Sceeto Stock Trading Indicators: Sep 3, 2012

Monday, September 3, 2012

Price Action Trading Daily Report 31st August 2012 Russell TF Futures

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Price Action Trading Daily Report 31st August 2012 Russell TF Futures.The top trading indicators for monitoring hft program trading or high frequency trading as well as order flow in Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
The concept of price action trading embodies the analysis of basic price movement as a methodology for financial speculation, as used by many retail traders and often institutionally where algorithmic trading is not employed, and at its most simplistic, it attempts to describe the human thought processes invoked by experienced, non-disciplinary traders as they observe and trade their markets.[1][2][3][4] Price action is simply how prices change - the action of price. It is readily observed in markets where liquidity and price volatility are highest, but anything that is bought or sold freely in a market will per se demonstrate price action. Price action trading can be included under the umbrella of technical analysis but is covered here in a separate article because it incorporates the behavioural analysis of market participants as a crowd from evidence displayed in price action - a type of analysis whose academic coverage isn't focused in any one area, rather is widely described and commented on in the literature on trading, speculation, gambling and competition generally. It includes a large part of the methodology employed by floor traders[5] and tape readers.[6] It can also optionally include analysis of volume and level 2 quotes.
The trader observes the relative size, shape, position, growth (when watching the current real-time price) and volume (optionally) of the bars on an OHLC bar or candlestick chart, starting as simple as a single bar, most often combined with chart formations found in broader technical analysis such as moving averages, trend lines or trading ranges.[7][8] The use of price action analysis for financial speculation doesn't exclude the simultaneous use of other techniques of analysis, and on the other hand, a minimalist price action trader can rely completely on the behavioural interpretation of price action to build a trading strategy.
The various authors who write about price action, e.g. Brooks,[8] Duddella,[9] give names to the price action chart formations and behavioural patterns they observe, which may or may not be unique to that author and known under other names by other authors (more investigation into other authors to be done here). These patterns can often only be described subjectively and the idealized formation or pattern can in reality appear with great variation.
This article attempts to outline most major candlestick bars, patterns, chart formations, behavioural observations and trade setups that are used in price action trading. It covers the way that they are interpreted by price action traders, whether they signal likely future market direction, and how the trader would place orders correspondingly to profit from that (and where protective exit orders would be placed to minimise losses when wrong). Since price action traders combine bars, patterns, formations, behaviours and setups together with other bars, patterns, formations etc. to create further setups, many of the descriptions here will refer to other descriptions in the article. The layout of descriptions here is linear, but there is no one perfect sequence - they appear here loosely in the sequence: behavioural observations, trends, reversals and trading ranges. This editing approach reflects the nature of price action, sub-optimal as it might appear.
Algorithmic trading, also called automated trading, black-box trading, or algo 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 funds, mutual funds, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades to manage market impact, and risk.[1][2] Sell side traders, such as market makers and some hedge funds, 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.[3]

High Frequency Trading HFT Trading Daily Report 31st August 2012 S&P 500...

High Frequency Trading HFT Trading Daily Report 31st August 2012 S&P 500 Emini Futures.The top trading indicators for monitoring hft program trading or high frequency trading as well as order flow in Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
Algorithmic trading, also called automated trading, black-box trading, or algo 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 funds, mutual funds, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades to manage market impact, and risk.[1][2] Sell side traders, such as market makers and some hedge funds, 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.[3]
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.[4] As of 2009, HFT firms account for 73% of all US equity trading volume.[5]
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 markets also have active algo trading (about 25% of orders in 2006).[6] Futures and options markets are considered fairly easy to integrated into algorithmic trading,[7] with about 20% of options volume expected to be computer-generated by 2010.[dated info][8] Bond markets are moving toward more access to algorithmic traders.[9]
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.[10]
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 said they contributed to some of the volatility during the 2010 Flash Crash,[11][12][13][14][15][16][17][18] 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."

Program Trading Daily Report 31st August 2012 Forex Euro USD 6E Futures

Program Trading Daily Report 31st August 2012 Forex Euro USD 6E Futures.The top trading indicators for monitoring hft program trading or high frequency trading as well as order flow in Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
Program trading is 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.[1] There are essentially two reasons to use program trading, either because of the desire to trade a large number of stocks at the same time (for example, when a mutual fund receives an influx of money it will use that money to increase its holdings in the multiple stocks which the fund is based on), or alternatively to arbitrage temporary price discrepancies between related financial instruments, such as between an index and its constituent parts.[2]
According to the New York Stock Exchange, in 2006 program trading accounts for about 30% and as high as 46.4% of the trading volume on that exchange every day.[3] Barrons breaks down its weekly figures for program trading between index arbitrage and other types of program trading. As of July 2012, program trading made up about 30% of the volume on the NYSE; index arbitrage made up less than 1%.Several factors help to explain the explosion in program trading. Technological advances spawned the growth of electronic communication networks. These electronic exchanges, like Instinet and Archipelago Exchange, allow thousands of buy and sell orders to be matched very rapidly, without human intervention.
In addition, the proliferation of hedge funds with all their sophisticated trading strategies have helped drive program-trading volume.[5]
As technology advanced and access to electronic exchanges became easier and faster, program trading developed into the much broader algorithmic trading and high-frequency trading strategies employed by the investment banks and hedge funds.Program Trading is a strategy normally used by large institutional traders. Barrons shows a detailed breakdown of the NYSE-published program trading figures each week, giving the figures for the largest program trading firms (such as investment banks)Index Arbitrage is a particular type of Program Trading which attempts to profit from price discrepancies between the basket of stocks which make up a stock index and its derivatives (such as the future based on that index). As of July 2012, it makes up less than 5% of the active Program Trading volume on the NYSE daily.[7]
[edit]Premium Buy and Sell Execution Levels
The "premium" (PREM) or "spread" is the difference between the stock index future fair value and the actual index level. As the derivative is based on the index, the two should normally have a very close relationship. If there is a sufficiently large difference the arbitraging program will attempt to buy the relatively cheap level (whether that is the basket of stocks which make up the index or the index future) and sell the relatively expensive product, making money from the price discrepancy. The fair value calculation takes into account the time to expiration of the future contract, the dividends received from holding all the stocks, and the interest cost of buying the stocks

Order Flow Monitoring Daily Report 31st August 2012 Crude Oil Futures

Order Flow Monitoring Daily Report 31st August 2012 Crude Oil Futures.The top trading indicators for monitoring hft program trading or high frequency trading as well as order flow in Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

The Top 10+ Core Principles Regarding How Changes in Order Flow Affect Changes in Price:

Price is always a function of Supply & Demand - Regardless of the market.
Changes in Supply and/or Demand effect changes in Price. The futures markets are no different from a widget market or the Ice Cream market.
Changes in Order Flow precede changes in Price.
Program Trading is the Primary Cause of changes in Supply & Demand.
Buy Programs Usurp Supply - Thereby increasing price.
Sell Programs Increase Supply - Thereby decreasing price.
Increases in Price momentum will fade if they are not backed by substantive Program Trading
As changes in Order Flow precede changes in Price, it is advisable to always enter each trade via a Stop, this way, Price activity confirms the Order Flow information. Long trades are entered via a Buy Stop one tick above the most recent pivot, and Short trades are entered via a Sell Stop one tick below the most recent pivot. If after a Long Entry Stop is place, price moves down and breaches the most recent low pivot, the Entry Stop is to be removed. If after a Short Entry Stop is placed, price moves upwards and breaches the most recent high pivot, the Entry Stop is to be removed.
Software can monitor this activity in real-time thereby creating ongoing opportunities to follow and feast off of the Big Money just like a Pilot Fish follows and feasts off of a Shark.
'Smart Money' really does exist. For Smart Money to profit from their insight, they must trade. When they trade in an electronic market, their transactions get recorded in real-time. Thus, they leave a footprint that can be, and is, monitored by custom TLA software.
There are really, really sophisticated trading entities thriving in today's electronic marketplace. They exist and thrive because the microprocessor is at the heart of today's electronic futures markets and it enables them to write algorithms to take advantage of any, and every, discrepancy in the market.
Stop Losses are the bread and butter of short-term algorithmic trading shops. They 'know' where the stops are and can fire off Program Trades with sufficient force to trigger a bucket of stops. By doing this they create immediate liquidity which allows them to close out their positions.
You can use software to tell when a market is tired and is likely to turn.
The Forbes 400 List is wholly inaccurate. In my opinion, If the truth be known, the Forbes 400 List would be littered with the Managing Director's of small trading enterprises that fire off thousands of trades a day using sophisticated software that is plumb smarter than the man on the street's.
You can increase your percentage of winning trades by incorporating Order Flow monitoring and interpretation into your analysis...primarily by having the real-time information which offers you the ability and skill to never fight the tape.

MultiCharts Daily Report 30th August 2012 Russell TF Futures

MultiCharts Daily Report 30th August 2012 Russell TF Futures.The top trading indicators for Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
Algorithmic trading, also called automated trading, black-box trading, or algo 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 funds, mutual funds, and other buy side (investor driven) institutional traders, to divide large trades into several smaller trades to manage market impact, and risk.[1][2] Sell side traders, such as market makers and some hedge funds, 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.[3]
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.[4] As of 2009, HFT firms account for 73% of all US equity trading volume.[5]
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 markets also have active algo trading (about 25% of orders in 2006).[6] Futures and options markets are considered fairly easy to integrated into algorithmic trading,[7] with about 20% of options volume expected to be computer-generated by 2010.[dated info][8] Bond markets are moving toward more access to algorithmic traders.[9]
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.[10]
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 said they contributed to some of the volatility during the 2010 Flash Crash,[11][12][13][14][15][16][17][18] 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."

SierraCharts Daily Report 30th August 2012 S&P 500 Emini Futures

SierraCharts Daily Report 30th August 2012 S&P 500 Emini Futures.The top trading indicators for Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
One of the key developments in the history of ECNs was the NASDAQ over-the-counter quotation system. NASDAQ was created following a 1969 American Stock Exchange study which estimated that errors in the processing of hand-written securities orders cost brokerage firms approximately $100 million per year. The NASDAQ system automated such order processing and provided brokers with the latest competitive price quotes via a computer terminal. In March 1994, a study by two economists, William Christie and Paul Schultz, noted that NASDAQ bid-ask spreads were larger than was statistically likely, indicating "We are unable to envision any scenario in which 40 to 60 dealers who are competing for order flow would simultaneously and consistently avoid using odd-eighth quotes without an implicit agreement to post quotes only on the even price fractions. However, our data do not provide direct evidence of tacit collusion among NASDAQ market makers." These results led to an antitrust lawsuit being filed against NASDAQ. As part of NASDAQ's settlement of the antitrust charges, NASDAQ adopted new order handling rules that integrated ECNs into the NASDAQ system. Shortly after this settlement, the SEC adopted Regulation ATS, which permitted ECNs the option of registering as stock exchanges or else being regulated under a separate set of standards for ECNs.[2][3]
At that time major ECNs that became active were Instinet and Island (part of Instinet was spun off, merged with Island into Inet, and acquired by NASDAQ), Archipelago Exchange (which was acquired by the NYSE) and Brut (now acquired by NASDAQ).
ECNs enjoyed a resurgence after the adoption of SEC Regulation NMS, which required "trade through" protection of orders in the market, regardless of where those orders are placed.After-hours trading is stock trading that occurs after the traditional trading hours of the major exchanges, such as the New York Stock Exchange and the Nasdaq Stock Market. Since 1985, the regular trading hours in the United States have been from 9:30 a.m. to 4:00 p.m. Eastern Time (ET).[1]

Example chart of extended hours trading, via Google Finance
Trading outside these regular hours is not a new phenomenon but previously was limited to high net-worth investors and institutional investors like mutual funds.[2] The emergence of private trading systems, known as electronic communication networks or ECNs, has allowed individual investors to participate in after-hours trading.
After-hours trading on a day with a normal session occurs from 4:00 to 8:00 p.m. ET.[3]
After-hours trading is frequently abbreviated on message boards as AH. That has led people to jokingly refer to after-hours trading as "amateur hour", as the people who trade during that time are mostly small retail traders and not institutional investors, and, barring material news, it frequently does not reflect how trading will be the next morning.[citation needed]
Trading also occurs before the traditional trading hours and is known as pre-market trading. Pre-market trading occurs from 7:00 to 9:30 a.m. ET.[4]
National Association of Securities Dealers (NASD) members who voluntarily enter quotations during the after-hours session are required to comply with all applicable limit order protection and display rules (e.g., the Manning rule and the SEC order handling rules)

NinjaTrader Daily Report 30th August 2012 Forex Euro USD 6E Futures

NinjaTrader Daily Report 30th August 2012 Forex Euro USD 6E Futures.The top trading indicators for Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
For stock trading, ECNs exist as a class of SEC-permitted Alternative Trading Systems (ATS). As an ATS, ECNs exclude broker-dealers' internal crossing networks – i.e., systems that match orders in private using prices from a public exchange.
[edit]Fee structure

ECN's fee structure can be grouped in two basic structures: a classic structure and a credit (or rebate) structure. Both fee structures offer advantages of their own. The classic structure tends to attract liquidity removers while the credit structure appeals to liquidity providers. However since both removers and providers of liquidity are necessary to create a market, ECNs must choose their fee structures carefully.
In a credit structure ECNs make a profit from paying liquidity providers a credit while charging a debit to liquidity removers. Credits range from $0.002 to $0.00295 per share for liquidity providers, and debits from $0.0025 to $0.003 per share for liquidity removers. The fee can be determined by monthly volume provided and removed, or by a fixed structure, depending on the ECN. This structure is common on the NASDAQ market.[1]. Traders commonly quote the fees in millicents or mils (e.g. $0.00295 is 29.5 mils).
In a classic structure, the ECN will charge a small fee to all market participants using their network, both liquidity providers and removers. They also can attract volume to their networks by giving lower prices to large liquidity providers. Fees for ECNs that operate under a classic structure range from $0 to $0.0015, or even higher depending on each ECN. This fee structure is more common in the NYSE, however recently some ECNs have moved their NYSE operations into a credit structure.The first ECN for internet currency trading was New-York based Matchbook FX formed in 1999. Back then, all the prices were created & supplied by Matchbook FX's traders/users, including banks, within its ECN network. This was quite unique at the time, as it empowered buy-side FX market participants, historically always "price takers", to finally be price makers as well. Today, FX ECNs like Currenex, Bloomberg Tradebook (an affiliate of Bloomberg L.P.), Hotspot FX, 360T, FXall & BAXTER Financial Services Ltd with Currency Dealing provide access to an electronic trading network, supplied with streaming quotes from the top tier banks in the world. Their matching engines perform limit checks and match orders, usually in less than 100 milliseconds per order. The matching is quote driven and these are the prices that match against all orders. Spreads are discretionary but in general multibank competition creates 1-2 pip spreads on USD Majors and Euro Crosses. The order book is not a routing system that sends orders to individual market makers. It is a live exchange type book working against the best bid/offer of all quotes. By trading through an ECN, a currency trader generally benefits from greater price transparency, faster processing, increased liquidity and more availability in the marketplace. Banks also reduce their costs as there is less manual effort involved in using an ECN for trading.

Tradestation - Daily Report 30th August 2012 Crude Oil Futures

Tradestation - Daily Report 30th August 2012 Crude Oil Futures.The top trading indicators for Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc .

text Courtesy Of Wikipedia
To trade with an ECN, one must be a subscriber or have an account with a broker that provides direct access trading. ECN subscribers can enter orders into the ECN via a custom computer terminal or network protocols. The ECN will then match contra-side orders (i.e. a sell-order is "contra-side" to a buy-order with the same price and share count) for execution. The ECN will post unmatched orders on the system for other subscribers to view. Generally, the buyer and seller are anonymous, with the trade execution reports listing the ECN as the party.
Some ECN brokers may offer additional features to subscribers such as negotiation, reserve size, and pegging, and may have access to the entire ECN book (as opposed to the "top of the book") that real-time market data regarding depth of trading interest.
ECNs are generally facilitated by electronic negotiation, a type of communication between agents that allows cooperative and competitive sharing of information to determine a proper price.
[edit]Negotiation types
The most common paradigm is the electronic auction type. As of 2005, most e-business negotiation systems can only support price negotiations. Traditional negotiations typically include discussion of other attributes of a deal, such as delivery terms or payment conditions. This one-dimensional approach is one of the reasons why electronic markets struggle for acceptance. Multiattributive and combinatorial auction mechanisms are emerging to allow further types of negotiation.
Support for complex multi-attribute negotiations is a critical success factor for the next generation of electronic markets and, more generally, for all types of electronic exchanges. This is what the second type of Electronic negotiation, namely Negotiation Support, addresses. While auctions are essentially mechanisms, bargaining is often the only choice in complex cases or those cases where no choice of partners is given. Bargaining is a hard, error-prone, ambiguous task often performed under time pressure. Information technology has some potential to facilitate negotiation processes which is analyzed in research projects/prototypes such as INSPIRE, Negoisst or WebNS.
The third type of negotiation is automated argumentation, where agents exchange not only values, but also arguments for their offers/counter-offers. This requires agents to be able to reason about the mental states of other market participants.One research area that has paid particular attention to modeling automated negotiations is that of autonomous agents. If negotiations occur frequently, possibly on a minute per minute basis in order to schedule network capacity, or negotiation topics can be clearly defined it may be desirable to automate this coordination effort.
Automated negotiation is a key form of interaction in complex systems composed of autonomous agents. Negotiation is a process of making offers and counteroffers, with the aim of finding an acceptable agreement. During negotiation, each offer is based on its own utility and expectation of what other agents do. This means that a multi criteria decision making is need to be taken for each offer.

Russell TF Futures Ninja Trader Daily Report 29th Aug 2012 Futures

Russell TF Futures Ninja Trader Daily Report 29th Aug 2012 Futures.Whether you want to trade Forex, the Emini Futures, The Dow The Russell or Crude oil you need the best trading software and free signals out there.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc . We have indicators for Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts

text Courtesy Of Wikipedia
In 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 brokers, market makers, Investment banks or stock exchanges. Such platforms allow electronic trading to be carried out by users from any location and are in contrast to traditional floor trading using open outcry and telephone based trading.
Electronic trading platforms typically stream live market prices on which users can trade and may provide additional trading tools, such as charting packages, news feeds and account management functions. Some platforms have been specifically designed to allow individuals to gain access to financial markets that could traditionally only be accessed by specialist trading firms such as allowing margin trading on forex and derivatives such as contract for difference. They may also be designed to automatically trade specific strategies based on technical analysis or to do high-frequency trading.The first electronic trading platforms were typically associated with stock exchanges and allowed brokers to place orders remotely using private dedicated networks and dumb terminals. Early systems would not always provide live streaming prices and instead allowed brokers or clients to place an order which would be confirmed some time later, these were known as 'request for quote' based systems.
Trading systems evolved to allow for live streaming prices and near instant execution of orders as well as using the internet as the underlying network meaning that location became much less relevant. Some electronic trading platforms have built in scripting tools and even APIs allowing traders to develop automatic or algorithmic trading systems and robots, which have been used by high frequency traders.
The client graphical user interface of the electronic trading platforms can be used to trade currencies, equities, future, or options and are also sometimes called trading turrets (this may be true, but is probably a misues of the term, as trading turret refers to the specialized phone appliance used by traders).

S&P 500 Emini Futures Ninja Trader Daily Report 29th Aug 2012 Futures

S&P 500 Emini Futures Ninja Trader Daily Report 29th Aug 2012 Futures.Whether you want to trade Forex, the Emini Futures, The Dow The Russell or Crude oil you need the best trading software and free signals out there.For the worlds fastest trading indicators please go to http://www.sceeto.com please also visit http://www.BinaryForecast.com . Check it out with a free trial for free signals. The free signals on both sites can be used to trade binary options , spread bet, futures forex etc . We have indicators for Ninja Trader , Trade Station ,Multi Charts, and Sierra Charts

text Courtesy Of Wikipedia
Advanced computerized trading platforms and market gateways are becoming standard tools of most types of traders, including high-frequency traders. Broker-dealers now compete on routing order flow directly, in the fastest and most efficient manner, to the line handler where it undergoes a strict set of Risk Filters before hitting the execution venue(s). Ultra Low Latency Direct Market Access (ULLDMA) is a hot topic amongst Brokers and Technology vendors such as Goldman Sachs, Credit Suisse, and UBS. Typically, ULLDMA systems can currently handle high amounts of volume and boast round-trip order execution speeds (from hitting "transmit order" to receiving an acknowledgment) of 10 milliseconds or less.
Such performance is achieved with the use of hardware acceleration or even full-hardware processing of incoming Market data, in association with high-speed communication protocols, such as 10 Gigabit Ethernet or PCI Express. More specifically, some companies provide full-hardware appliances based on FPGA to obtain sub-microsecond end-to-end Market data processing.High-frequency trading (HFT) is the use of sophisticated technological tools to trade securities like stocks or options, and is typically characterized by several distinguishing features:[1][2][3]
It is highly quantitative, employing computerized algorithms to analyze incoming market data and implement proprietary trading strategies;
An investment position is held only for very brief periods of time - from seconds to hours - and rapidly trades into and out of those positions, sometimes thousands or tens of thousands of times a day;[4]
At the end of a trading day there is no net investment position;
It is mostly employed by proprietary firms or on proprietary trading desks in larger, diversified firms;
It is very sensitive to the processing speed of markets and of their own access to the market;
Many high-frequency traders provide liquidity and price discovery to the markets through market-making and arbitrage trading; high-frequency traders also take liquidity to manage risk or lock in profits.
Positions are taken in equities, options, futures, ETFs, currencies, and other financial instruments that can be traded electronically.[5]
High-frequency traders compete on a basis of speed with other high-frequency traders, not long-term investors (who typically look for opportunities over a period of weeks, months, or years), and compete for very small, consistent profits.[6][7] As a result, high-frequency trading has been shown to have a potential Sharpe ratio (measure of reward per unit of risk) thousands of times higher than the traditional buy-and-hold strategies.[8]
Aiming to capture just a fraction of a penny per share or currency unit on every trade, high-frequency traders move in and out of such short-term positions several times each day. Fractions of a penny accumulate fast to produce significantly positive results at the end of every day.[2] High-frequency trading firms do not employ significant leverage, do not accumulate positions, and typically liquidate their entire portfolios on a daily basis.[7]
By 2010 high-frequency trading accounted for over 70% of equity trades in the US and was rapidly growing in popularity in Europe and Asia.
Algorithmic and high-frequency trading were both found to have contributed to volatility in the May 6, 2010 Flash Crash, when high-frequency liquidity providers were in fact found to have withdrawn from the market.[9][10][11][12][13][14][15][16] 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."[1][17]

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High-frequency trading has been the subject of intense public focus since regulators claimed these practices contributed to volatility on May 6, 2010, popularly known as the 2010 Flash Crash,[9][10][11][12][13][14][15][16] a United States stock market crash on May 6, 2010 in which the Dow Jones Industrial Average plunged to its largest intraday point loss, but not percentage loss,[54] in history, only to recover much of those losses within minutes.[55] Another area of controversy, related to SEC and CFTC findings in their joint report on the Flash Crash that equity market "market makers and other liquidity providers widened their quote spreads, others reduced offered liquidity, and a significant number withdrew completely from the markets"[51] during the Flash Crash, is whether high-frequency market makers should be subject to regulations that would require them to stay active in volatile markets.[56] As SEC Chairman Mary Schapiro said in a speech on September 22, 2010, "...high frequency trading firms have a tremendous capacity to affect the stability and integrity of the equity markets. Currently, however, high frequency trading firms are subject to very little in the way of obligations either to protect that stability by promoting reasonable price continuity in tough times, or to refrain from exacerbating price volatility."[57]
Despite studies reporting positive findings about high-frequency trading, including that high-frequency trading reduces volatility and does not pose a systemic risk,[7][36][35][49] and both lowers transaction costs for retail investors,[37][36][35] and at the same time does so without impacting long term investors,[2][7][35] high-frequency trading is the subject of increased debate.[58] This debate has been fueled by U.S. Securities and Exchange Commission and Commodity Futures Trading Commission empirical findings that high-frequency trading contributed to volatility in the May 6, 2010 Flash Crash.[9][10][11][12][13][14][15][16] Politicians, regulators, journalists and market participants have all raised concerns on both sides of the Atlantic.[23][58][59] In September 2010, SEC chairperson Mary Schapiro signaled that US authorities were considering the introduction of regulations targeted at HFT, such as a minimum "time in force" rule, to prevent buy orders being canceled very soon after being issued. Criticisms of this proposed law are that currently exchanges allow excess message traffic to queue up at their servers' ports, where it is processed sequentially at a fixed rate and as a result poses no threat to the exchanges.[7] In addition to this, equity options markets produce far more message volume than equity markets and have consistently handled the data without issue.[7] Some HFT systems cancel many of their orders almost immediately after placing them as they don't intend the trades to carry through; the false orders are used as part of a pinging tactic to discover the upper price other traders are willing to pay.[58] Some high-frequency trading firms state that so many orders get canceled because the orders people get are not the same ones they send. This happens frequently because of an existing regulation regarding re-priced orders.[7]
Another area of concern relates to flash trading. Flash trading is a form of trading in which certain market participants are allowed to see incoming orders to buy or sell securities very slightly earlier than the general market participants, typically 30 milliseconds, in exchange for a fee. According to some sources, the programs can inspect major orders as they come in and use that information to profit.[5] Currently, the majority of exchanges either do not offer flash trading, or have discontinued it, although the exchange Direct Edge currently does offer it to participants. Direct Edge's response to this is that flash trading reduces market impact, increases average size of executed orders, reduces trading latency, and provides additional liquidity.[60] Direct Edge also

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An academic study[37] found that, for large-cap stocks and in quiescent markets during periods of "generally rising stock prices", high-frequency trading lowers the cost of trading and increases the informativeness of quotes;[38] however, it found "no significant effects for smaller-cap stocks"[39], and "it remains an open question whether algorithmic trading and algorithmic liquidity supply are equally beneficial in more turbulent or declining markets...algorithmic liquidity suppliers may simply turn off their machines when markets spike downward."[40]
In September 2011, Nanex, LLC (a high-frequency trading software company) published a report stating the contrary. They looked at the amount of quote traffic compared to the value of trade transactions over 4 and half years and saw a 10-fold decrease in efficiency.[41] Many discussions about HFT focus solely on the frequency aspect of the algorithms and not on their decision-making logic (which is typically kept secret by the companies that develop them). This makes it difficult for observers to pre-identify market scenarios where HFT will dampen or amplify price fluctuations. The growing quote traffic compared to trade value could indicate that more firms are trying to profit from cross-market arbitrage techniques that do not add significant value through increased liquidity when measured globally.
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.
The speeds of computer connections, measured in milliseconds or microseconds, have become important.[42][43] Competition is developing among exchanges for the fastest processing times for completing trades. For example, in 2009 the London Stock Exchange bought a technology firm called MillenniumIT and announced plans to implement its Millennium Exchange platform[44] which they claim has an average latency of 126 microseconds.[45] Since then, competitive exchanges have continued to reduce latency, and today, with turnaround times of three milliseconds available, are useful to traders to pinpoint the consistent and probable performance ranges of 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, in which a small mistake can lead to a large loss. Absolute frequency data play into the development of the trader's pre-programmed instructions.[46]
Spending on computers and software in the financial industry increased to $26.4 billion in 2005.[47]
The brief but dramatic stock market crash of May 6, 2010 was originally alleged to have been caused by high-frequency trading.[48] However, CME Group, a large futures exchange, stated that, insofar as stock index futures traded on CME Group were concerned, its investigation had found no support for the notion that high-frequency trading was related to the crash, and actually stated it had a market stabilizing effect.[49] This conclusion is contradicted in a report on the Flash Crash by the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission, wherein regulators stated that the actions of high-frequency trading firms on May 6, 2010 contributed to volatility during the crash.[9][10][11][12][13][14][15][16] Despite the original perception that high-frequency traders typically cause no market price impact,[7] and have a stabilizing effect in times of volatility,[7][36][49] and some suggestions that they may actually have been a major factor in minimizing and partially reversing the Flash Crash,[50] later reports determined that high-frequency trading had significant price impact and a destabilizing role during the Flash Crash, helping to drive prices down.[9][10][11][12]

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Ticker tape trading
Much information happens to be unwittingly embedded in market data, such as quotes and volumes. By observing a flow of quotes, high-frequency trading machines are capable of extracting information that has not yet crossed the news screens. Since all quote and volume information is public, such strategies are fully compliant with all the applicable laws.
Filter trading is one of the more primitive high-frequency trading strategies that involves monitoring large amounts of stocks for significant or unusual price changes or volume activity. This includes trading on announcements, news, or other event criteria. Software would then generate a buy or sell order depending on the nature of the event being looked for.Event arbitrage
Certain recurring events generate predictable short-term responses in a selected set of securities. High-frequency traders take advantage of such predictability to generate short-term profits.
[edit]Statistical arbitrage
Another set of high-frequency trading strategies are strategies that exploit predictable temporary deviations from stable statistical relationships among securities. Statistical arbitrage at high frequencies is actively used in all liquid securities, including equities, bonds, futures, foreign exchange, etc. Such strategies may also involve classical arbitrage strategies, such as covered interest rate parity in the foreign exchange market, which gives a relationship 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. High-frequency trading allows similar arbitrages using models of greater complexity involving many more than four securities. The TABB Group estimates that annual aggregate profits of high-frequency arbitrage strategies currently exceed US$21 billion.A separate, "naïve" class of high-frequency trading strategies relies exclusively on ultra-low latency direct market access technology. In these strategies, computer scientists rely on speed to gain minuscule advantages in arbitraging price discrepancies in some particular security trading simultaneously on disparate markets.The effects of algorithmic and high-frequency trading in volatile markets are the subject of ongoing research since regulators claim these practices contributed to volatility in the May 6, 2010 Flash Crash, as discussed later in this section.[9][10][11][12][13][16]
"The fast-growing practice of high-frequency trading, in which traders place vast flurries of securities trades, is speeding up execution times for all investors, making it cheaper to buy or sell and posing no risk to small investors." - Chicago Board Options Exchange[35]
Members of the financial industry claim high-frequency trading substantially improves market liquidity,[7] narrows Bid-offer spread, lowers volatility and makes trading and investing cheaper for other market participants

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High-frequency trading is quantitative trading that is characterized by short portfolio holding periods (see Wilmott (2008)). All portfolio-allocation decisions are made by computerized quantitative models. The success of high-frequency trading strategies is largely driven by their ability to simultaneously process volumes of information, something ordinary human traders cannot do. Specific algorithms are closely guarded by their owners and are known as "algos".
Most high-frequency trading strategies fall within one of the following trading strategies.Market making is a set of high-frequency trading strategies that involve placing a limit order to sell (or offer) or a buy limit order (or bid) in order to earn the bid-ask spread. By doing so, market makers provide counterpart to incoming market orders. Although the role of market maker was traditionally fulfilled by specialist firms, this class of strategy is now implemented by a large range of investors, thanks to wide adoption of direct market access. As pointed out by empirical studies[25] this renewed competition among liquidity providers causes reduced effective market spreads, and therefore reduced indirect costs for final investors.
Some high-frequency trading firms use market making as their primary trading strategy.[7] 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 the NASDAQ and the New York Stock Exchange.[26] Building up market making strategies typically involves precise modeling of the target market microstructure[27][28] together with stochastic control techniques.These strategies appear intimately related to the entry of new electronic venues. Academic study of Chi-X's entry into the European equity market reveals that its launch coincided with a large HFT that made markets using both the incumbent market, NYSE-Euronext, and the new market, Chi-X. The study shows that the new market provided ideal conditions for HFT market-making, low fees (i.e., rebates for quotes that led to execution) and a fast system, yet the HFT was equally active in the incumbent market to offload nonzero positions. New market entry and HFT arrival are further shown to coincide with a significant improvement in liquidity supply.

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High-frequency trading has taken place at least since 1999, after the U.S. Securities and Exchange Commission (SEC) authorized electronic exchanges in 1998. At the turn of the 21st century, HFT trades had an execution time of several seconds, whereas by 2010 this had decreased to milli- and even microseconds.[18] Until recently, high-frequency trading was a little-known topic outside the financial sector, with an article published by the New York Times in July 2009 being one of the first to bring the subject to the public's attention.[19]
[edit]Market growth
In the early 2000s, high-frequency trading still accounted for less than 10% of equity orders, but this proportion was soon to begin rapid growth. According to data from the NYSE, trading volume grew by about 164% between 2005 and 2009 for which high-frequency trading might be accounted.[19] As of the first quarter in 2009, total assets under management for hedge funds with high-frequency trading strategies were $141 billion, down about 21% from their peak before the worst of the crises.[20] The high-frequency strategy was first made successful by Renaissance Technologies.[21] Many high-frequency firms are market makers and provide liquidity to the market which has lowered volatility and helped narrow Bid-offer spreads, making trading and investing cheaper for other market participants.[20] In the United States, high-frequency trading firms represent 2% of the approximately 20,000 firms operating today, but account for 73% of all equity orders volume.[22] The largest high-frequency trading firms in the US include names like Getco LLC, Knight Capital Group, Jump Trading, and Citadel LLC. The Bank of England estimates similar percentages for the 2010 US market share, also suggesting that in Europe HFT accounts for about 40% of equity orders volume and for Asia about 5-10%, with potential for rapid growth.[18] By value, HFT was estimated in 2010 by consultancy Tabb Group to make up 56% of equity trades in the US and 38% in Europe

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An automated trading system (ATS) is a computer trading program that automatically submits trades to an exchange. As of the year 2010 more than 70% of the stock shares traded on the NYSE and NASDAQ are generated from automated trading systems.[citation needed] They are designed to trade stocks, futures and forex based on a predefined set of rules which determine when to enter a trade, when to exit it and how much to invest in it.
An example of an early ATS is Instinet. This allows traders to input trades invisibly to the market, with a crossing price determined by a VWAP measure. Instinet also enables anonymous conversations and negotiations to take place between bidders, and so reduces informational costs to the participants.
Trading system designers / programmers often test their automated trading systems on historical or current market data in order to determine whether the underlying algorithm guiding the system is profitable or not. Backtesting software are special trading platforms which enable trading system designer to develop and test their trading systems on historical market data while aiming to produce optimal historical results.High-frequency trading (HFT) is the use of sophisticated technological tools to trade securities like stocks or options, and is typically characterized by several distinguishing features:[1][2][3]
It is highly quantitative, employing computerized algorithms to analyze incoming market data and implement proprietary trading strategies;
An investment position is held only for very brief periods of time - from seconds to hours - and rapidly trades into and out of those positions, sometimes thousands or tens of thousands of times a day;[4]
At the end of a trading day there is no net investment position;
It is mostly employed by proprietary firms or on proprietary trading desks in larger, diversified firms;
It is very sensitive to the processing speed of markets and of their own access to the market;
Many high-frequency traders provide liquidity and price discovery to the markets through market-making and arbitrage trading; high-frequency traders also take liquidity to manage risk or lock in profits.
Positions are taken in equities, options, futures, ETFs, currencies, and other financial instruments that can be traded electronically.[5]
High-frequency traders compete on a basis of speed with other high-frequency traders, not long-term investors (who typically look for opportunities over a period of weeks, months, or years), and compete for very small, consistent profits.[6][7] As a result, high-frequency trading has been shown to have a potential Sharpe ratio (measure of reward per unit of risk) thousands of times higher than the traditional buy-and-hold strategies.[8]
Aiming to capture just a fraction of a penny per share or currency unit on every trade, high-frequency traders move in and out of such short-term positions several times each day. Fractions of a penny accumulate fast to produce significantly positive results at the end of every day.[2] High-frequency trading firms do not employ significant leverage, do not accumulate positions, and typically liquidate their entire portfolios on a daily basis.[7]
By 2010 high-frequency trading accounted for over 70% of equity trades in the US and was rapidly growing in popularity in Europe and Asia.
Algorithmic and high-frequency trading were both found to have contributed to volatility in the May 6, 2010 Flash Crash, when high-frequency liquidity providers were in fact found to have withdrawn from the market.[9][10][11][12][13][14][15][16] 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."[1][17]

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Relation of the stock market to the modern financial system
The financial system in most western countries has undergone a remarkable transformation. One feature of this development is disintermediation. A portion of the funds involved in saving and financing, flows directly to the financial markets instead of being routed via the traditional bank lending and deposit operations. The general public interest in investing in the stock market, either directly or through mutual funds, has been an important component of this process.
Statistics show that in recent decades shares have made up an increasingly large proportion of households' financial assets in many countries. In the 1970s, in Sweden, deposit accounts and other very liquid assets with little risk made up almost 60 percent of households' financial wealth, compared to less than 20 percent in the 2000s. The major part of this adjustment is that financial portfolios have gone directly to shares but a good deal now takes the form of various kinds of institutional investment for groups of individuals, e.g., pension funds, mutual funds, hedge funds, insurance investment of premiums, etc.
The trend towards forms of saving with a higher risk has been accentuated by new rules for most funds and insurance, permitting a higher proportion of shares to bonds. Similar tendencies are to be found in other industrialized countries. In all developed economic systems, such as the European Union, the United States, Japan and other developed nations, the trend has been the same: saving has moved away from traditional (government insured) bank deposits to more risky securities of one sort or another.From experience we know that investors may 'temporarily' move financial prices away from their long term aggregate price 'trends'. (Positive or up trends are referred to as bull markets; negative or down trends are referred to as bear markets.) Over-reactions may occur—so that excessive optimism (euphoria) may drive prices unduly high or excessive pessimism may drive prices unduly low. Economists continue to debate whether financial markets are 'generally' efficient.
According to one interpretation of the efficient-market hypothesis (EMH), only changes in fundamental factors, such as the outlook for margins, profits or dividends, ought to affect share prices beyond the short term, where random 'noise' in the system may prevail. (But this largely theoretic academic viewpoint—known as 'hard' EMH—also predicts that little or no trading should take place, contrary to fact, since prices are already at or near equilibrium, having priced in all public knowledge.) The 'hard' efficient-market hypothesis is sorely tested by such events as the stock market crash in 1987, when the Dow Jones index plummeted 22.6 percent—the largest-ever one-day fall in the United States.[14]
This event demonstrated that share prices can fall dramatically even though, to this day, it is impossible to fix a generally agreed upon definite cause: a thorough search failed to detect any 'reasonable' development that might have accounted for the crash. (But note that such events are predicted to occur strictly by chance, although very rarely.) It seems also to be the case more generally that many price movements (beyond that which are predicted to occur 'randomly') are not occasioned by new information; a study of the fifty largest one-day share price movements in the United States in the post-war period seems to confirm this.[14]

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Market participants include individual retail investors, institutional investors such as mutual funds, banks, insurance companies and hedge funds, and also publicly traded corporations trading in their own shares. Some studies have suggested that institutional investors and corporations trading in their own shares generally receive higher risk-adjusted returns than retail investors.[7]
A few decades ago, worldwide, buyers and sellers were individual investors, such as wealthy businessmen, usually with long family histories to particular corporations. Over time, markets have become more "institutionalized"; buyers and sellers are largely institutions (e.g., pension funds, insurance companies, mutual funds, index funds, exchange-traded funds, hedge funds, investor groups, banks and various other financial institutions).
The rise of the institutional investor has brought with it some improvements in market operations. There has been a gradual tendency for "fixed" (and exorbitant) fees being reduced for all investors, partly from falling administration costs but also assisted by large institutions challenging brokers' oligopolistic approach to setting standardised fees.The stock market is one of the most important sources for companies to raise money. This allows businesses to be publicly traded, or raise additional financial capital for expansion by selling shares of ownership of the company in a public market. The liquidity that an exchange affords the investors gives them the ability to quickly and easily sell securities. This is an attractive feature of investing in stocks, compared to other less liquid investments such as real estate.[citation needed] Some companies actively increase liquidity by trading in their own shares.[11][12]
History has shown that the price of shares and other assets is an important part of the dynamics of economic activity, and can influence or be an indicator of social mood. An economy where the stock market is on the rise is considered to be an up-and-coming economy. In fact, the stock market is often considered the primary indicator of a country's economic strength and development.[citation needed]
Rising share prices, for instance, tend to be associated with increased business investment and vice versa. Share prices also affect the wealth of households and their consumption. Therefore, central banks tend to keep an eye on the control and behavior of the stock market and, in general, on the smooth operation of financial system functions. Financial stability is the raison d'être of central banks.[citation needed]
Exchanges also act as the clearinghouse for each transaction, meaning that they collect and deliver the shares, and guarantee payment to the seller of a security. This eliminates the risk to an individual buyer or seller that the counterparty could default on the transaction.[citation needed]
The smooth functioning of all these activities facilitates economic growth in that lower costs and enterprise risks promote the production of goods and services as well as possibly employment. In this way the financial system is assumed to contribute to increased prosperity

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Participants in the stock market range from small individual stock investors to large hedge fund traders, who can be based anywhere. Their orders usually end up with a professional at a stock exchange, who executes the order of buying or selling.
Some exchanges are physical locations where transactions are carried out on a trading floor, by a method known as open outcry. This type of auction is used in stock exchanges and commodity exchanges where traders may enter "verbal" bids and offers simultaneously. The other type of stock exchange is a virtual kind, composed of a network of computers where trades are made electronically via traders.
Actual trades are based on an auction market model where a potential buyer bids a specific price for a stock and a potential seller asks a specific price for the stock. (Buying or selling at market means you will accept any ask price or bid price for the stock, respectively.) When the bid and ask prices match, a sale takes place, on a first-come-first-served basis if there are multiple bidders or askers 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 (virtual or real). The exchanges provide real-time trading information on the listed securities, facilitating price discovery.
The New York Stock Exchange(NYSE) is a physical exchange, also referred to as a listed exchange – only stocks listed with the exchange may be traded, with a hybrid market for placing orders both electronically and manually on the trading floor. Orders executed on the trading floor enter by way of exchange members and flow down to a floor broker, who goes to the floor trading post specialist for that stock to trade the order. The specialist's job is to match buy and sell orders using open outcry. If a spread exists, no trade immediately takes place—in this case the specialist should use his/her own resources (money or stock) to close the difference after his/her judged time. Once a trade has been made the details are reported on the "tape" and sent back to the brokerage firm, which then notifies the investor who placed the order. Although there is a significant amount of human contact in this process, computers play an important role, especially for so-called "program trading".
The NASDAQ is a virtual listed exchange, where all of the trading is done over a computer network. The process is similar to the New York Stock Exchange. However, buyers and sellers are electronically matched. One or more NASDAQ market makers will always provide a bid and ask price at which they will always purchase or sell 'their' stock.[5]
The Paris Bourse, now part of Euronext, is an order-driven, 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 or the Palais Brongniart. In 1986, the CATS trading system was introduced, and the order matching process was fully automated.
From time to time, active trading (especially in large blocks of securities) have moved away from the 'active' exchanges. Securities firms, led by UBS AG, Goldman Sachs Group Inc. and Credit Suisse Group, already steer 12 percent of U.S. security trades away from the exchanges to their internal systems. That share probably will increase to 18 percent by 2010 as more investment banks bypass the NYSE and NASDAQ and pair buyers and sellers of securities themselves, according to data compiled by Boston-based Aite Group LLC, a brokerage-industry consultant.[6]
Now that computers have eliminated the need for trading floors like the Big Board's, the balance of power in equity markets is shifting. By bringing more orders in-house, where clients can move big blocks of stock anonymously, brokers pay the exchanges less in fees and capture a bigger share of the $11 billion a year that institutional investors pay in trading commissions.

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A stock market or equity market is a public entity (a loose network of economic transactions, not a physical facility or discrete entity) for the trading of company stock (shares) and derivatives at an agreed price; these are securities listed on a stock exchange as well as those only traded privately.
The size of the world stock market was estimated at about $36.6 trillion at the beginning of October 2008.[1] The total world derivatives market has been estimated at about $791 trillion face or nominal value,[2] 11 times the size of the entire world economy.[3] The value of the derivatives market, because it is stated in terms of notional values, cannot be directly compared to a stock or a fixed income security, which traditionally refers to an actual value. Moreover, the vast majority of derivatives 'cancel' each other out (i.e., a derivative 'bet' on an event occurring is offset by a comparable derivative 'bet' on the event not occurring). Many such relatively illiquid securities are valued as marked to model, rather than an actual market price.
The stocks are listed and traded on stock exchanges which are entities of a corporation or mutual organization specialized in the business of bringing buyers and sellers of the organizations to a listing of stocks and securities together. The largest stock market in the United States, by market capitalization, is the New York Stock Exchange (NYSE). In Canada, the largest stock market is the Toronto Stock Exchange. Major European examples of stock exchanges include the Amsterdam Stock Exchange, London Stock Exchange, Paris Bourse, and the Deutsche Börse (Frankfurt Stock Exchange). In Africa, examples include Nigerian Stock Exchange, JSE Limited, etc. Asian examples include the Singapore Exchange, the Tokyo Stock Exchange, the Hong Kong Stock Exchange, the Shanghai Stock Exchange, and the Bombay Stock Exchange. In Latin America, there are such exchanges as the BM&F Bovespa and the BMV.
Market participants include individual retail investors, institutional investors such as mutual funds, banks, insurance companies and hedge funds, and also publicly traded corporations trading in their own shares. Some studies have suggested that institutional investors and corporations trading in their own shares generally receive higher risk-adjusted returns than retail investors