Sceeto Stock Trading Indicators: Oct 14, 2012

Sunday, October 14, 2012

Trading Secret For Crude Oil 12th oct 2012 Daily report

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Truly dark liquidity can be collected off-market in dark pools. Dark pools are generally very similar to standard markets with similar order types, pricing rules and prioritization rules. However, the liquidity is deliberately not advertised—there is no market depth feed. Such markets have no need of an iceberg order type. In addition, they prefer not to print the trades to any public data feed, or if legally required to do so, will do so with as large a delay as legally possible—all to reduce the market impact of any trade. Dark pools are often formed from brokers' order books and other off-market liquidity. When comparing pools, careful checks should be made as to how liquidity numbers were calculated—some venues count both sides of the trade, or even count liquidity that was posted but not filled.
Dark liquidity pools offer institutional investors many of the efficiencies associated with trading on the exchanges' public limit order books but without showing their actions to others. Dark liquidity pools avoid this risk because neither the price nor the identity of the trading company is displayed.[5]
Dark pools are recorded to the national consolidated tape. However, they are recorded as over-the-counter transactions. Therefore, detailed information about the volumes and types of transactions is left to the crossing network to report to clients if they desire and are contractually obligated.[6]
Dark pools allow funds to line up and move large blocks of equities without tipping their hands as to what they are up to. Modern trading platforms and the lack of human interaction have reduced the time scale on market movements. This increased responsiveness of the price of an equity to market pressures has made it more difficult to move large blocks of stock without affecting the price. [7]
Dark pools are run by private brokerages which operate under fewer regulatory and public disclosure requirements than public exchanges.[8] Tabb Group estimates trading on the dark pools accounts for 32% of trades in 2012 vs 26% in 2008.For an asset that can be only publicly traded, the standard price discovery process is generally assumed to ensure that at any given time the price is approximately "correct" or "fair". However, very few assets are in this category since most can be traded off market without printing the trade to a publicly accessible data source. As the proportion of the daily volume of the asset that is traded in such a hidden manner increases, the public price might still be considered fair. However, if public trading continues to decrease as hidden trading increases, it can be seen that the public price does not take into account all information about the asset (in particular it does not take into account what was traded but hidden) and thus the public price may no longer be "fair".
Yet when trades executed in dark pools are incporporated into a post-trade transparency regime, investors have access to them as a part of a consolidated tape. This can aid price discovery because institutional investors who are reluctant to tip their hands in lit market still have to trade and thus a dark pool with post-trade transparency improves price discovery by increasing the amount of trading taking place.[9]
[edit]Market impact

Whilst it is safe to say that trading on a dark venue will reduce market impact, it is very unlikely to reduce it to zero. In particular the liquidity that crosses when there is a transaction has to come from somewhere—and at least some of it is likely to come from the public market, as automated broker systems intercept market-bound orders and instead cross them with the buyer/seller. This disappearance of the opposite side liquidity as it trades with the buyer/seller and leaves the market will cause impact. In addition, the
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Trading Secret For Russell TF Futures 12th oct 2012 Daily report

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In finance, dark pools of liquidity (also referred to as dark liquidity or simply dark pools) is trading volume or liquidity that is not openly available to the public.[1] The bulk of these represent large trades by financial institutions that are offered away from public exchanges so that trades are anonymous. The fragmentation of financial trading venues and electronic trading has allowed dark pools to be created, and they are normally accessed through crossing networks or directly between market participants.
One of the main advantages for institutional investors in using dark pools is for buying or selling large blocks of securities without showing their hand to others and thus avoiding market impact as neither the size of the trade nor the identity are revealed until the trade is filled. But it also means that some market participants are disadvantaged as they cannot see the trades before they are executed; prices are agreed upon by participants in the dark pools, so the market becomes no longer transparent.[2]
There are three major types of dark pools. The first type is independent companies set up to offer a unique differentiated basis for trading. The second type is broker-owned dark pools where clients of the broker interact, most commonly with other clients of the broker (possibly including its own proprietary traders) in conditions of anonymity. Finally, some public exchanges are creating their own dark pools to allow their clients the benefits of anonymity and non-display of orders while offering an exchange ‘infrastructure’. Depending on the precise way in which a ‘dark’ pool operates and interacts with other venues it may be considered, and indeed referred to by some vendors as a ‘grey’ pool.Some markets allow dark liquidity to be posted inside the existing limit order book alongside public liquidity, usually through the use of iceberg orders.[4] Iceberg orders generally specify an additional display quantity, smaller than the overall order quantity. The order is queued along with other orders but only the display quantity is printed to the market depth. When the order reaches the front of its price queue, only the display quantity is filled before the order is automatically put at the back of the queue and must wait for its next chance to get a fill. Such orders will, therefore, get filled less quickly than the fully public equivalent, and they often carry an explicit cost penalty in the form of a larger execution cost charged by the market. Iceberg orders are not truly dark either, as the trade is usually visible after the fact in the market's public trade feed.
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Trading Secret For Forex Euro USD 6E 12th oct 2012 Daily report

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Alternative trading systems (ATS), are United States Securities and Exchange Commission approved non-exchange trading venues specifically designed to match buyers and sellers to find counterparties for transactions, instead of trading large blocks of shares on the normal exchange, a practice that can skew the market price in a particular direction, depending on a security's market capitalization and trading volume.
ATS have to be distinguished from electronic communication networks (ECNs), that are a "fully electronic subset of ATSs that automatically and anonymously match orders".[1] The equivalent term of ECN under European legislation is a Multilateral Trading Facility (MTF). These venues play an important role in public markets for allowing alternative means of accessing liquidity.
Rule 300(a) of the SEC's Regulation ATS provides the following legal definition of an "alternative trading system":
Any organization, association, person, group of persons, or system:
That constitutes, maintains, or provides a market place or facilities for bringing together purchasers and sellers of securities or for otherwise performing with respect to securities the functions commonly performed by a stock exchange within the meaning of Rule 3b-16 of this chapter; and
That does not:
Set rules governing the conduct of subscribers other than the conduct of such subscribers' trading on such organization, association, person, group of persons, or system; or
Discipline subscribers other than by exclusion from trading.
Regulation ATS was introduced by the SEC in 1998 and is designed to protect investors and resolve any concerns arising from this type of trading system. Regulation ATS requires stricter record keeping and demands more intensive reporting on issues such as transparency once the system reaches more than 5% of the trading volume for any given security.
Specifically, it requires that an alternative trading system comply with the reporting and record keeping requirements Rule 301 (b)(5)(ii) of Reg ATS, if during at least 4 of the preceding 6 calendar months, such alternative trading system had:
With respect to any NMS stock, 5 percent or more of the average daily volume in that security reported by an effective transaction reporting plan;
With respect to an equity security that is not an NMS stock and for which transactions are reported to a self-regulatory organization, 5 percent or more of the average daily trading volume in that security as calculated by the self-regulatory organization to which such transactions are reported;
With respect to municipal securities, 5 percent or more of the average daily volume traded in the United States; or
With respect to corporate debt securities, 5 percent or more of the average daily volume traded in the United States.
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Trading Secret For S&P 500 Emini Futures 12th oct 2012 Daily report

Trading Secret For S&P 500 Emini Futures 12th oct 2012 Daily report. A famous saying give a man a fish he'll feed his family for a day , teach the man to fish he'll feed his family forever. Want to know this big trading secret. It is no secret the bots control the markets these days. We want you to be able to feed your family. Thats why sceeto exists to show traders like you when the bots or high frequency traders are active and in what direction. Using our tools we show you how to jump on board their trades whether up or down and we do it in real time. get a free trial now at http://www.sceeto.com learn to fish , stalk the bots and catch the big moves.
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Though its development may have been prompted by decreasing trade sizes caused by decimalization, algorithmic trading has reduced trade sizes further. Jobs once done by human traders are being switched to computers. The speeds of computer connections, measured in milliseconds and even microseconds, have become very important.[57][58]
More fully automated markets such as NASDAQ, Direct Edge and BATS, in the US, have gained market share from less automated markets such as the NYSE. Economies of scale in electronic trading have contributed to lowering commissions and trade processing fees, and contributed to international mergers and consolidation of financial exchanges.
Competition is developing among exchanges for the fastest processing times for completing trades. For example, in June 2007, the London Stock Exchange launched a new system called TradElect that promises an average 10 millisecond turnaround time from placing an order to final confirmation and can process 3,000 orders per second.[59] Since then, competitive exchanges have continued to reduce latency with turnaround times of 3 milliseconds available. This is of great importance to high-frequency traders, because they have to attempt to pinpoint the consistent and probable performance ranges of given financial instruments. These professionals are often dealing in versions of stock index funds like the E-mini S&Ps, because they seek consistency and risk-mitigation along with top performance. They must filter market data to work into their software programming so that there is the lowest latency and highest liquidity at the time for placing stop-losses and/or taking profits. With high volatility in these markets, this becomes a complex and potentially nerve-wracking endeavor, where a small mistake can lead to a large loss. Absolute frequency data play into the development of the trader's pre-programmed instructions.[60]
Spending on computers and software in the financial industry increased to $26.4 billion in 2005.[1]
[edit]Communication standards.Algorithmic trades require communicating considerably more parameters than traditional market and limit orders. A trader on one end (the "buy side") must enable their trading system (often called an "order management system" or "execution management system") to understand a constantly proliferating flow of new algorithmic order types. The R&D and other costs to construct complex new algorithmic orders types, along with the execution infrastructure, and marketing costs to distribute them, are fairly substantial. What was needed was a way that marketers (the "sell side") could express algo orders electronically such that buy-side traders could just drop the new order types into their system and be ready to trade them without constant coding custom new order entry screens each time.
FIX Protocol LTD http://www.fixprotocol.org is a trade association that publishes free, open standards in the securities trading area. The FIX language was originally created by Fidelity Investments, and the association Members include virtually all large and many midsized and smaller broker dealers, money center banks, institutional investors, mutual funds, etc. This institution dominates standard setting in the pretrade and trade areas of security transactions. In 2006-2007 several members got together and published a draft XML standard for expressing algorithmic order types. The standard is called FIX Algorithmic Trading Definition Language (FIXatdl).[61] The first version of this standard, 1.0 was not widely adopted due to limitations in the specification, but the second version, 1.1 (released in March 2010) is expected to achieve broad adoption and in the process dramatically reduce time-to-market and costs associated with distributing new algorithms.
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When Pigs Fly Daily Report Crude Oil Futures 11th Oct 2012

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"When pigs fly" is an adynaton, a way of saying that something will never happen. The phrase is often used for humorous effect, to scoff at over-ambition. There are numerous variations on the theme; when an individual with a reputation for failure finally succeeds, onlookers may sarcastically claim to see a flying pig. ("Hey look! A flying pig!") [1] Other variations on the phrase include "And pigs will fly," this one in retort to an outlandish statement.
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Financial market news is now being formatted by firms such as Need To Know News, Thomson Reuters, Dow Jones, and Bloomberg, to be read and traded on via algorithms.
"Computers are now being used to generate news stories about company earnings results or economic statistics as they are released. And this almost instantaneous information forms a direct feed into other computers which trade on the news."[50]
The algorithms do not simply trade on simple news stories but also interpret more difficult to understand news. Some firms are also attempting to automatically assign sentiment (deciding if the news is good or bad) to news stories so that automated trading can work directly on the news story.[51]
"Increasingly, people are looking at all forms of news and building their own indicators around it in a semi-structured way," as they constantly seek out new trading advantages said Rob Passarella, global director of strategy at Dow Jones Enterprise Media Group. His firm provides both a low latency news feed and news analytics for traders. Passarella also pointed to new academic research being conducted on the degree to which frequent Google searches on various stocks can serve as trading indicators, the potential impact of various phrases and words that may appear in Securities and Exchange Commission statements and the latest wave of online communities devoted to stock trading topics.[51]
"Markets are by their very nature conversations, having grown out of coffee houses and taverns", he said. So the way conversations get created in a digital society will be used to convert news into trades, as well, Passarella said.[51]
“There is a real interest in moving the process of interpreting news from the humans to the machines” says Kirsti Suutari, global business manager of algorithmic trading at Reuters. "More of our customers are finding ways to use news content to make money."[50]
An example of the importance of news reporting speed to algorithmic traders was an advertising campaign by Dow Jones (appearances included page W15 of the Wall Street Journal, on March 1, 2008) claiming that their service had beaten other news services by 2 seconds in reporting an interest rate cut by the Bank of England.
In July 2007, Citigroup, which had already developed its own trading algorithms, paid $680 million for Automated Trading Desk, a 19-year-old firm that trades about 200 million shares a day.[52] Citigroup had previously bought Lava Trading and OnTrade Inc.
In late 2010, The UK Government Office for Science initiated a Foresight project investigating the future of computer trading in the financial markets,[53] led by Dame Clara Furse, ex-CEO of the London Stock Exchange and in September 2011 the project published its initial findings in the form of a three-chapter working paper available in three languages, along with 16 additional papers that provide supporting evidence.[54] All of these findings are authored or co-authored by leading academics and practitioners, and were subjected to anonymous peer-review. The Foresight project is set to conclude in late 2012.
In September 2011, RYBN has launched "ADM8",[55] an open source Trading Bot prototype, already active on the financial markets.
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When Pigs Fly Daily Report Russell TF Futures 11th Oct 2012

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"When pigs fly" is an adynaton, a way of saying that something will never happen. The phrase is often used for humorous effect, to scoff at over-ambition. There are numerous variations on the theme; when an individual with a reputation for failure finally succeeds, onlookers may sarcastically claim to see a flying pig. ("Hey look! A flying pig!") [1] Other variations on the phrase include "And pigs will fly," this one in retort to an outlandish statement.
text courtesy of Wikipedia
“The downside with these systems is their black box-ness,” Mr. Williams said. “Traders have intuitive senses of how the world works. But with these systems you pour in a bunch of numbers, and something comes out the other end, and it’s not always intuitive or clear why the black box latched onto certain data or relationships.” [33]
“The Financial Services Authority has been keeping a watchful eye on the development of black box trading. In its annual report the regulator remarked on the great benefits of efficiency that new technology is bringing to the market. But it also pointed out that ‘greater reliance on sophisticated technology and modelling brings with it a greater risk that systems failure can result in business interruption’.” [44]
UK Treasury minister Lord Myners has warned that companies could become the "playthings" of speculators because of automatic high-frequency trading. Lord Myners said the process risked destroying the relationship between an investor and a company. [45]
Other issues include the technical problem of latency or the delay in getting quotes to traders,[46] security and the possibility of a complete system breakdown leading to a market crash. [47]
"Goldman spends tens of millions of dollars on this stuff. They have more people working in their technology area than people on the trading desk...The nature of the markets has changed dramatically." [48]
On 1st of August 2012 Knight Capital Group experienced a technology issue in their automated trading system (Knight Capital Group Provides Update Regarding August 1st Disruption To Routing In NYSE-listed Securities), causing a loss of $440 million.
This issue was related to Knight's installation of trading software and resulted in Knight sending numerous erroneous orders in NYSE-listed securities into the market. This software has been removed from the company's systems. [..] Clients were not negatively affected by the erroneous orders, and the software issue was limited to the routing of certain listed stocks to NYSE. Knight has traded out of its entire erroneous trade position, which has resulted in a realized pre-tax loss of approximately $440 million.
Algorithmic and HFT were shown to have contributed to volatility during the May 6, 2010 Flash Crash, [11][13] when the Dow Jones Industrial Average plunged about 600 points only to recover those losses within minutes. At the time, it was the second largest point swing, 1,010.14 points, and the biggest one-day point decline, 998.5 points, on an intraday basis in Dow Jones Industrial Average history. [49]
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When Pigs Fly Daily Report Forex Euro USD 6E Futures 11th Oct 2012

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"When pigs fly" is an adynaton, a way of saying that something will never happen. The phrase is often used for humorous effect, to scoff at over-ambition. There are numerous variations on the theme; when an individual with a reputation for failure finally succeeds, onlookers may sarcastically claim to see a flying pig. ("Hey look! A flying pig!") [1] Other variations on the phrase include "And pigs will fly," this one in retort to an outlandish statement.
text courtesy of Wikipedia
HFT is often confused with low-latency trading that uses computers that execute trades within milliseconds, or "with extremely low latency" in the jargon of the trade. Low-latency traders depend on ultra-low latency networks. They profit by providing information, such as competing bids and offers, to their algorithms microseconds faster than their competitors.[5] The revolutionary advance in speed has led to the need for firms to have a real-time, colocated trading platform to benefit from implementing high-frequency strategies.[5] Strategies are constantly altered to reflect the subtle changes in the market as well as to combat the threat of the strategy being reverse engineered by competitors. There is also a very strong pressure to continuously add features or improvements to a particular algorithm, such as client specific modifications and various performance enhancing changes (regarding benchmark trading performance, cost reduction for the trading firm or a range of other implementations). This is due to the evolutionary nature of algorithmic trading strategies – they must be able to adapt and trade intelligently, regardless of market conditions, which involves being flexible enough to withstand a vast array of market scenarios. As a result, a significant proportion of net revenue from firms is spent on the R&D of these autonomous trading systems.Most of the algorithmic strategies are implemented using modern programming languages, although some still implement strategies designed in spreadsheets. Increasingly, the algorithms used by large brokerages and asset managers are written to the FIX Protocol's Algorithmic Trading Definition Language (FIXatdl), which allows firms receiving orders to specify exactly how their electronic orders should be expressed. Orders built using FIXatdl can then be transmitted from traders' systems via the FIX Protocol.[41] Basic models can rely on as little as a linear regression, while more complex game-theoretic and pattern recognition[42] or predictive models can also be used to initiate trading. Neural networks and genetic programming have been used to create these models.
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When Pigs Fly Daily Report S&P 500 Emini Futures 11th Oct 2012

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"When pigs fly" is an adynaton, a way of saying that something will never happen. The phrase is often used for humorous effect, to scoff at over-ambition. There are numerous variations on the theme; when an individual with a reputation for failure finally succeeds, onlookers may sarcastically claim to see a flying pig. ("Hey look! A flying pig!") [1] Other variations on the phrase include "And pigs will fly," this one in retort to an outlandish statement.
text courtesy of Wikipedia
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 (DOT, and later SuperDOT), which routed orders electronically to the proper trading post, which executed them manually. The "opening automated reporting system" (OARS) aided the specialist in determining the market clearing opening price (SOR; Smart Order Routing).
Program trading is defined by the New York Stock Exchange as an order to buy or sell 15 or more stocks valued at over US$1 million total. In practice this means that all program trades are entered with the aid of a computer. In the 1980s program trading became widely used in trading between the S&P500 equity and futures markets.
In stock index arbitrage a trader buys (or sells) a stock index futures contract such as the S&P 500 futures and sells (or buys) a portfolio of up to 500 stocks (can be a much smaller representative subset) at the NYSE matched against the futures trade. The program trade at the NYSE would be pre-programmed into a computer to enter the order automatically into the NYSE’s electronic order routing system at a time when the futures price and the stock index were far enough apart to make a profit.
At about the same time portfolio insurance was designed to create a synthetic put option on a stock portfolio by dynamically trading stock index futures according to a computer model based on the Black–Scholes option pricing model.
Both strategies, often simply lumped together as "program trading", were blamed by many people (for example by the Brady report) for exacerbating or even starting the 1987 stock market crash. Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community.[21]
Financial markets with fully electronic execution and similar electronic communication networks developed in the late 1980s and 1990s. In the U.S., decimalization, which changed the minimum tick size from 1/16 of a dollar (US$0.0625) to US$0.01 per share, may have encouraged algorithmic trading as it changed the market microstructure by permitting smaller differences between the bid and offer prices, decreasing the market-makers' trading advantage, thus increasing market liquidity.
This increased market liquidity led to institutional traders splitting up orders according to computer algorithms so they could execute orders at a better average price. These average price benchmarks are measured and calculated by computers by applying the time-weighted average price or more usually by the volume-weighted average price.
A further encouragement for the adoption of algorithmic trading in the financial markets came in 2001 when a team of IBM researchers published a paper[22] at the International Joint Conference on Artificial Intelligence where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard's ZIP) could consistently out-perform human traders. MGD was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7;[23] the ZIP algorithm had been invented at HP by Dave Cliff (professor) in 1996.[24] In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.
As more electronic markets opened, other algorithmic trading strategies were introduced. These strategies are more easily implemented by computers, because machines can react more rapidly to temporary mispricing and examine prices from several markets simultaneously.
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The Bots Are In Control Crude Oil 10th Oct 2012 Daily Report

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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 "
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The Bots Are In Control Russell TF 10th Oct 2012 Daily Report

The Bots Are In Control Russell TF 10th Oct 2012 Daily Report.Did you ever see the trickery by the Wizard in the wizard of oz . All those smoke and mirrors tricks? Well he has nothing on the trading bots of the stock market. They control what way the market moves most of the time. You need to track them live to see what they are doing. Sign up now for sceeto and track the bots in real time at http://www.sceeto.com . Sceeto is real time and gives you trading alerts or signals based on what the big program trading bots are doing.
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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%..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.[8]
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The Bots Are In Control Forex Euro USD 6E 10th Oct 2012 Daily Report

The Bots Are In Control Forex Euro USD 6E 10th Oct 2012 Daily Report.Did you ever see the trickery by the Wizard in the wizard of oz . All those smoke and mirrors tricks? Well he has nothing on the trading bots of the stock market. They control what way the market moves most of the time. You need to track them live to see what they are doing. Sign up now for sceeto and track the bots in real time at http://www.sceeto.com . Sceeto is real time and gives you trading alerts or signals based on what the big program trading bots are doing.
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Most technical analysis software includes a library of de-facto standard indicators (e.g. moving averages and MACD). Some software will also provide a mean to customize, combine or create new indicators. This is typically achieved with a proprietary scripting or graphical language.
[edit]Data feed
Technical analysis software is typically used with end of day (EOD), delayed or real time data feeds. EOD data feeds provide the end of day closing price for the given equity and is typically updated once a day at market close. Delayed data is typically delayed 15 to 30 minutes depending on the exchange and is the most commonly used data feed type.[citation needed] Real time data feeds provide tick by tick 'real time' data. Real time data is licensed on a per-exchange basis whereas delayed data is typically purchased on a regional basis, such as US markets, rather than an exchange basis.[citation needed]
[edit]Broker interface
Some technical analysis software can be integrated with brokerage platforms to enable traders to place trades via a user interface that they are familiar with. Typically these software providers try to differentiate themselves from the brokerage software through enhanced features such as automated trading.
[edit]Platforms

Technical analysis software is available in the form of commercial or open source software. Such software may be available on a computer, or on a mobile phone or personal digital assistant (PDA). Mobile phones and PDAs allow a user to access online technical analysis packages when away from their computer. However, packages that require the use of Java applets may not work on older model mobile phones or PDAs. Online technical analysis software packages provide access from any Internet-connected computer (including a suitably equipped mobile or PDA), but may require the user to store their information with the provider. Installed, downloaded software will only be available on the computers that the user has downloaded and installed it on.Fundamental analysis of a business involves analyzing its financial statements and health, its management and competitive advantages, and its competitors and markets. When applied to futures and forex, it focuses on the overall state of the economy, interest rates, production, earnings, and management. When analyzing a stock, futures contract, or currency using fundamental analysis there are two basic approaches one can use; bottom up analysis and top down analysis.[1] The term is used to distinguish such analysis from other types of investment analysis, such as quantitative analysis and technical analysis.
Fundamental analysis is performed on historical and present data, but with the goal of making financial forecasts. There are several possible objectives:
to conduct a company stock valuation and predict its probable price evolution,
to make a projection on its business performance,
to evaluate its management and make internal business decisions,
to calculate its credit risk.
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The Bots Are In Control S&P 500 Emini 10th Oct 2012 Daily Report

The Bots Are In Control S&P 500 Emini 10th Oct 2012 Daily Report. Did you ever see the trickery by the Wizard in the wizard of oz . All those smoke and mirrors tricks? Well he has nothing on the trading bots of the stock market. They control what way the market moves most of the time. You need to track them live to see what they are doing. Sign up now for sceeto and track the bots in real time at http://www.sceeto.com . Sceeto is real time and gives you trading alerts or signals based on what the big program trading bots are doing.
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A graphical interface that presents price, volume and technical analysis indicators through a variety of visual interfaces such as line, bar, candlestick and open-high-low-close (OHLC) charts. The chart data is presented as a time series and users typically have the ability to view historical data with varying interval (sampling) periods. Interval periods range from seconds through to months; short term traders tend to use frequent interval periods, such as 1 minute i.e. the price data is updated every 1 minute, whereas longer term traders tend to use daily, weekly or monthly interval periods when trying to identify price and technical analysis trends. Some charting packages enable users to draw support and resistance trend line or for example Fibonacci retracements to help establish trending patterns.
[edit]Back testing
Enables traders to test technical analysis investment timing strategies against historical price movement for one or more specific securities. Strategies are compared to each other using diverse performance measurements such as maximum drawdown, annual profit and Sharpe ratio. The objective is to try and develop a trading strategy based on technical analysis indicator criteria, which will generate a positive return. This concept was computerized and introduced to traders by Louis B. Mendelsohn in 1983 with his ProfitTaker Futures Trading Software (see August 2010 issue of Stocks, Futures & Options Magazine).
[edit]Optimization
A process of testing technical analysis indicator parameters, with the view to developing an investment strategy that generates the maximum return based on historical price movement. The optimization process is achieved through the fine-tuning of the associated technical analysis charting parameters. Typically technical analysis indicators have a range of parameters that can be adjusted, such as the interval period and the technical analysis indicator variables. For example the stochastic indicator has four parameters that effect its results: %k, %d, slowing period, interval period. Optimization must be performed carefully to avoid curve fitting. Back testing of an over-optimized system will perform real-time. One way to diminish over-optimization is by carrying out optimization on historical data and then performing future testing (sometimes referred to as 'out of sample') before making a final evaluation of a trading strategy.
[edit]Scanner
Scanners enable users to 'scan' the market, be it stocks, options, currencies etc., to identify investment opportunities that meet a user's specific investment criteria. Using a technical analysis scanner, a user could, for example, scan the market to identify oversold stocks that have stochastic and RSI value of less than 20% and 30 respectively.
[edit]Alerts
Alert software is used to monitor specific equities, such as stocks, options, currencies, warrants, etc., and provide a notification of when specific price, volume and technical analysis investment conditions are met. As an example, a person who uses technical analysis might want to be notified when the RSI indicator rises above 70, followed by the price falling below its 20 day moving average; using alerting software the user will be able to create an alert, which will provide a notification of when the technical analysis investment conditions are met. When alert conditions are met, a notification is typically communicated via an on screen pop up or sent as an email, instant message or text alert (to a mobile phone).
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