History[ edit ] High-frequency trading has taken place at least since the s, mostly in the form of specialists and pit traders buying and selling positions at the physical location of the exchange, with high-speed telegraph service to other exchanges.
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The high-frequency strategy was first made popular by Renaissance Technologies  who use both HFT and quantitative aspects in their trading. Many high-frequency firms are market makers and provide liquidity to the market which lowers volatility and helps narrow bid-offer spreadsmaking trading and investing cheaper for other market participants.
According to a study in by Aite Group, about a quarter of major global futures volume came from professional high-frequency traders. The success of high-frequency trading strategies is largely driven by their ability to simultaneously process large volumes of information, something ordinary human traders cannot do.
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Specific algorithms are closely guarded by their owners. Many practical algorithms are in fact quite simple arbitrages which could previously have been performed at lower frequency—competition tends to occur through who can execute them the fastest rather than who can create new breakthrough algorithms. The common types of high-frequency trading include several types of market-making, event arbitrage, statistical arbitrage, and latency arbitrage.
Most high-frequency trading strategies are not fraudulent, but instead exploit minute deviations from market equilibrium. You'll most often hear about market makers in the context of the Nasdaq or other "over the counter" OTC markets.
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Market makers that stand ready to buy and sell stocks listed on an exchange, such as the New York Stock Exchangeare called "third raportul zilei de tranzacționare a comercianților makers". Many OTC stocks have more than one market-maker.
Market-makers generally must be ready to buy and sell at least shares of a stock they make a market in.
As a result, a large order from an investor may have to be filled by a number of market-makers at potentially different prices. There can be a significant overlap between a "market maker" and "HFT firm".
HFT firms characterize their business as "Market making" — 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.
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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,  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 strategy.
Building up market making strategies typically involves precise modeling of the target market microstructure   together with stochastic control techniques. The study shows that the new market provided ideal conditions for HFT market-making, low fees i.
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New market entry and HFT arrival are further shown to coincide with a significant improvement in liquidity supply. It involves quickly entering and withdrawing a large number of orders in an attempt to flood the market creating confusion in the market and trading opportunities for high-frequency traders.
Much information happens to be unwittingly embedded in market data, such as quotes and volumes. By observing a flow of quotes, computers 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.
For example, a large order from a pension fund to buy will take place over several hours or even days, and will cause a rise in price due to increased demand.
An arbitrageur can try to spot this happening then buy up the security, then profit from selling back to the pension fund.
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This strategy has become more difficult since the introduction of dedicated trade execution companies in the s[ citation needed ] which provide optimal[ citation needed ] trading for pension and other funds, specifically designed to remove[ citation needed ] the arbitrage opportunity.
Event arbitrage[ edit ] Certain recurring events generate predictable short-term responses in a selected set of securities.
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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 marketwhich 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.
If a HFT firm is able to access and process information which predicts these changes before the tracker funds do so, they can buy up raportul zilei de tranzacționare a comercianților in advance of the trackers and sell them on to them at a profit. News-based trading[ edit ] Company news in electronic text format is available from many sources including commercial providers like Bloombergpublic news websites, and Twitter feeds. Automated systems can identify company names, keywords and sometimes semantics to make news-based trades before human traders can process the news.
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Low-latency strategies[ edit ] 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.
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Especially sincethere has been a trend to use microwaves to transmit data across key connections such as the one between New York City and Chicago. Such orders may offer a profit to their counterparties that high-frequency traders can try to obtain. Examples of these features include the age of an order  or the sizes of displayed orders.
Securities and Exchange Commission has made the following warnings to day traders:  Be prepared to suffer severe financial losses Day traders do not "invest" Day trading is an extremely stressful and expensive full-time job Day traders depend heavily on borrowing money or buying stocks on margin Don't believe claims of easy profits Watch out for "hot tips" and "expert advice" from newsletters and websites catering to day traders Remember that "educational" seminars, classes, and books about day trading may not be objective Check out day trading firms with your state securities regulator Most traders who day trade lose money. Based on trading records from toit was concluded that day trading is almost uniformly unprofitable: We show that it is virtually impossible for individuals to compete with HFTs and day trade for a living, contrary to what course providers claim.
Effects[ edit ] The effects of algorithmic and high-frequency trading are the subject of ongoing research. High frequency trading causes regulatory concerns as a contributor to market fragility.
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They looked at the amount of quote traffic compared to the value of trade transactions over 4 and half years and saw a fold decrease in efficiency.