Algorithmic trading
Encyclopedia
In electronic financial markets
, algorithmic trading or automated trading, also known as algo trading, black-box trading or robo trading, is the use of electronic platforms for entering trading orders
with an algorithm
deciding on aspects of the order such as the timing, price, or quantity of the order, or in many cases initiating the order without human intervention.
Algorithmic trading is widely used by pension fund
s, mutual fund
s, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades in order to manage market impact
, and risk. Sell side traders, such as market maker
s and some hedge fund
s, provide liquidity to the market, generating and executing orders automatically.
A special class of algorithmic trading is "high-frequency trading
" (HFT), in which computers make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. This has resulted in a dramatic change of the market microstructure, particularly in the way liquidity is provided.
Algorithmic trading may be used in any investment strategy
, including market making
, inter-market spreading, arbitrage
, or pure speculation
(including trend following
). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically.
A third of all European Union and United States stock trades in 2006 were driven by automatic programs, or algorithms, according to Boston-based financial services industry research and consulting firm Aite Group. As of 2009, HFT firms account for 73% of all US equity trading volume.
In 2006 at the London Stock Exchange
, over 40% of all orders were entered by algo traders, with 60% predicted for 2007. American markets and European markets generally have a higher proportion of algo trades than other markets, and estimates for 2008 range as high as an 80% proportion in some markets. Foreign exchange market
s also have active algo trading (about 25% of orders in 2006). Futures
and options
markets are considered to be fairly easily integrated into algorithmic trading, with about 20% of options volume expected to be computer generated by 2010. Bond
markets are moving toward more access to algorithmic traders.
One of the main issues regarding HFT is the difficulty in determining just how profitable it is. A report released in August 2009 by the TABB Group, a financial services industry research firm, estimated that the 300 securities firms and hedge funds that specialize in this type of trading took in roughly US$21 billion
in profits in 2008.
Algorithmic and HFT have been the subject of much public debate since the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission
implicated them in the 2010 Flash Crash, when the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered. (See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions
(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."
’s “designated order turnaround” system (DOT, and later SuperDOT
) which routed orders electronically to the proper trading post to be executed manually, and the "opening automated reporting system" (OARS) which aided the specialist in determining the market clearing
opening price (SOR; Smart Order Routing).
Program trading
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 this means that all program trades are entered with the aid of a computer. In the 1980s program trading became widely used in trading between the S&P500 equity
and futures
markets.
In stock index arbitrage
a trader buys (or sells) a stock index futures contract such as the S&P 500
futures and sells (or buys) a portfolio of up to 500 stocks (can be a much smaller representative subset) at the NYSE matched against the futures trade. The program trade at the NYSE would be pre-programmed into a computer to enter the order automatically into the NYSE’s electronic order routing system at a time when the futures price and the stock index were far enough apart to make a profit.
At about the same time portfolio insurance
was designed to create a synthetic put option
on a stock portfolio by dynamically trading stock index futures according to a computer model based on the Black–Scholes option pricing model.
Both strategies, often simply lumped together as "program trading", were blamed by many people (for example by the Brady report
) for exacerbating or even starting the 1987 stock market crash. Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.
Financial markets with fully electronic execution and similar electronic communication network
s developed in the late 1980s and 1990s. In the U.S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US$0.0625) to US$0.01 per share, may have encouraged algorithmic trading as it changed the market microstructure
by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.
This increased market liquidity led to institutional traders splitting up orders according to computer algorithms in order to execute their orders at a better average price. These average price benchmarks are measured and calculated by computers by applying the time-weighted average price or more usually by the volume-weighted average price.
A further encouragement for the adoption of algorithmic trading in the financial markets came in 2001 when a team of IBM
researchers published a paper at the International Joint Conference on Artificial Intelligence
where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard
's ZIP) could consistently out-perform human traders. In their paper, the IBM team wrote that the financial impact of their results "...might be measured in billions of dollars annually"; this paper generated international media coverage.
As more electronic markets opened, other algorithmic trading strategies were introduced. These strategies are more easily implemented by computers because machines can react more rapidly to temporary mispricing and examine prices from several markets simultaneously. For example Stealth (developed by the Deutsche Bank
), Sniper and Guerilla (developed by Credit Suisse
), arbitrage
, statistical arbitrage
, trend following
, and mean reversion
.
This type of trading is what is driving the new demand for Low Latency Proximity Hosting and Global Exchange Connectivity. It is imperative to understand what is latency when putting together a strategy for electronic trading. Latency
refers to the delay between the transmission of information from a source and the reception of the information at a destination. Latency has as a lower bound the speed of light; this corresponds to about 3.3 milliseconds per 1,000 kilometers of optical fibre. Any signal regenerating or routing equipment will introduce greater latency than this speed-of-light baseline.
is an investment strategy that tries to take advantage of long-term moves that seem to play out in various markets. The system aims to work on the market trend
mechanism and take benefit from both sides of the market
enjoying the profits from the ups and downs of the stock or futures markets. Traders
who use this approach can use current market price calculation, moving averages and channel
breakouts to determine the general direction of the market and to generate trade signals. Traders who subscribe to a trend following strategy do not aim to forecast or predict specific price levels; they simply jump on the trend and ride it.
or pair trading is a market neutral
trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sidewise movement. This trading strategy is categorized as a statistical arbitrage
and convergence trading strategy.
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 delta components offset, resulting in the portfolio's value being relatively insensitive to changes in the value of the underlying security.
and finance
, arbitrage
(ˈɑrbɨtrɑːʒ) is the practice of taking advantage of a price difference between two or more market
s: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market price
s. When used by academics, an arbitrage is a transaction that involves no negative cash flow
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.
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 transactions must occur simultaneously to avoid 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 each leg of the trade is executed the prices in the market may have moved. Missing one of the legs of the trade (and subsequently having to trade it soon after at a worse price) is called 'execution risk' or more specifically 'leg risk'.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'.
In the simplest example, any good sold in one market should sell for the same price in another. Traders
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 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.
See rational pricing
, particularly arbitrage mechanics, for further discussion.
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.
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 price are expected to revert to the average.
The Standard deviation
of the most recent prices (e.g., the last 20) is often used as a buy or sell indicator.
Stock reporting services (such as Yahoo! Finance, MS Investor, Morningstar, 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.
Mean reversion has the appearance of a more scientific method of choosing stock buy and sell points than charting, because precise numerical values are derived from historical data to identify the buy/sell values, rather than trying to interpret price movements using charts (charting, also known as technical analysis
).
is a method of arbitrage of small price gaps created by the bid-ask spread. Scalpers attempt to act like traditional market makers or specialists. To make the spread means to buy at the bid price and sell at the ask price, to gain the bid/ask difference. This procedure allows for profit even when the bid and ask do not move at all, as long as there are traders who are willing to take market prices. It normally involves establishing and liquidating a position quickly, usually within minutes or even seconds.
The role of a scalper is actually the role of market makers or specialists who are to maintain the liquidity and order flow of a product of a market. A market maker is basically a specialized scalper. The volume a market maker trades are many times more than the average individual scalpers. A market maker has a sophisticated trading system to monitor trading activity. However, a market maker is bound by strict exchange rules while the individual trader is not. For instance, NASDAQ
requires each market maker to post at least one bid and one ask at some price level, so as to maintain a two-sided market for each stock represented.
) and "Sniffer". Yet are at their core quite simple mathematical constructs. Dark pools
are alternative electronic stock exchanges where trading takes place anonymously, with most orders hidden or "iceberged." Gamers or "sharks" sniff 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.
One of the unintended adverse effects of algorithmic trading, has been the dramatic increase in the volume of trade allocations and settlements, as well as the transaction settlement costs associated with them. Since 2004, there have been a number of technological advances and service providers by individuals like Scott Kurland, who have built solutions for aggregating trades executed across algorithms, in order to counter these rising settlement costs.
. High-frequency funds started to become especially popular in 2007 and 2008. Many HFT firms are market makers and provide liquidity to the market which has lowered volatility and helped narrow Bid-offer spread
s making trading and investing cheaper for other market participants. HFT has been a subject of intense public focus since the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission
implicated both algorithmic and HFT in the May 6, 2010 Flash Crash.
High-frequency trading is quantitative trading that is characterized by short portfolio holding periods (see Wilmott (2008), Aldridge (2009)). 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 HFT strategies is largely driven by their ability to simultaneously process volumes of information, something ordinary human traders cannot do.
strategy might involve several securities such as covered interest rate parity
in the foreign exchange market
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 forward contract
on the currency. If the market prices are sufficiently different from those implied in the model to cover transaction cost
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.
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.
Merger arbitrage also called risk arbitrage
would be an example of this. Merger arbitrage generally consists of buying the stock of a company that is the target of a takeover
while shorting 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 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.
by competitors. There is also a very strong pressure to continuously add features or improvements to a particular algorithm, such as client specific modifications and various performance enhancing changes (regarding benchmark trading performance, cost reduction for the trading firm or a range of other implementations). 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 net revenue from firms is spent on the R&D of these autonomous trading systems.
or predictive models can also be used to initiate trading. Neural network
s and genetic programming
have been used to create these models.
among other benefits. However, improvements in productivity brought by algorithmic trading have been opposed by human brokers and traders facing stiff competition from computers.
Other issues include the technical problem of latency
or the delay in getting quotes to traders, security and the possibility of a complete system breakdown leading to a market crash
.
Algorithmic and HFT were implicated in 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 the biggest one-day point decline, 998.5 points, on an intraday basis in Dow Jones Industrial Average history.
, Dow Jones, and Bloomberg
, to be read and traded on via algorithms.
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 sentiment (deciding if the news is good or bad) to news stories so that automated trading can work directly on the news story.
An example of the importance of news reporting speed to algorithmic traders was an advertising
campaign by Dow Jones (appearances included page W15 of the Wall Street Journal, on March 1, 2008) claiming that their service had beaten other news services by 2 seconds in reporting an interest rate cut by the Bank of England.
In July 2007, Citigroup
, 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.
In late 2010, The UK Government Office for Science initiated a Foresight project investigating the future of computer trading in the financial markets, led by Dame Clara Furse, ex-CEO of the London Stock Exchange
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 were subjected to anonymous peer-review. The Foresight project is set to conclude in late 2012.
In September 2011, RYBN has launched "ADM8", an open source Trading Bot prototype, already active on the financial markets.
With the wide use of social networks, some systems implement scanning or screening technologies to read posts of users extracting human sentiment and influence the trading strategies.
s and even microsecond
s, have become very important.
More fully automated markets such as NASDAQ, Direct Edge and BATS, 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 processing fees, and contributed to international mergers and consolidation of financial exchanges
.
Competition is developing among exchanges for the fastest processing times for completing trades. For example, in June 2007, the London Stock Exchange
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. 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.
Spending on computers and software in the financial industry increased to $26.4 billion in 2005.
") must enable their trading system (often called an "order management system
" or "execution management system
") 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 "sell side
") 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.
FIX Protocol
LTD http://www.fixprotocol.org 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 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 (FIXatdl
). The first version of this standard, 1.0 was not widely adopted due to limitations in the specification, but the second version, 1.1 (released in March 2010) is expected to achieve broad adoption and in the process dramatically reduce time-to-market and costs associated with distributing new algorithms.
Electronic trading
Electronic trading, sometimes called etrading, is a method of trading securities , foreign exchange or financial derivatives electronically...
, algorithmic trading or automated trading, also known as algo trading, black-box trading or robo trading, is the use of electronic platforms for entering trading orders
Order (exchange)
An order in a market such as a stock market, bond market, commodity market or financial derivative market is an instruction from customers to brokers to buy or sell on the exchange.These instructions can be simple or complicated...
with an algorithm
Algorithm
In mathematics and computer science, an algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning...
deciding on aspects of the order such as the timing, price, or quantity of the order, or in many cases initiating the order without human intervention.
Algorithmic trading is widely used by pension fund
Pension fund
A pension fund is any plan, fund, or scheme which provides retirement income.Pension funds are important shareholders of listed and private companies. They are especially important to the stock market where large institutional investors dominate. The largest 300 pension funds collectively hold...
s, mutual fund
Mutual fund
A mutual fund is a professionally managed type of collective investment scheme that pools money from many investors to buy stocks, bonds, short-term money market instruments, and/or other securities.- Overview :...
s, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades in order to manage market impact
Market impact
In financial markets, market impact is the effect that a market participant has when it buys or sells an asset. It is the extent to which the buying or selling moves the price against the buyer or seller, i.e. upward when buying and downward when selling...
, and risk. Sell side traders, such as market maker
Market maker
A market maker is a company, or an individual, that quotes both a buy and a sell price in a financial instrument or commodity held in inventory, hoping to make a profit on the bid-offer spread, or turn. From a market microstructure theory standpoint, market makers are net sellers of an option to be...
s and some hedge fund
Hedge fund
A hedge fund is a private pool of capital actively managed by an investment adviser. Hedge funds are only open for investment to a limited number of accredited or qualified investors who meet criteria set by regulators. These investors can be institutions, such as pension funds, university...
s, provide liquidity to the market, generating and executing orders automatically.
A special class of algorithmic trading is "high-frequency trading
High-frequency trading
High-frequency trading is the use of sophisticated technological tools to trade securities like stocks or options, and is typically characterized by several distinguishing features:...
" (HFT), in which computers make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. This has resulted in a dramatic change of the market microstructure, particularly in the way liquidity is provided.
Algorithmic trading may be used in any investment strategy
Investment strategy
In finance, an investment strategy is a set of rules, behaviors or procedures, designed to guide an investor's selection of an investment portfolio...
, including market making
Market maker
A market maker is a company, or an individual, that quotes both a buy and a sell price in a financial instrument or commodity held in inventory, hoping to make a profit on the bid-offer spread, or turn. From a market microstructure theory standpoint, market makers are net sellers of an option to be...
, inter-market spreading, arbitrage
Arbitrage
In economics and finance, arbitrage is the practice of taking advantage of a price difference between two or more markets: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market prices...
, or pure speculation
Speculation
In finance, speculation is a financial action that does not promise safety of the initial investment along with the return on the principal sum...
(including trend following
Trend following
Trend following is an investment strategy that tries to take advantage of long-term moves that seem to play out in various markets. The strategy aims to work on the market trend mechanism and take benefit from both sides of the market, enjoying the profits from the ups and downs of the stock or...
). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically.
A third of all European Union and United States stock trades in 2006 were driven by automatic programs, or algorithms, according to Boston-based financial services industry research and consulting firm Aite Group. As of 2009, HFT firms account for 73% of all US equity trading volume.
In 2006 at the London Stock Exchange
London Stock Exchange
The London Stock Exchange is a stock exchange located in the City of London within the United Kingdom. , the Exchange had a market capitalisation of US$3.7495 trillion, making it the fourth-largest stock exchange in the world by this measurement...
, over 40% of all orders were entered by algo traders, with 60% predicted for 2007. American markets and European markets generally have a higher proportion of algo trades than other markets, and estimates for 2008 range as high as an 80% proportion in some markets. Foreign exchange market
Foreign exchange market
The foreign exchange market is a global, worldwide decentralized financial market for trading currencies. Financial centers around the world function as anchors of trading between a wide range of different types of buyers and sellers around the clock, with the exception of weekends...
s also have active algo trading (about 25% of orders in 2006). Futures
Futures contract
In finance, a futures contract is a standardized contract between two parties to exchange a specified asset of standardized quantity and quality for a price agreed today with delivery occurring at a specified future date, the delivery date. The contracts are traded on a futures exchange...
and options
Option (finance)
In finance, an option is a derivative financial instrument that specifies a contract between two parties for a future transaction on an asset at a reference price. The buyer of the option gains the right, but not the obligation, to engage in that transaction, while the seller incurs the...
markets are considered to be fairly easily integrated into algorithmic trading, with about 20% of options volume expected to be computer generated by 2010. Bond
Bond (finance)
In finance, a bond is a debt security, in which the authorized issuer owes the holders a debt and, depending on the terms of the bond, is obliged to pay interest to use and/or to repay the principal at a later date, termed maturity...
markets are moving toward more access to algorithmic traders.
One of the main issues regarding HFT is the difficulty in determining just how profitable it is. A report released in August 2009 by the TABB Group, a financial services industry research firm, estimated that the 300 securities firms and hedge funds that specialize in this type of trading took in roughly US$21 billion
1000000000 (number)
1,000,000,000 is the natural number following 999,999,999 and preceding 1,000,000,001.In scientific notation, it is written as 109....
in profits in 2008.
Algorithmic and HFT have been the subject of much public debate since the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission
Commodity Futures Trading Commission
The U.S. Commodity Futures Trading Commission is an independent agency of the United States government that regulates futures and option markets....
implicated them in the 2010 Flash Crash, when the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered. (See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions
International Organization of Securities Commissions
The International Organization of Securities Commissions is an association of organisations that regulate the world’s securities and futures markets....
(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."
History
Computerization of the order flow in financial markets began in the early 1970s with some landmarks being the introduction of the New York Stock ExchangeNew York Stock Exchange
The New York Stock Exchange is a stock exchange located at 11 Wall Street in Lower Manhattan, New York City, USA. It is by far the world's largest stock exchange by market capitalization of its listed companies at 13.39 trillion as of Dec 2010...
’s “designated order turnaround” system (DOT, and later SuperDOT
SuperDot
SuperDot was the electronic system used by the New York Stock Exchange to route market orders and limit orders from investors or their agents to a specialist located on the floor of the exchange. SuperDot was the upgraded form of the previous electronic system used to route orders, known as the...
) which routed orders electronically to the proper trading post to be executed manually, and the "opening automated reporting system" (OARS) which aided the specialist in determining the market clearing
Market clearing
In economics, market clearing refers to either# a simplifying assumption made by the new classical school that markets always go to where the quantity supplied equals the quantity demanded; or# the process of getting there via price adjustment....
opening price (SOR; Smart Order Routing).
Program trading
Program trading
Program trading is a generic term used to describe a type of trading in securities, usually consisting of baskets of fifteen stocks or more that are executed by a computer program simultaneously based on predetermined conditions...
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 this means that all program trades are entered with the aid of a computer. In the 1980s program trading became widely used in trading between the S&P500 equity
Stock
The capital stock of a business entity represents the original capital paid into or invested in the business by its founders. It serves as a security for the creditors of a business since it cannot be withdrawn to the detriment of the creditors...
and futures
Futures contract
In finance, a futures contract is a standardized contract between two parties to exchange a specified asset of standardized quantity and quality for a price agreed today with delivery occurring at a specified future date, the delivery date. The contracts are traded on a futures exchange...
markets.
In stock index arbitrage
Index arbitrage
Index arbitrage is a subset of statistical arbitrage focusing on index components.The idea is that an index is made up of several components that influence the index price in a different manner.For instance, there are leaders...
a trader buys (or sells) a stock index futures contract such as the S&P 500
S&P 500
The S&P 500 is a free-float capitalization-weighted index published since 1957 of the prices of 500 large-cap common stocks actively traded in the United States. The stocks included in the S&P 500 are those of large publicly held companies that trade on either of the two largest American stock...
futures and sells (or buys) a portfolio of up to 500 stocks (can be a much smaller representative subset) at the NYSE matched against the futures trade. The program trade at the NYSE would be pre-programmed into a computer to enter the order automatically into the NYSE’s electronic order routing system at a time when the futures price and the stock index were far enough apart to make a profit.
At about the same time portfolio insurance
Constant proportion portfolio insurance
Constant proportion portfolio insurance is a capital guarantee derivative security that embeds a dynamic trading strategy in order to provide participation to the performance of a certain underlying asset. See also dynamic asset allocation...
was designed to create a synthetic put option
Put option
A put or put option is a contract between two parties to exchange an asset, the underlying, at a specified price, the strike, by a predetermined date, the expiry or maturity...
on a stock portfolio by dynamically trading stock index futures according to a computer model based on the Black–Scholes option pricing model.
Both strategies, often simply lumped together as "program trading", were blamed by many people (for example by the Brady report
Nicholas F. Brady
Nicholas Frederick Brady was United States Secretary of the Treasury under Presidents Ronald Reagan and George H. W. Bush, and is also known for articulating the Brady Plan in March 1989.-Early life:...
) for exacerbating or even starting the 1987 stock market crash. Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.
Financial markets with fully electronic execution and similar electronic communication network
Electronic communication network
An electronic communication network is the term used in financial circles for a type of computer system that facilitates trading of financial products outside of stock exchanges. The primary products that are traded on ECNs are stocks and currencies. The first ECN, Instinet, was created in 1969...
s developed in the late 1980s and 1990s. In the U.S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US$0.0625) to US$0.01 per share, may have encouraged algorithmic trading as it changed the market microstructure
Market microstructure
Market microstructure is a branch of finance concerned with the details of how exchange occurs in markets. While the theory of market microstructure applies to the exchange of real or financial assets, more evidence is available on the microstructure of financial markets due to the availability of...
by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.
This increased market liquidity led to institutional traders splitting up orders according to computer algorithms in order to execute their orders at a better average price. These average price benchmarks are measured and calculated by computers by applying the time-weighted average price or more usually by the volume-weighted average price.
A further encouragement for the adoption of algorithmic trading in the financial markets came in 2001 when a team of IBM
IBM
International Business Machines Corporation or IBM is an American multinational technology and consulting corporation headquartered in Armonk, New York, United States. IBM manufactures and sells computer hardware and software, and it offers infrastructure, hosting and consulting services in areas...
researchers published a paper at the International Joint Conference on Artificial Intelligence
International Joint Conference on Artificial Intelligence
The International Joint Conference on Artificial Intelligence is a meeting of researchers from the different areas of artificial intelligence . It is organized by the IJCAI, Inc., and has been held every other year since 1969. Originally, the other years saw the meetings of the ECAI, AAAI, and a...
where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard
Hewlett-Packard
Hewlett-Packard Company or HP is an American multinational information technology corporation headquartered in Palo Alto, California, USA that provides products, technologies, softwares, solutions and services to consumers, small- and medium-sized businesses and large enterprises, including...
's ZIP) could consistently out-perform human traders. In their paper, the IBM team wrote that the financial impact of their results "...might be measured in billions of dollars annually"; this paper generated international media coverage.
As more electronic markets opened, other algorithmic trading strategies were introduced. These strategies are more easily implemented by computers because machines can react more rapidly to temporary mispricing and examine prices from several markets simultaneously. For example Stealth (developed by the Deutsche Bank
Deutsche Bank
Deutsche Bank AG is a global financial service company with its headquarters in Frankfurt, Germany. It employs more than 100,000 people in over 70 countries, and has a large presence in Europe, the Americas, Asia Pacific and the emerging markets...
), Sniper and Guerilla (developed by Credit Suisse
Credit Suisse
The Credit Suisse Group AG is a Swiss multinational financial services company headquartered in Zurich, with more than 250 branches in Switzerland and operations in more than 50 countries.-History:...
), arbitrage
Arbitrage
In economics and finance, arbitrage is the practice of taking advantage of a price difference between two or more markets: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market prices...
, statistical arbitrage
Statistical arbitrage
In the world of finance and investments, statistical arbitrage is used in two related but distinct ways:* In academic literature, "statistical arbitrage" is opposed to arbitrage. In deterministic arbitrage, a sure profit can be obtained from being long some securities and short others...
, trend following
Trend following
Trend following is an investment strategy that tries to take advantage of long-term moves that seem to play out in various markets. The strategy aims to work on the market trend mechanism and take benefit from both sides of the market, enjoying the profits from the ups and downs of the stock or...
, and mean reversion
Mean reversion
Mean reversion is a mathematical concept sometimes used for stock investing, but it can be applied to other assets. In general terms, the essence of the concept is the assumption that both a stock's high and low prices are temporary and that a stock's price will tend to move to the average price...
.
This type of trading is what is driving the new demand for Low Latency Proximity Hosting and Global Exchange Connectivity. It is imperative to understand what is latency when putting together a strategy for electronic trading. Latency
Latency (engineering)
Latency is a measure of time delay experienced in a system, the precise definition of which depends on the system and the time being measured. Latencies may have different meaning in different contexts.-Packet-switched networks:...
refers to the delay between the transmission of information from a source and the reception of the information at a destination. Latency has as a lower bound the speed of light; this corresponds to about 3.3 milliseconds per 1,000 kilometers of optical fibre. Any signal regenerating or routing equipment will introduce greater latency than this speed-of-light baseline.
Trend following
Trend followingTrend following
Trend following is an investment strategy that tries to take advantage of long-term moves that seem to play out in various markets. The strategy aims to work on the market trend mechanism and take benefit from both sides of the market, enjoying the profits from the ups and downs of the stock or...
is an investment strategy that tries to take advantage of long-term moves that seem to play out in various markets. The system aims to work on the market trend
Market trends
A market trend is a putative tendency of a financial market to move in a particular direction over time. These trends are classified as secular for long time frames, primary for medium time frames, and secondary for short time frames...
mechanism and take benefit from both sides of the market
Financial instruments
A financial instrument is a tradable asset of any kind, either cash; evidence of an ownership interest in an entity; or a contractual right to receive, or deliver, cash or another financial instrument....
enjoying the profits from the ups and downs of the stock or futures markets. Traders
Trader (finance)
A trader is someone in finance who buys and sells financial instruments such as stocks, bonds, commodities and derivatives. A broker who simply fills buy or sell orders is not a trader, as they are merely executing instructions given to them. According to the Wall Street Journal in 2004, a managing...
who use this approach can use current market price calculation, moving averages and channel
Price channels
A price channel is a pair of parallel trend lines that form a chart pattern for a stock or commodity. Channels may be horizontal, ascending or descending. When prices pass through and stay through a trendline representing support or resistance, the trend is said to be broken and there is a...
breakouts to determine the general direction of the market and to generate trade signals. Traders who subscribe to a trend following strategy do not aim to forecast or predict specific price levels; they simply jump on the trend and ride it.
Pair trading
The pairs tradePairs trade
The pairs trade or pair trading is a market neutral trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sideways movement. This strategy is categorized as a statistical arbitrage and convergence trading strategy...
or pair trading is a market neutral
Market neutral
An investment strategy or portfolio is considered market neutral if it seeks to entirely avoid some form of market risk, typically by hedging. In order to evaluate market neutrality, it is first necessary to specify the risk being avoided...
trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sidewise movement. This trading strategy is categorized as a statistical arbitrage
Statistical arbitrage
In the world of finance and investments, statistical arbitrage is used in two related but distinct ways:* In academic literature, "statistical arbitrage" is opposed to arbitrage. In deterministic arbitrage, a sure profit can be obtained from being long some securities and short others...
and convergence trading strategy.
Delta neutral strategies
In finance, delta neutralDelta neutral
In finance, delta neutral 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...
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 delta components offset, resulting in the portfolio's value being relatively insensitive to changes in the value of the underlying security.
Arbitrage
In economicsEconomics
Economics is the social science that analyzes the production, distribution, and consumption of goods and services. The term economics comes from the Ancient Greek from + , hence "rules of the house"...
and finance
Finance
"Finance" is often defined simply as the management of money or “funds” management Modern finance, however, is a family of business activity that includes the origination, marketing, and management of cash and money surrogates through a variety of capital accounts, instruments, and markets created...
, arbitrage
Arbitrage
In economics and finance, arbitrage is the practice of taking advantage of a price difference between two or more markets: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market prices...
(ˈɑrbɨtrɑːʒ) is the practice of taking advantage of a price difference between two or more market
Market
A market is one of many varieties of systems, institutions, procedures, social relations and infrastructures whereby parties engage in exchange. While parties may exchange goods and services by barter, most markets rely on sellers offering their goods or services in exchange for money from buyers...
s: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market price
Market price
In economics, market price is the economic price for which a good or service is offered in the marketplace. It is of interest mainly in the study of microeconomics...
s. When used by academics, an arbitrage is a transaction that involves no negative cash flow
Cash flow
Cash flow is the movement of money into or out of a business, project, or financial product. It is usually measured during a specified, finite period of time. Measurement of cash flow can be used for calculating other parameters that give information on a company's value and situation.Cash flow...
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.
Conditions for arbitrage
Arbitrage is possible when one of three conditions is met:- The same asset does not trade at the same price on all markets (the "law of one priceLaw of one priceThe law of one price is an economic law stated as: "In an efficient market, all identical goods must have only one price."-Intuition:The intuition for this law is that all sellers will flock to the highest prevailing price, and all buyers to the lowest current market price. In an efficient market...
"). - Two assets with identical cash flows do not trade at the same price.
- An asset with a known price in the future does not today trade at its future price discounted at the risk-free interest rateRisk-free interest rateRisk-free interest rate is the theoretical rate of return of an investment with no risk of financial loss. The risk-free rate represents the interest that an investor would expect from an absolutely risk-free investment over a given period of time....
(or, the asset does not have negligible costs of storage; as such, for example, this condition holds for grain but not for securitiesSecurity (finance)A security is generally a fungible, negotiable financial instrument representing financial value. Securities are broadly categorized into:* debt securities ,* equity securities, e.g., common stocks; and,...
).
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 transactions must occur simultaneously to avoid 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 each leg of the trade is executed the prices in the market may have moved. Missing one of the legs of the trade (and subsequently having to trade it soon after at a worse price) is called 'execution risk' or more specifically 'leg risk'.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'.
In the simplest example, any good sold in one market should sell for the same price in another. Traders
Merchant
A merchant is a businessperson who trades in commodities that were produced by others, in order to earn a profit.Merchants can be one of two types:# A wholesale merchant operates in the chain between producer and retail merchant...
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 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.
See rational pricing
Rational pricing
Rational pricing is the assumption in financial economics that asset prices will reflect the arbitrage-free price of the asset as any deviation from this price will be "arbitraged away"...
, particularly arbitrage mechanics, for further discussion.
Mean reversion
Mean reversion 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 will tend to have an average price over time.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.
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 price are expected to revert to the average.
The Standard deviation
Standard deviation
Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or "dispersion" there is from the average...
of the most recent prices (e.g., the last 20) is often used as a buy or sell indicator.
Stock reporting services (such as Yahoo! Finance, MS Investor, Morningstar, 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.
Mean reversion has the appearance of a more scientific method of choosing stock buy and sell points than charting, because precise numerical values are derived from historical data to identify the buy/sell values, rather than trying to interpret price movements using charts (charting, also known as technical analysis
Technical analysis
In finance, technical analysis is security analysis discipline for forecasting the direction of prices through the study of past market data, primarily price and volume. Behavioral economics and quantitative analysis incorporate technical analysis, which being an aspect of active management stands...
).
Scalping
Scalping (trading)Scalping (trading)
Scalping, when used in reference to trading in securities, commodities and foreign exchange, may refer to# a fraudulent form of market manipulation# a legitimate method of arbitrage of small price gaps created by the bid-ask spread....
is a method of arbitrage of small price gaps created by the bid-ask spread. Scalpers attempt to act like traditional market makers or specialists. To make the spread means to buy at the bid price and sell at the ask price, to gain the bid/ask difference. This procedure allows for profit even when the bid and ask do not move at all, as long as there are traders who are willing to take market prices. It normally involves establishing and liquidating a position quickly, usually within minutes or even seconds.
The role of a scalper is actually the role of market makers or specialists who are to maintain the liquidity and order flow of a product of a market. A market maker is basically a specialized scalper. The volume a market maker trades are many times more than the average individual scalpers. A market maker has a sophisticated trading system to monitor trading activity. However, a market maker is bound by strict exchange rules while the individual trader is not. For instance, NASDAQ
NASDAQ
The NASDAQ Stock Market, also known as the NASDAQ, is an American stock exchange. "NASDAQ" originally stood for "National Association of Securities Dealers Automated Quotations". It is the second-largest stock exchange by market capitalization in the world, after the New York Stock Exchange. As of...
requires each market maker to post at least one bid and one ask at some price level, so as to maintain a two-sided market for each stock represented.
Transaction cost reduction
Most strategies referred to as algorithmic trading (as well as algorithmic liquidity seeking) fall into the cost-reduction category. Large orders are broken down into several smaller orders and entered into the market over time. This basic strategy is called "iceberging". The success of this strategy may be measured by the average purchase price against the volume-weighted average price for the market over that time period. One algorithm designed to find hidden orders or icebergs is called "Stealth". Most of these strategies were first documented in 'Optimal Trading Strategies' by Robert Kissell.Strategies that only pertain to dark pools
Recently, HFT, which comprises a broad set of buy-side as well as market making 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", "Guerrilla", "Sniper", "BASOR" (developed by Quod FinancialQuod Financial
Quod Financial is a privately owned adaptive trading technology provider which specialises in software and services such as algorithmic trading, smart order routing and of liquidity. The firm provides electronic trading solutions to liquidity venues, exchanges, retail brokers, buy side and sell...
) and "Sniffer". Yet are at their core quite simple mathematical constructs. Dark pools
Dark liquidity
In finance, dark pools of liquidity also referred to as dark liquidity or simply dark pools is trading volume or liquidity that is not openly available to the public. The bulk of these represent large trades by financial institutions that are offered away from public exchanges so that trades are...
are alternative electronic stock exchanges where trading takes place anonymously, with most orders hidden or "iceberged." Gamers or "sharks" sniff 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.
“Now it’s an arms race,” said Andrew Lo, director of the Massachusetts Institute of TechnologyMassachusetts Institute of TechnologyThe Massachusetts Institute of Technology is a private research university located in Cambridge, Massachusetts. MIT has five schools and one college, containing a total of 32 academic departments, with a strong emphasis on scientific and technological education and research.Founded in 1861 in...
’s Laboratory for Financial Engineering. “Everyone is building more sophisticated algorithms, and the more competition exists, the smaller the profits.”
One of the unintended adverse effects of algorithmic trading, has been the dramatic increase in the volume of trade allocations and settlements, as well as the transaction settlement costs associated with them. Since 2004, there have been a number of technological advances and service providers by individuals like Scott Kurland, who have built solutions for aggregating trades executed across algorithms, in order to counter these rising settlement costs.
High-frequency trading
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 Renaissance TechnologiesRenaissance Technologies
Renaissance Technologies is a hedge fund management company of about 275 employees and more than $ billion in assets under management in three funds...
. High-frequency funds started to become especially popular in 2007 and 2008. Many HFT firms are market makers and provide liquidity to the market which has lowered volatility and helped narrow Bid-offer spread
Bid-offer spread
The bid–offer spread for securities is the difference between the prices quoted for an immediate sale and an immediate purchase...
s making trading and investing cheaper for other market participants. HFT has been a subject of intense public focus since the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission
Commodity Futures Trading Commission
The U.S. Commodity Futures Trading Commission is an independent agency of the United States government that regulates futures and option markets....
implicated both algorithmic and HFT in the May 6, 2010 Flash Crash.
High-frequency trading is quantitative trading that is characterized by short portfolio holding periods (see Wilmott (2008), Aldridge (2009)). 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 HFT strategies is largely driven by their ability to simultaneously process volumes of information, something ordinary human traders cannot do.
Market making
Market making is a set of HFT strategies that 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 in order to benefit from the bid-ask spread. Automated Trading Desk, which was bought by Citigroup in July 2007, has been an active market maker, accounting for about 6% of total volume on both NASDAQ and the New York Stock Exchange.Statistical arbitrage
Another set of HFT strategies is classical arbitrageArbitrage
In economics and finance, arbitrage is the practice of taking advantage of a price difference between two or more markets: striking a combination of matching deals that capitalize upon the imbalance, the profit being the difference between the market prices...
strategy might involve several securities such as covered interest rate parity
Interest rate parity
Interest rate parity is a no-arbitrage condition representing an equilibrium state under which investors will be indifferent to interest rates available on bank deposits in two countries. Two assumptions central to interest rate parity are capital mobility and perfect substitutability of domestic...
in the foreign exchange market
Foreign exchange market
The foreign exchange market is a global, worldwide decentralized financial market for trading currencies. Financial centers around the world function as anchors of trading between a wide range of different types of buyers and sellers around the clock, with the exception of weekends...
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 forward contract
Forward contract
In finance, a forward contract or simply a forward is a non-standardized contract between two parties to buy or sell an asset at a specified future time at a price agreed today. This is in contrast to a spot contract, which is an agreement to buy or sell an asset today. It costs nothing to enter a...
on the currency. If the market prices are sufficiently different from those implied in the model to cover transaction cost
Transaction cost
In economics and related disciplines, a transaction cost is a cost incurred in making an economic exchange . For example, most people, when buying or selling a stock, must pay a commission to their broker; that commission is a transaction cost of doing the stock deal...
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.
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.
Event arbitrage
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 profit.Merger arbitrage also called risk arbitrage
Risk arbitrage
Risk arbitrage, or merger arbitrage, is an investment or trading strategy often associated with hedge funds.Two principal types of merger are possible: a cash merger, and a stock merger. In a cash merger, an acquirer proposes to purchase the shares of the target for a certain price in cash...
would be an example of this. Merger arbitrage generally consists of buying the stock of a company that is the target of a takeover
Takeover
In business, a takeover is the purchase of one company by another . In the UK, the term refers to the acquisition of a public company whose shares are listed on a stock exchange, in contrast to the acquisition of a private company.- Friendly takeovers :Before a bidder makes an offer for another...
while shorting 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 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.
Low-latency trading
HFT is often confused with low-latency trading that uses computers that execute trades within milliseconds, or "with extremely low latency" in the jargon of the trade. Low-latency trading is highly dependent on ultra-low latency networks. 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, colocated trading platform in order 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 reverse engineeredReverse engineering
Reverse engineering is the process of discovering the technological principles of a device, object, or system through analysis of its structure, function, and operation...
by competitors. There is also a very strong pressure to continuously add features or improvements to a particular algorithm, such as client specific modifications and various performance enhancing changes (regarding benchmark trading performance, cost reduction for the trading firm or a range of other implementations). 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 net revenue from firms is spent on the R&D of these autonomous trading systems.
Strategy implementation
Most of the algorithmic strategies are implemented using modern programming languages, although some still implement strategies designed in spreadsheets. Basic models can rely on as little as a linear regression, while more complex game-theoretic and pattern recognitionPattern recognition
In machine learning, pattern recognition is the assignment of some sort of output value to a given input value , according to some specific algorithm. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes...
or predictive models can also be used to initiate trading. Neural network
Neural network
The term neural network was traditionally used to refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes...
s and genetic programming
Genetic programming
In artificial intelligence, genetic programming is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms where each individual is a computer program...
have been used to create these models.
Issues and developments
Algorithmic trading has been shown to substantially improve market liquidityMarket liquidity
In business, economics or investment, market liquidity is an asset's ability to be sold without causing a significant movement in the price and with minimum loss of value...
among other benefits. However, improvements in productivity brought by algorithmic trading have been opposed by human brokers and traders facing stiff competition from computers.
Concerns
“The downside with these systems is their black box-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.”
“The Financial Services AuthorityFinancial Services AuthorityThe Financial Services Authority is a quasi-judicial body responsible for the regulation of the financial services industry in the United Kingdom. Its board is appointed by the Treasury and the organisation is structured as a company limited by guarantee and owned by the UK government. Its main...
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 it a greater risk that systems failure can result in business interruption’.”
UK Treasury minister Lord Myners 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.
Other issues include the technical problem of latency
Latency (engineering)
Latency is a measure of time delay experienced in a system, the precise definition of which depends on the system and the time being measured. Latencies may have different meaning in different contexts.-Packet-switched networks:...
or the delay in getting quotes to traders, security and the possibility of a complete system breakdown leading to a market crash
Stock market crash
A stock market crash is a sudden dramatic decline of stock prices across a significant cross-section of a stock market, resulting in a significant loss of paper wealth. Crashes are driven by panic as much as by underlying economic factors...
.
"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."
Algorithmic and HFT were implicated in 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 the biggest one-day point decline, 998.5 points, on an intraday basis in Dow Jones Industrial Average history.
Recent developments
Financial market news is now being formatted by firms such as Need To Know News, Thomson ReutersThomson Reuters
Thomson Reuters Corporation is a provider of information for the world's businesses and professionals and is created by the Thomson Corporation's purchase of Reuters Group on 17 April 2008. Thomson Reuters is headquartered at 3 Times Square, New York City, USA...
, Dow Jones, and Bloomberg
Bloomberg L.P.
Bloomberg L.P. is an American privately held financial software, media, and data company. Bloomberg makes up one third of the $16 billion global financial data market with estimated revenue of $6.9 billion. Bloomberg L.P...
, to be read and traded on via algorithms.
"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."
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 sentiment (deciding if the news is good or bad) to news stories so that automated trading can work directly on the news story.
"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.
"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.
“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."
An example of the importance of news reporting speed to algorithmic traders was an advertising
Advertising
Advertising is a form of communication used to persuade an audience to take some action with respect to products, ideas, or services. Most commonly, the desired result is to drive consumer behavior with respect to a commercial offering, although political and ideological advertising is also common...
campaign by Dow Jones (appearances included page W15 of the Wall Street Journal, on March 1, 2008) claiming that their service had beaten other news services by 2 seconds in reporting an interest rate cut by the Bank of England.
In July 2007, Citigroup
Citigroup
Citigroup Inc. or Citi is an American multinational financial services corporation headquartered in Manhattan, New York City, New York, United States. Citigroup was formed from one of the world's largest mergers in history by combining the banking giant Citicorp and financial conglomerate...
, 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.
In late 2010, The UK Government Office for Science initiated a Foresight project investigating the future of computer trading in the financial markets, led by Dame Clara Furse, ex-CEO of the London Stock Exchange
London Stock Exchange
The London Stock Exchange is a stock exchange located in the City of London within the United Kingdom. , the Exchange had a market capitalisation of US$3.7495 trillion, making it the fourth-largest stock exchange in the world by this measurement...
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 were subjected to anonymous peer-review. The Foresight project is set to conclude in late 2012.
In September 2011, RYBN has launched "ADM8", an open source Trading Bot prototype, already active on the financial markets.
Technical design
The technical designs of such systems are not standardized. Conceptually, the design can be divided into logical units:- The data stream unit (the part of the systems that receives data (e.g. quotes, news) from external sources).
- The decision or strategy unit
- The execution unit.
With the wide use of social networks, some systems implement scanning or screening technologies to read posts of users extracting human sentiment and influence the trading strategies.
Effects
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 millisecondMillisecond
A millisecond is a thousandth of a second.10 milliseconds are called a centisecond....
s and even microsecond
Microsecond
A microsecond is an SI unit of time equal to one millionth of a second. Its symbol is µs.A microsecond is equal to 1000 nanoseconds or 1/1000 millisecond...
s, have become very important.
More fully automated markets such as NASDAQ, Direct Edge and BATS, 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 processing fees, and contributed to international mergers and consolidation of financial exchanges
Financial market
In economics, a financial market is a mechanism that allows people and entities to buy and sell financial securities , commodities , and other fungible items of value at low transaction costs and at prices that reflect supply and demand.Both general markets and...
.
Competition is developing among exchanges for the fastest processing times for completing trades. For example, in June 2007, the London Stock Exchange
London Stock Exchange
The London Stock Exchange is a stock exchange located in the City of London within the United Kingdom. , the Exchange had a market capitalisation of US$3.7495 trillion, making it the fourth-largest stock exchange in the world by this measurement...
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. 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.
Spending on computers and software in the financial industry increased to $26.4 billion in 2005.
Communication standards
Algorithmic trades require communicating considerably more parameters than traditional market and limit orders. A trader on one end (the "buy sideBuy side
Buy-side is a term used in investment banking to refer to advising institutions concerned with buying, rather than selling, assets or securities...
") must enable their trading system (often called an "order management system
Order management system
An order management system, or OMS, is a computer software system used in a number of industries for order entry and processing.- Electronic commerce and catalogers :...
" or "execution management system
Execution management system
Execution management systems are software applications utilized by institutional traders designed to display market data and provide seamless access to trading destinations fast for the purpose of transacting orders. They contain broker provided and independent algorithms, global market data and...
") 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 "sell side
Sell side
Sell side is a term used in the financial services industry. It is a general term that indicates a firm that sells investment services to asset management firms, typically referred to as the buy side, or corporate entities...
") 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.
FIX Protocol
FIX protocol
The Financial Information eXchange protocol is an electronic communications protocol initiated in 1992 for international real-time exchange of information related to the securities transactions and markets...
LTD http://www.fixprotocol.org 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 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 (FIXatdl
FIXatdl
FIXatdl is a standard for the exchange of meta-information required to enable algorithmic trading activity within the financial markets...
). The first version of this standard, 1.0 was not widely adopted due to limitations in the specification, but the second version, 1.1 (released in March 2010) is expected to achieve broad adoption and in the process dramatically reduce time-to-market and costs associated with distributing new algorithms.
Algorithms
Some common trading algorithms include:- -TILT-
- 2-step
- 2200 BTU's
- 4-Wheel Drive
- 60-Step
- The Abyss
- Algo Mountains
- Almost Human
- Apollo
- Asimov's Nightmare
- The Awakening
- Back to School
- The Bagman
- Banker's Ball
- Bankers Blitz
- BAT Cave
- BAT Code
- BAT Discovery
- BAT Dribble
- BAT Fence
- BAT Hats
- BAT Horizon
- BAT Lego
- Bat Pig
- Batastic
- Batsicles
- BBOBomber
- The Beach
- Beyond the Blue Wall
- Bid Stuffer
- The Bird
- Blast This
- Blockhead
- Blotter
- Blue Bandsaw
- The Blue Bidder
- Blue Blaster
- Blue Blind
- Blue Blocker
- Blue Flicker
- Blue Ice
- The Blue Pig
- Blue Stubble
- Blue Thicket
- Blue Wave
- Blue Zinger
- Bluegrass
- Boston Buck'r
- Boston Shuffle
- Boston Zapper
- Bot Town
- Bot Wars
- Botastic
- BOTvsBOT
- The Bridge
- Bristles
- Broken BAT
- Broken Highway
- Broken SKY
- Broken Zanti
- Buckaroo Banzai
- The Bug
- The Bunker
- CancelBot
- CancelBot Jr.
- Cancelled Check
- Cannons
- Cannons 2
- The Carnival
- Castle Wall
- Changing Tide
- Cherokee Nation
- The Circus Comes to Town
- City Of BATS
- City Under Siege
- The Click
- Clockwork Orange
- Clogged Artery
- Continental Crust
- Control Tower
- Crazy Eyes
- The Crown
- Danger Will Robinson
- Day Trippin
- The Dead Pool
- The Deep
- The Deer Hunter
- Deer vs. Bat
- Depth Ping
- Detox
- Dinosaur Hunt
- Dirty Glaciers
- Don't Tread On Me
- Double Dip
- Double Pole, Double Throw
- The Drowning
- Early Discovery
- Early Riser
- Enchanted Forest
- EPIC Zapper
- Eraser Head
- Faster Zapper
- Flag Repeater
- The Flood
- Flutter
- Focus
- The Follower
- Fred
- Frog Pond
- From Above
- From Below
- Full Moon Rising
- Fuzzy Orange
- Gold Finger
- Gone Fishing
- Good Luck Human
- The Green Flash
- The Green Hornet
- Ground Strike
- Hairline
- Heart Attack
- High EQ
- High Tide
- I'm A PC
- Inner Chart
- Jump Shot
- Junior
- Just Ask
- The Knife
- Landmine
- Life and Death
- Lightning Strike
- Living On The Edge
- Local Dump
- Low Tide
- Made in America
- Mainframe
- Mannie, Moe and Jack
- Marco Polo
- Market Share
- Master Blaster
- Maxy-Zapper
- Meteors
- The Monster
- Monster Mash
- Morning Zanti
- The Morphing
- NARA Zapper
- No Joy
- No Reason
- Obstructus Maximus
- One Ping Only
- Orange Crush
- Orange Marmalade
- The Outer Limits
- Pacific Rim
- The Palace
- Penny Pincher
- The Pepsi Challenge
- Periscopes
- Petting Zoo
- Pinger
- Plate Shift
- Platform Drilling
- The Port
- Power Line
- Power Tower
- Puzzle Pieces
- The Quota
- Quota Catcher
- Quota Machine
- The Raceway
- Racing Stripe
- Railway
- The Ramp
- Red Sky at Night
- Red Tide
- Redline
- Repeater Wars
- Robot Fight
- Robot Hunting
- Rock Star
- Rollerball
- Rougue Wave
- The Rover
- Runaway
- S.O.S.
- Scissors
- Scofflaw
- Sea Level
- Sea of BATS
- Sea of BATS Star
- The Search
- Search Bots
- The Seekers
- Seen Too Much
- Seizure
- Shades of Blue
- The Shredder
- Simple BAT
- Single Track
- Social Butterfly
- Solar Flare
- Soylent Blue
- The Spartan
- Spastic BAT
- Street Lamps
- Stubby Triangles
- Sunshowers
- T1 Killer
- Take Two
- Tank Tracks
- Tesla's Cathedral
- Test Pattern
- Them
- tHigh EQ
- The Thin Blue Line
- Thin Blue Line
- Things that make you go 'hmmmm'
- The Tickler
- To The Moon, Alice!
- Twilight
- Wading Pool
- Wake Up Call
- Warp 15
- Waste Pool
- When the Levee Breaks
- Wild Thing
- Wild Thing Edge
- Yellow Picket Fence
- Yellow Snow
- You Don't Know Jack
- Zanti Mahem
- The Zanti Misfit
- Zapata
- Zappa Street
- Zapper Clone
- Zero to Sixty
See also
- Alternative Trading SystemsAlternative Trading SystemsAlternative Trading Systems , are United States Securities and Exchange Commission approved non-exchange trading venues specifically designed to match buyers and sellers to find counterparties for transactions, instead of trading large blocks of shares on the normal exchange, a practice that can...
- Artificial intelligenceArtificial intelligenceArtificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
- Complex event processingComplex Event ProcessingComplex event processing consists of processing many events happening across all the layers of an organization, identifying the most meaningful events within the event cloud, analyzing their impact, and taking subsequent action in real time....
- Electronic trading platformElectronic trading platformIn finance, an Electronic trading platform is a computer system that can be used to place orders for financial products over a network with a financial intermediary. This includes products such as shares, bonds, currencies, commodities and derivatives with a financial intermediary, such as a...
- 2010 Flash Crash
- High-frequency tradingHigh-frequency tradingHigh-frequency trading is the use of sophisticated technological tools to trade securities like stocks or options, and is typically characterized by several distinguishing features:...
- Implementation shortfallImplementation shortfallIn financial markets, Implementation Shortfall is the difference between the decision price and the final execution price for a trade. This is also known as the "slippage"...
- Mirror tradingMirror tradingThe mirror trading method allows traders in financial markets to select a trading strategy and to automatically “mirror” the trades executed by the selected strategies in the trader's brokerage account....
External links
- Advanced Trading Magazine: Algorithmic Trading Resource Center Advanced Trading Magazine
- Motley Fool definition and references for Algorithmic Trading
- BusinessWeek.com – SEC Risks Harm With High-Frequency Trading Curbs, CME CEO Says
- The G-Bot Algorithmic Trading Project and Platform
- Findings Regarding the Market Events of May 6, 2010, Report of the staffs of the CFTC and SEC to the Joint Advisory Committee on Emerging Regulatory Issues, September 30, 2010
- The Flash Crash: The Impact of High Frequency Trading on an Electronic Market, Andrei A. Kirilenko (Commodity Futures Trading Commission) Albert S. Kyle (University of Maryland; National Bureau of Economic Research (NBER)) Mehrdad Samadi (Commodity Futures Trading Commission) Tugkan Tuzun (University of Maryland – Robert H. Smith School of Business), October 1, 2010
- Regulatory Issues Raised by the Impact of Technological Changes on Market Integrity and Efficiency, Technical Committee of the International Organization of Securities Commissions, July, 2011