Algorithmic trading is a method of executing a large order using automated pre-programmed trading instructions accounting for variables such as time and volume to send small slices of the order out to the market over time. They were developed so that traders do not need to watch a stock and send those slices out manually. Popular "algos" include Percentage of Volume, Pegged, VWAP, TWAP, Implementation Shortfall, Target Close. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. Algorithmic trading is not an attempt to make a trading profit, it is a way to minimize the cost, market impact and risk in execution of an order. It is used by investment banks, pension funds, mutual funds, hedge funds because these institutional traders need to execute large orders in markets that cannot support all of the size at once; the term is used to mean automated trading system. These do indeed have the goal of making a profit. Known as black box trading, these encompass trading strategies that are reliant on complex mathematical formulas and high-speed computer programs.
Such systems run strategies including market making, inter-market spreading, arbitrage, or pure speculation such as trend following. Many fall into the category of high-frequency trading, which are characterized by high turnover and high order-to-trade ratios; as a result, in February 2012, the Commodity Futures Trading Commission formed a special working group that included academics and industry experts to advise the CFTC on how best to define HFT. HFT strategies utilize computers that make elaborate decisions to initiate orders based on information, received electronically, before human traders are capable of processing the information they observe. Algorithmic trading and HFT have resulted in a dramatic change of the market microstructure in the way liquidity is provided. Profitability projections by the TABB Group, a financial services industry research firm, for the US equities HFT industry were US$1.3 billion before expenses for 2014 down on the maximum of US$21 billion that the 300 securities firms and hedge funds that specialized in this type of trading took in profits in 2008, which the authors had called "relatively small" and "surprisingly modest" when compared to the market's overall trading volume.
In March 2014, Virtu Financial, 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, empirically demonstrating the law of large numbers benefit of trading thousands to millions of tiny, low-risk and low-edge trades every trading day. 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 50% in 2012. In 2006, at the London Stock Exchange, over 40% of all orders were entered by algorithmic traders, with 60% predicted for 2007. American markets and European markets have a higher proportion of algorithmic trades than other markets, estimates for 2008 range as high as an 80% proportion in some markets. Foreign exchange markets have active algorithmic trading. Futures markets are considered easy to integrate 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. Algorithmic trading and HFT have been the subject of much public debate since the U. S. Securities and Exchange Commission and the Commodity Futures Trading Commission said in reports that an algorithmic trade entered by a mutual fund company triggered a wave of selling that led to the 2010 Flash Crash; the same reports found HFT strategies may have contributed to subsequent volatility by pulling liquidity from the market. As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing to that date, though prices recovered. A July 2011 report by the International Organization of Securities Commissions, 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 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 alter trading inventory during the Flash Crash. Some algorithmic trading ahead of index fund rebalancing transfers profits from investors. Computerization of the order flow in financial markets began in the early 1970s, with some landmarks being the introduction of the New York Stock Exchange's “designated order turnaround” system, which routed orders electronically to the proper trading post, which executed them manually; the "opening automated reporting system" aided the specialist in determining the market clearing opening price. 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. In the 1980s, program trading became used in trading between the S&P 500 equity and futures markets. In stock index arbitrage a trader buys a stock index futures contract such as the S&P 500 futures and sells a portfolio of
In finance, a short sale is the sale of an asset that the seller has borrowed in order to profit from a subsequent fall in the price of the asset. After borrowing the asset, the short seller sells it to a buyer at the market price at that time. Subsequently, the resulting short position is "covered" when the seller repurchases the same asset in a market transaction and delivers the purchased asset back to the lender to replace the asset, borrowed. In the event of an interim price decline, the short seller will profit, since the cost of purchase will be less than the proceeds received upon the initial sale. Conversely, the short position will result in a loss if the price of a shorted asset rises prior to repurchase. "Shorting" can refer more to the use of derivatives or other techniques to achieve the same effect, such that the investor profits from the fall in the value of an asset without undertaking the borrowing of securities. Potential loss on a short sale is theoretically unlimited, as there is no theoretical limit to a rise in the price of the instrument.
However, in practice, the short seller is required to post margin or collateral to cover losses, inability to do so in a timely way would cause its broker or counterparty to liquidate the position. In the securities markets, the seller must borrow the securities to effect delivery in the short sale. In some cases, the short seller must pay a fee to borrow the securities and must additionally reimburse the lender for cash returns the lender would have received had the securities not been loaned out. Short selling is most done with instruments traded in public securities, futures or currency markets, due to the liquidity and real-time price dissemination characteristic of such markets and because the instruments defined within each class are fungible. In practical terms, "going short" can be considered the opposite of the conventional practice of "going long", whereby an investor profits from an increase in the price of the asset. Mathematically, the return from a short position is equivalent to that of owning a negative amount of the instrument.
A short sale may have a variety of objectives. Speculators may sell short hoping to realize a profit on an instrument that appears overvalued, just as long investors or speculators hope to profit from a rise in the price of an instrument that appears undervalued. Traders or fund managers may hedge a long position or a portfolio through one or more short positions. In contrast to a traditional merchant who sets out to "buy low, sell high", a short-seller sets out to "sell high, buy low", or to "buy high, sell low" when this buy is in fact "on tick". Research indicates that banning short selling has negative effects on markets. Short selling is subject to criticism and periodically faces hostility from society and policymakers; the following example describes the short sale of a security. To profit from a decrease in the price of a security, a short seller can borrow the security and sell it expecting that it will be cheaper to repurchase in the future; when the seller decides that the time is right, the seller buys equivalent securities and returns them to the lender.
The process relies on the fact. A short seller borrows through a broker, holding the securities for another investor who owns the securities; the lender does not lose the right to sell the securities while they have been lent, as the broker holds a large pool of such securities for a number of investors which, as such securities are fungible, can instead be transferred to any buyer. In most market conditions there is a ready supply of securities to be borrowed, held by pension funds, mutual funds and other investors; the act of buying back the securities that were sold short is called "covering the short" or "covering the position". A short position can be covered at any time. Once the position is covered, the short seller is not affected by subsequent rises or falls in the price of the securities, as he holds the securities required to repay the lender. Short selling refers broadly to any transaction used by an investor to profit from the decline in price of a borrowed asset or financial instrument.
However some short positions, for example those undertaken by means of derivatives contracts, are not technically short sales because no underlying asset is delivered upon the initiation of the position. Derivatives contracts include futures and swaps. Shares in ACME Inc. trade at $10 per share. A short seller investor borrows from a lender 100 shares of ACME Inc. and sells them for a total of $1,000. Subsequently, the price of the shares falls to $8 per share. Short seller now buys 100 shares of ACME Inc. for $800. Short seller returns the shares to the lender, who must accept the return of the same number of shares as was lent despite the fact that the market value of the shares has decreased. Short seller profits from the $200 difference between the price at which the short seller sold th
In mathematics, infinitesimals are things so small that there is no way to measure them. The insight with exploiting infinitesimals was that entities could still retain certain specific properties, such as angle or slope though these entities were quantitatively small; the word infinitesimal comes from a 17th-century Modern Latin coinage infinitesimus, which referred to the "infinite-th" item in a sequence. Infinitesimals are a basic ingredient in the procedures of infinitesimal calculus as developed by Leibniz, including the law of continuity and the transcendental law of homogeneity. In common speech, an infinitesimal object is an object, smaller than any feasible measurement, but not zero in size—or, so small that it cannot be distinguished from zero by any available means. Hence, when used as an adjective, "infinitesimal" means "extremely small". To give it a meaning, it must be compared to another infinitesimal object in the same context. Infinitely many infinitesimals are summed to produce an integral.
The concept of infinitesimals was introduced around 1670 by either Nicolaus Mercator or Gottfried Wilhelm Leibniz. Archimedes used what came to be known as the method of indivisibles in his work The Method of Mechanical Theorems to find areas of regions and volumes of solids. In his formal published treatises, Archimedes solved the same problem using the method of exhaustion; the 15th century saw the work of Nicholas of Cusa, further developed in the 17th century by Johannes Kepler, in particular calculation of area of a circle by representing the latter as an infinite-sided polygon. Simon Stevin's work on decimal representation of all numbers in the 16th century prepared the ground for the real continuum. Bonaventura Cavalieri's method of indivisibles led to an extension of the results of the classical authors; the method of indivisibles related to geometrical figures as being composed of entities of codimension 1. John Wallis's infinitesimals differed from indivisibles in that he would decompose geometrical figures into infinitely thin building blocks of the same dimension as the figure, preparing the ground for general methods of the integral calculus.
He exploited an infinitesimal denoted 1/∞ in area calculations. The use of infinitesimals by Leibniz relied upon heuristic principles, such as the law of continuity: what succeeds for the finite numbers succeeds for the infinite numbers and vice versa; the 18th century saw routine use of infinitesimals by mathematicians such as Leonhard Euler and Joseph-Louis Lagrange. Augustin-Louis Cauchy exploited infinitesimals both in defining continuity in his Cours d'Analyse, in defining an early form of a Dirac delta function; as Cantor and Dedekind were developing more abstract versions of Stevin's continuum, Paul du Bois-Reymond wrote a series of papers on infinitesimal-enriched continua based on growth rates of functions. Du Bois-Reymond's work inspired both Émile Thoralf Skolem. Borel explicitly linked du Bois-Reymond's work to Cauchy's work on rates of growth of infinitesimals. Skolem developed the first non-standard models of arithmetic in 1934. A mathematical implementation of both the law of continuity and infinitesimals was achieved by Abraham Robinson in 1961, who developed non-standard analysis based on earlier work by Edwin Hewitt in 1948 and Jerzy Łoś in 1955.
The hyperreals implement an infinitesimal-enriched continuum and the transfer principle implements Leibniz's law of continuity. The standard part function implements Fermat's adequality. Vladimir Arnold wrote in 1990: Nowadays, when teaching analysis, it is not popular to talk about infinitesimal quantities. Present-day students are not in command of this language, it is still necessary to have command of it. The notion of infinitely small quantities was discussed by the Eleatic School; the Greek mathematician Archimedes, in The Method of Mechanical Theorems, was the first to propose a logically rigorous definition of infinitesimals. His Archimedean property defines a number x as infinite if it satisfies the conditions |x|>1, |x|>1+1, |x|>1+1+1... and infinitesimal if x≠0 and a similar set of conditions holds for x and the reciprocals of the positive integers. A number system is said to be Archimedean if it contains infinitesimal members; the English mathematician John Wallis introduced the expression 1/∞ in his 1655 book Treatise on the Conic Sections.
The symbol, which denotes the reciprocal, or inverse, of ∞, is the symbolic representation of the mathematical concept of an infinitesimal. In his Treatise on the Conic Sections Wallis discusses the concept of a relationship between the symbolic representation of infinitesimal 1/∞ that he introduced and the concept of infinity for which he introduced the symbol ∞; the concept suggests a thought experiment of adding an infinite number of parallelograms of infinitesimal width to form a finite area. This concept was the predecessor to the modern method of integration used in integral calculus; the conceptual origins of the concept of the infinitesimal 1/∞ can be traced as far back as the Greek philosopher Zeno of Elea, whose Zeno's dichotomy paradox was the first mathematical concept to consider the relationship between a finite interval and an interval approaching that of an infinitesimal-sized interval. Infinitesimals were the subject of political and religious controversies in 17th century Europe, including a ban on infinitesimals issued by clerics in Rome in 1632.
Prior to the invention of calculus mathematicians were able to calculate tangent lines using Pierre de
In finance, statistical arbitrage is a class of short-term financial trading strategies that employ mean reversion models involving broadly diversified portfolios of securities held for short periods of time. These strategies are supported by substantial mathematical and trading platforms; as a trading strategy, statistical arbitrage is a quantitative and computational approach to securities trading. It involves statistical methods, as well as the use of automated trading systems. StatArb evolved out of the simpler pairs trade strategy, in which stocks are put into pairs by fundamental or market-based similarities; when one stock in a pair outperforms the other, the poorer performing stock is bought long with the expectation that it will climb towards its outperforming partner, the other is sold short. Mathematically speaking, the strategy is to find a pair of stocks with high correlation, cointegration, or other common factor characteristics. Various statistical tools have been used in the context of pairs trading ranging from simple distance-based approaches to more complex tools such as cointegration and copula concepts.
StatArb considers not pairs of stocks but a portfolio of a hundred or more stocks—some long, some short—that are matched by sector and region to eliminate exposure to beta and other risk factors. Portfolio construction consists of two phases. In the first or "scoring" phase, each stock in the market is assigned a numeric score or rank that reflects its desirability; the details of the scoring formula vary and are proprietary, but they involve a short term mean reversion principle so that, e.g. stocks that have done unusually well in the past week receive low scores and stocks that have underperformed receive high scores. In the second or "risk reduction" phase, the stocks are combined into a portfolio in matched proportions so as to eliminate, or at least reduce and factor risk; this phase uses commercially available risk models like MSCI/Barra/APT/Northfield/Risk Infotech/Axioma to constrain or eliminate various risk factors. Broadly speaking, StatArb is any strategy, bottom-up, beta-neutral in approach and uses statistical/econometric techniques in order to provide signals for execution.
Signals are generated through a contrarian mean reversion principle but can be designed using such factors as lead/lag effects, corporate activity, short-term momentum, etc. This is referred to as a multi-factor approach to StatArb; because of the large number of stocks involved, the high portfolio turnover and the small size of the effects one is trying to capture, the strategy is implemented in an automated fashion and great attention is placed on reducing trading costs. Statistical arbitrage has become a major force at both hedge funds and investment banks. Many bank proprietary operations now center to varying degrees around statistical arbitrage trading. Over a finite period of time, a low probability market movement may impose heavy short-term losses. If such short-term losses are greater than the investor's funding to meet interim margin calls, its positions may need to be liquidated at a loss when its strategy's modeled forecasts turn out to be correct; the 1998 default of Long-Term Capital Management was a publicized example of a fund that failed due to its inability to post collateral to cover adverse market fluctuations.
Statistical arbitrage is subject to model weakness as well as stock- or security-specific risk. The statistical relationship on which the model is based may be spurious, or may break down due to changes in the distribution of returns on the underlying assets. Factors, which the model may not be aware of having exposure to, could become the significant drivers of price action in the markets, the inverse applies also; the existence of the investment based upon model itself may change the underlying relationship if enough entrants invest with similar principles. The exploitation of arbitrage opportunities themselves increases the efficiency of the market, thereby reducing the scope for arbitrage, so continual updating of models is necessary. On a stock-specific level, there is risk of M&A activity or default for an individual name; such an event would invalidate the significance of any historical relationship assumed from empirical statistical analysis of the past data. During July and August 2007, a number of StatArb hedge funds experienced significant losses at the same time, difficult to explain unless there was a common risk factor.
While the reasons are not yet understood, several published accounts blame the emergency liquidation of a fund that experienced capital withdrawals or margin calls. By closing out its positions the fund put pressure on the prices of the stocks it was long and short; because other StatArb funds had similar positions, due to the similarity of their alpha models and risk-reduction models, the other funds experienced adverse returns. One of the versions of the events describes how Morgan Stanley's successful StatArb fund, PDT, decided to reduce its positions in response to stresses in other parts of the firm, how this contributed to several days of hectic trading. In a sense, the fact of a stock being involved in StatArb is itself a risk factor, one, new and thus was not taken into account by the StatArb models; these events showed that StatArb has developed to a point where it is
Foreign exchange market
The foreign exchange market is a global decentralized or over-the-counter market for the trading of currencies. This market determines the foreign exchange rate, it includes all aspects of buying and exchanging currencies at current or determined prices. In terms of trading volume, it is by far the largest market in the world, followed by the Credit market; the main participants in this market are the larger international banks. Financial centers around the world function as anchors of trading between a wide range of multiple types of buyers and sellers around the clock, with the exception of weekends. Since currencies are always traded in pairs, the foreign exchange market does not set a currency's absolute value but rather determines its relative value by setting the market price of one currency if paid for with another. Ex: US$1 is worth X CAD, or CHF, or JPY, etc; the foreign exchange market operates on several levels. Behind the scenes, banks turn to a smaller number of financial firms known as "dealers", who are involved in large quantities of foreign exchange trading.
Most foreign exchange dealers are banks, so this behind-the-scenes market is sometimes called the "interbank market". Trades between foreign exchange dealers can be large, involving hundreds of millions of dollars; because of the sovereignty issue when involving two currencies, Forex has little supervisory entity regulating its actions. The foreign exchange market assists international trade and investments by enabling currency conversion. For example, it permits a business in the United States to import goods from European Union member states Eurozone members, pay Euros though its income is in United States dollars, it supports direct speculation and evaluation relative to the value of currencies and the carry trade speculation, based on the differential interest rate between two currencies. In a typical foreign exchange transaction, a party purchases some quantity of one currency by paying with some quantity of another currency; the modern foreign exchange market began forming during the 1970s.
This followed three decades of government restrictions on foreign exchange transactions under the Bretton Woods system of monetary management, which set out the rules for commercial and financial relations among the world's major industrial states after World War II. Countries switched to floating exchange rates from the previous exchange rate regime, which remained fixed per the Bretton Woods system; the foreign exchange market is unique because of the following characteristics: its huge trading volume, representing the largest asset class in the world leading to high liquidity. As such, it has been referred to as the market closest to the ideal of perfect competition, notwithstanding currency intervention by central banks. According to the Bank for International Settlements, the preliminary global results from the 2016 Triennial Central Bank Survey of Foreign Exchange and OTC Derivatives Markets Activity show that trading in foreign exchange markets averaged $5.09 trillion per day in April 2016.
This is down from $5.4 trillion in April 2013 but up from $4.0 trillion in April 2010. Measured by value, foreign exchange swaps were traded more than any other instrument in April 2016, at $2.4 trillion per day, followed by spot trading at $1.7 trillion. The $5.09 trillion break-down is as follows: $1.654 trillion in spot transactions $700 billion in outright forwards $2.383 trillion in foreign exchange swaps $96 billion currency swaps $254 billion in options and other products Currency trading and exchange first occurred in ancient times. Money-changers were living in the Holy Land in the times of the Talmudic writings; these people used city stalls, at feast times the Temple's Court of the Gentiles instead. Money-changers were the silversmiths and/or goldsmiths of more recent ancient times. During the 4th century AD, the Byzantine government kept a monopoly on the exchange of currency. Papyri PCZ I 59021, shows the occurrences of exchange of coinage in Ancient Egypt. Currency and exchange were important elements of trade in the ancient world, enabling people to buy and sell items like food and raw materials.
If a Greek coin held more gold than an Egyptian coin due to its size or content a merchant could barter fewer Greek gold coins for more Egyptian ones, or for more material goods. This is why, at some point in their history, most world currencies in circulation today had a value fixed to a specific quantity of a recognized standard like silver and gold. During the 15th century, the Medici family were required to open banks at foreign locations in order to exchange currencies to act on behalf of textile merchants. To facilitate trade, the bank created the nostro account book which contained two columned entries showing amounts of foreign and local currencies. During the 17th century, Amsterdam maintained an active Forex market. In 1704, foreign exchange took place between agents acting in the interests of the Kingdom of Englan
In finance, an option is a contract which gives the buyer the right, but not the obligation, to buy or sell an underlying asset or instrument at a specified strike price prior to or on a specified date, depending on the form of the option. The strike price may be set by reference to the spot price of the underlying security or commodity on the day an option is taken out, or it may be fixed at a discount or at a premium; the seller has the corresponding obligation to fulfill the transaction – to sell or buy – if the buyer "exercises" the option. An option that conveys to the owner the right to buy at a specific price is referred to as a call. Both are traded, but the call option is more discussed; the seller may grant an option to a buyer as part of another transaction, such as a share issue or as part of an employee incentive scheme, otherwise a buyer would pay a premium to the seller for the option. A call option would be exercised only when the strike price is below the market value of the underlying asset, while a put option would be exercised only when the strike price is above the market value.
When an option is exercised, the cost to the buyer of the asset acquired is the strike price plus the premium, if any. When the option expiration date passes without the option being exercised, the option expires and the buyer would forfeit the premium to the seller. In any case, the premium is income to the seller, a capital loss to the buyer; the owner of an option may on-sell the option to a third party in a secondary market, in either an over-the-counter transaction or on an options exchange, depending on the option. The market price of an American-style option closely follows that of the underlying stock being the difference between the market price of the stock and the strike price of the option; the actual market price of the option may vary depending on a number of factors, such as a significant option holder may need to sell the option as the expiry date is approaching and does not have the financial resources to exercise the option, or a buyer in the market is trying to amass a large option holding.
The ownership of an option does not entitle the holder to any rights associated with the underlying asset, such as voting rights or any income from the underlying asset, such as a dividend. Contracts similar to options have been used since ancient times; the first reputed option buyer was the ancient Greek mathematician and philosopher Thales of Miletus. On a certain occasion, it was predicted that the season's olive harvest would be larger than usual, during the off-season, he acquired the right to use a number of olive presses the following spring; when spring came and the olive harvest was larger than expected he exercised his options and rented the presses out at a much higher price than he paid for his'option'. In London, puts and "refusals" first became well-known trading instruments in the 1690s during the reign of William and Mary. Privileges were options sold over the counter in nineteenth century America, with both puts and calls on shares offered by specialized dealers, their exercise price was fixed at a rounded-off market price on the day or week that the option was bought, the expiry date was three months after purchase.
They were not traded in secondary markets. In the real estate market, call options have long been used to assemble large parcels of land from separate owners. Film or theatrical producers buy the right — but not the obligation — to dramatize a specific book or script. Lines of credit give the potential borrower the right — but not the obligation — to borrow within a specified time period. Many choices, or embedded options, have traditionally been included in bond contracts. For example, many bonds are convertible into common stock at the buyer's option, or may be called at specified prices at the issuer's option. Mortgage borrowers have long had the option to repay the loan early, which corresponds to a callable bond option. Options contracts have been known for decades; the Chicago Board Options Exchange was established in 1973, which set up a regime using standardized forms and terms and trade through a guaranteed clearing house. Trading activity and academic interest has increased since then.
Today, many options are created in a standardized form and traded through clearing houses on regulated options exchanges, while other over-the-counter options are written as bilateral, customized contracts between a single buyer and seller, one or both of which may be a dealer or market-maker. Options are part of a larger class of financial instruments known as derivative products, or derivatives. A financial option is a contract between two counterparties with the terms of the option specified in a term sheet. Option contracts may be quite complicated.
A stock market, equity market or share market is the aggregation of buyers and sellers of stocks, which represent ownership claims on businesses. Examples of the latter include shares of private companies which are sold to investors through equity crowdfunding platforms. Stock exchanges list shares of common equity as well as other security types, e.g. corporate bonds and convertible bonds. Stocks are categorized in various ways. One way is by the country. For example, Nestlé and Novartis are domiciled in Switzerland, so they may be considered as part of the Swiss stock market, although their stock may be traded on exchanges in other countries, for example, as American depository receipts on U. S. stock markets. As of 2017, the size of the world stock market was about US$79.225 trillion. By country, the largest market was the United States, followed by the United Kingdom; these numbers increased in 2013. As of 2015, there are a total of 60 stock exchanges in the world with a total market capitalization of $69 trillion.
Of these, there are 16 exchanges with a market capitalization of $1 trillion or more, they account for 87% of global market capitalization. Apart from the Australian Securities Exchange, these 16 exchanges are based in one of three continents: North America and Asia. A stock exchange is an exchange where stock brokers and traders can buy and sell shares of stock and other securities. Many large companies have their stocks listed on a stock exchange; this makes the stock more liquid and thus more attractive to many investors. The exchange may act as a guarantor of settlement. Other stocks may be traded "over the counter", that is, through a dealer; some large companies will have their stock listed on more than one exchange in different countries, so as to attract international investors. Stock exchanges may cover other types of securities, such as fixed interest securities or derivatives which are more to be traded OTC. Trade in stock markets means the transfer of a security from a seller to a buyer.
This requires these two parties to agree on a price. Equities confer an ownership interest in a particular company. Participants in the stock market range from small individual stock investors to larger investors, who can be based anywhere in the world, may include banks, insurance companies, pension funds and hedge funds, their buy or sell orders may be executed on their behalf by a stock exchange trader. Some exchanges are physical locations where transactions are carried out on a trading floor, by a method known as open outcry; this method is used in some stock exchanges and commodity exchanges, involves traders shouting bid and offer prices. The other type of stock exchange has a network of computers. An example of such an exchange is the NASDAQ. A potential buyer bids a specific price for a stock, a potential seller asks a specific price for the same stock. Buying or selling at the market means you will accept any ask price or bid price for the stock; when the bid and ask prices match, a sale takes place, on a first-come, first-served basis if there are multiple bidders at a given price.
The purpose of a stock exchange is to facilitate the exchange of securities between buyers and sellers, thus providing a marketplace. The exchanges provide real-time trading information on the listed securities, facilitating price discovery; the New York Stock Exchange is a physical exchange, with a hybrid market for placing orders electronically from any location as well as on the trading floor. Orders executed on the trading floor enter by way of exchange members and flow down to a floor broker, who submits the order electronically to the floor trading post for the Designated Market Maker for that stock to trade the order; the DMM's job is to maintain a two-sided market, making orders to buy and sell the security when there are no other buyers or sellers. If a spread exists, no trade takes place – in this case the DMM may use their own resources to close the difference. Once a trade has been made, the details are reported on the "tape" and sent back to the brokerage firm, which notifies the investor who placed the order.
Computers play an important role for program trading. The NASDAQ is a virtual exchange; the process is similar to the New York Stock Exchange. One or more NASDAQ market makers will always provide a bid and ask price at which they will always purchase or sell'their' stock; the Paris Bourse, now part of Euronext, is an electronic stock exchange. It was automated in the late 1980s. Prior to the 1980s, it consisted of an open outcry exchange. Stockbrokers met on the trading floor of the Palais Brongniart. In 1986, the CATS trading system was introduced, the order matching process was automated. People trading stock will prefer to trade on the most popular exchange since this gives the largest number of potential counter parties and the best price. However, there have always been alternatives such as brokers trying to bring parties together to trade outside the exchange; some third markets that were popular are Instinet, Island and Archipelago. One advantage is that this avoids the commissions