 5738: 5736: 5734:Related terms 5732: 5726: 5723: 5721: 5718: 5716: 5713: 5711: 5708: 5706: 5705:Swing trading 5703: 5701: 5698: 5696: 5693: 5690: 5687: 5684: 5681: 5679: 5676: 5674: 5673:Mosaic theory 5671: 5669: 5666: 5663: 5660: 5658: 5657:Market timing 5655: 5653: 5650: 5648: 5645: 5642: 5639: 5637: 5634: 5632: 5629: 5627: 5624: 5622: 5619: 5618: 5616: 5614: 5607: 5601: 5598: 5595: 5592: 5590: 5587: 5584: 5581: 5579: 5576: 5574: 5571: 5569: 5566: 5564: 5561: 5558: 5555: 5552: 5549: 5546: 5543: 5540: 5537: 5534: 5531: 5529: 5526: 5523: 5520: 5518: 5515: 5514: 5512: 5510: 5506: 5500: 5497: 5495: 5492: 5489: 5486: 5483: 5480: 5477: 5474: 5471: 5468: 5465: 5462: 5459: 5456: 5453: 5450: 5446: 5445:Trading hours 5443: 5441: 5438: 5437: 5436: 5433: 5432: 5430: 5426: 5420: 5417: 5413: 5410: 5409: 5408: 5405: 5403: 5400: 5398: 5395: 5393: 5390: 5388: 5385: 5381: 5378: 5376: 5373: 5372: 5371: 5368: 5366: 5363: 5361: 5360:Broker-dealer 5358: 5354: 5351: 5349: 5346: 5345: 5344: 5341: 5340: 5338: 5334: 5328: 5325: 5323: 5320: 5318: 5317:Issued shares 5315: 5313: 5310: 5309: 5307: 5305: 5304:Share capital 5301: 5295: 5292: 5290: 5287: 5285: 5282: 5280: 5277: 5275: 5272: 5271: 5269: 5267: 5262: 5256: 5255:Fourth market 5253: 5251: 5248: 5246: 5243: 5241: 5238: 5237: 5235: 5233: 5228: 5224: 5217: 5212: 5210: 5205: 5203: 5198: 5197: 5194: 5182: 5174: 5172: 5164: 5162: 5154: 5152: 5144: 5143: 5140: 5134: 5131: 5129: 5126: 5124: 5121: 5120: 5118: 5114: 5108: 5105: 5103: 5102:Pension funds 5100: 5098: 5095: 5093: 5090: 5088: 5085: 5083: 5080: 5078: 5075: 5073: 5070: 5068: 5065: 5063: 5060: 5058: 5057:Vulture funds 5055: 5054: 5052: 5048: 5038: 5035: 5033: 5030: 5028: 5025: 5023: 5020: 5018: 5015: 5013: 5010: 5007: 5003: 4999: 4995: 4992: 4989: 4988:delta neutral 4985: 4981: 4978: 4976: 4973: 4971: 4968: 4966: 4963: 4962: 4960: 4956: 4950: 4947: 4945: 4944:Money markets 4942: 4940: 4937: 4935: 4932: 4930: 4927: 4925: 4922: 4920: 4917: 4916: 4914: 4910: 4907: 4901: 4895: 4892: 4890: 4887: 4885: 4882: 4880: 4877: 4875: 4872: 4870: 4867: 4866: 4864: 4860: 4855: 4841: 4840:Multi-manager 4837: 4834: 4833: 4831: 4827: 4821: 4818: 4816: 4813: 4811: 4808: 4806: 4803: 4801: 4797: 4794: 4792: 4789: 4788: 4786: 4782: 4776: 4773: 4771: 4768: 4766: 4763: 4761: 4758: 4757: 4755: 4753: 4749: 4743: 4740: 4738: 4735: 4733: 4729: 4726: 4724: 4721: 4719: 4716: 4714: 4711: 4710: 4708: 4706: 4701: 4697: 4694: 4688: 4684: 4677: 4672: 4670: 4665: 4663: 4658: 4657: 4654: 4646: 4642: 4633: 4628: 4615: 4611: 4608: 4604: 4596: 4590: 4586: 4579: 4571: 4567: 4563: 4559: 4555: 4551: 4546: 4541: 4537: 4533: 4526: 4511: 4505: 4497: 4493: 4487: 4480: 4474: 4458: 4454: 4450: 4444: 4436: 4435:The Economist 4432: 4426: 4419: 4413: 4402: 4400: 4388: 4381: 4379: 4377: 4360: 4359:Markets Media 4356: 4350: 4342: 4338: 4332: 4330: 4322: 4318: 4315: 4310: 4302: 4298: 4294: 4288: 4286: 4284: 4275: 4271: 4265: 4263: 4255: 4251: 4245: 4241: 4238: 4233: 4226: 4221: 4214: 4209: 4201: 4197: 4193: 4186: 4179: 4174: 4167: 4162: 4156: 4150: 4139: 4135: 4131: 4127: 4123: 4118: 4113: 4109: 4105: 4098: 4091: 4077: 4073: 4069: 4063: 4059: 4058: 4050: 4043: 4039: 4035: 4031: 4027: 4023: 4019: 4015: 4008: 4001: 3997: 3994: 3989: 3981: 3975: 3956: 3949: 3943: 3935: 3922: 3914: 3910: 3906: 3902: 3898: 3894: 3887: 3871: 3867: 3861: 3852: 3844: 3831: 3823: 3819: 3815: 3811: 3807: 3803: 3796: 3780: 3774: 3767: 3764: 3759: 3744: 3740: 3734: 3715: 3711: 3710: 3702: 3695: 3688: 3684: 3680: 3679:working paper 3673: 3665: 3659: 3652: 3648: 3644: 3640: 3635: 3630: 3626: 3622: 3618: 3614: 3610: 3603: 3592: 3585: 3579: 3577: 3569: 3565: 3559: 3557: 3548: 3544: 3539: 3534: 3530: 3526: 3522: 3518: 3514: 3510: 3506: 3499: 3484: 3480: 3474: 3466: 3460: 3456: 3452: 3448: 3447: 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A19 3316: 3312: 3308: 3307:Wilmott, Paul 3302: 3294: 3290: 3283: 3275: 3271: 3264: 3256: 3252: 3247: 3242: 3238: 3234: 3227: 3212: 3208: 3201: 3185: 3181: 3175: 3164: 3157: 3150: 3148: 3139: 3135: 3130: 3125: 3121: 3117: 3113: 3106: 3095: 3089: 3074: 3070: 3063: 3047: 3043: 3037: 3018: 3014: 3007: 3000: 2998: 2982: 2978: 2974: 2970: 2963: 2956: 2954: 2938: 2934: 2927: 2917: 2916: 2908: 2892: 2888: 2887: 2882: 2875: 2861: 2860: 2852: 2845: 2837: 2833: 2826: 2818: 2814: 2807: 2799: 2795: 2788: 2780: 2776: 2769: 2761: 2757: 2750: 2742: 2738: 2731: 2729: 2720: 2713: 2705: 2701: 2694: 2692: 2683: 2682: 2674: 2658: 2654: 2648: 2640: 2639:The Economist 2636: 2630: 2622: 2621:The Economist 2618: 2612: 2605: 2600: 2593: 2588: 2581: 2577: 2573: 2570: 2564: 2562: 2560: 2558: 2556: 2547: 2543: 2537: 2530: 2529: 2522: 2515: 2509: 2503: 2497: 2489: 2482: 2474: 2467: 2459: 2446: 2438: 2432: 2424: 2420: 2416: 2412: 2408: 2404: 2400: 2393: 2385: 2379: 2375: 2371: 2367: 2366: 2358: 2350: 2338: 2323: 2317: 2313: 2312: 2304: 2296: 2292: 2285: 2270: 2266: 2262: 2256: 2248: 2242: 2238: 2231: 2216: 2212: 2208: 2206: 2198: 2191: 2187: 2183: 2179: 2178:, 22(1):1–29" 2177: 2168: 2161:, August 2001 2160: 2153: 2147: 2139: 2135: 2134: 2129: 2122: 2114: 2108: 2104: 2100: 2096: 2092: 2085: 2077: 2073: 2067: 2059: 2055: 2051: 2044: 2036: 2032: 2028: 2024: 2020: 2016: 2012: 2007: 2002: 1998: 1994: 1990: 1983: 1975: 1971: 1967: 1960: 1958: 1956: 1954: 1946: 1942: 1938: 1930: 1924: 1920: 1914: 1912: 1910: 1902: 1897: 1889: 1888:Bloomberg.com 1885: 1878: 1871: 1865: 1863: 1855: 1849: 1843: 1837: 1830: 1824: 1820: 1819: 1811: 1803: 1799: 1793: 1777: 1773: 1772:The Economist 1769: 1763: 1761: 1754: 1748: 1744: 1729: 1722: 1721: 1713: 1709: 1699: 1696: 1694: 1691: 1689: 1686: 1684: 1681: 1679: 1676: 1674: 1671: 1669: 1666: 1664: 1661: 1659: 1656: 1654: 1651: 1649: 1646: 1645: 1639: 1637: 1632: 1628: 1626: 1622: 1618: 1614: 1604: 1602: 1596: 1593: 1590: 1585: 1583: 1577: 1575: 1571: 1565: 1556: 1553: 1548: 1546: 1542: 1537: 1535: 1531: 1522: 1519: 1516: 1515: 1514: 1504: 1501: 1493: 1483: 1479: 1475: 1469: 1468: 1464: 1459:This section 1457: 1453: 1448: 1447: 1439: 1437: 1432: 1428: 1424: 1419: 1417: 1412: 1410: 1409: 1404: 1400: 1394: 1389: 1384: 1380: 1378: 1372: 1368: 1366: 1362: 1358: 1348: 1343: 1341: 1337: 1333: 1327: 1325: 1319: 1315: 1313: 1309: 1303: 1300: 1293: 1290: 1283: 1281: 1275: 1267: 1258: 1256: 1246: 1244: 1240: 1236: 1225: 1222: 1217: 1213: 1208: 1199: 1194: 1184: 1180: 1175: 1165: 1162: 1158: 1154: 1150: 1146: 1137: 1133: 1130: 1126: 1122: 1118: 1108: 1105: 1104:Market making 1099:Market making 1096: 1092: 1090: 1086: 1085:IMC Financial 1082: 1078: 1074: 1070: 1066: 1062: 1058: 1054: 1050: 1049:market makers 1045: 1043: 1036: 1026: 1022: 1019: 1017: 1014:and ensuring 1013: 1009: 1004: 1000: 998: 990:Market timing 987: 985: 980: 977: 972: 971:market making 962: 960: 956: 952: 947: 943: 939: 930: 928: 924: 919: 914: 912: 908: 907:market makers 904: 894: 891: 883: 873: 869: 865: 859: 858: 854: 849:This section 847: 843: 838: 837: 829: 827: 823: 818: 816: 811: 807: 804: 802: 797: 788: 785: 780: 772: 768: 764: 760: 757: 754: 750: 749: 748: 744: 734: 732: 727: 723: 722:market prices 719: 713: 680: 676: 666: 664: 659: 658:delta-neutral 649: 647: 643: 639: 634: 630: 626: 622: 621:Pairs trading 616:Pairs trading 613: 611: 606: 602: 598: 594: 590: 586: 582: 578: 563: 561: 557: 553: 548: 544: 540: 536: 531: 529: 525: 521: 517: 507: 503: 501: 496: 492: 482: 478: 474: 472: 468: 464: 460: 456: 455: 454:Credit Suisse 450: 449: 448:Deutsche Bank 444: 439: 435: 431: 428: 424: 420: 416: 412: 408: 404: 400: 394: 391: 387: 381: 376: 374: 370: 364: 362: 358: 357:market-makers 354: 350: 346: 342: 332: 330: 326: 321: 319: 318:Black–Scholes 315: 311: 306: 304: 300: 296: 291: 289: 284: 280: 265: 264:is provided. 263: 259: 255: 251: 247: 243: 239: 235: 234:market making 231: 226: 224: 220: 216: 211: 209: 205: 201: 200:pension funds 197: 192: 189: 179: 176: 174: 171: 169: 166: 164: 161: 159: 156: 154: 151: 149: 146: 144: 141: 139: 136: 134: 131: 129: 126: 124: 121: 119: 116: 114: 111: 109: 106: 105: 104: 103: 99: 98: 93: 90: 88: 87:Prime brokers 85: 83: 82:Pension funds 80: 78: 75: 73: 70: 68: 65: 63: 60: 58: 57:Credit unions 55: 54: 53: 52: 49:Organisations 48: 47: 44: 41: 40: 37: 33: 19: 5952:Tender offer 5872:Public float 5842:Market trend 5832:Market depth 5652:Growth stock 5626:Buy and hold 5620: 5535:(Cap-to-GDP) 5375:Floor trader 5365:Market maker 5348:Floor broker 5336:Participants 5279:Golden share 5274:Common stock 5250:Third market 4934:Fixed income 4868: 4810:Global macro 4752:Event-driven 4603: 4584: 4578: 4538:(6): 26–39. 4535: 4531: 4525: 4513:. Retrieved 4504: 4495: 4486: 4473: 4461:. Retrieved 4457:the original 4452: 4443: 4434: 4425: 4412: 4363:. Retrieved 4358: 4349: 4340: 4309: 4301:the original 4296: 4273: 4250: 4232: 4220: 4208: 4200:the original 4195: 4185: 4173: 4161: 4149: 4138:the original 4107: 4103: 4090: 4079:, retrieved 4056: 4049: 4020:(6): 68005, 4017: 4013: 4007: 3988: 3962:. Retrieved 3955:the original 3942: 3921:cite journal 3886: 3874:. Retrieved 3870:the original 3860: 3851: 3830:cite journal 3795: 3783:. Retrieved 3773: 3765: 3758: 3747:, retrieved 3742: 3733: 3721:. Retrieved 3714:the original 3707: 3694: 3678: 3672: 3616: 3612: 3602: 3591:the original 3567: 3512: 3508: 3498: 3486:. Retrieved 3482: 3473: 3445: 3438: 3421: 3417: 3404: 3376:Rob Curren, 3372: 3364: 3359: 3348:the original 3343: 3331: 3319:. Retrieved 3314: 3301: 3292: 3282: 3273: 3263: 3236: 3226: 3214:. Retrieved 3210: 3200: 3188:. Retrieved 3183: 3174: 3163:the original 3119: 3115: 3105: 3088: 3076:. Retrieved 3072: 3062: 3050:. 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