Retrieved September 10,
The benefits of trading the forex markets with liquidity comes with a cost. The cost of participating in a market that has adequate liquidity is that there are many traders who are looking to benefit from creating that liquidity. Capturing most of the headlines these days are the high frequency traders who provide liquidity but also take their pound of flesh for providing this luxury.
Prior to discussing the pros and cons of high frequency trading in the forex market, it is important to track the roots of some of the earliest liquidity providers.
Market makers have been around for more than a century; as specialists on the New York Stock Exchange, these traders were responsible for making sure a proper bid and offer were provided for the stocks they handled.
Based on the supply and demand for a specific stock, the specialist was responsible for finding a fair market price. The specialist would make sure that if a customer order to buy a security was above the best offer, that the transaction was filled at the lowest offer.
As floor trading was replaced by computerized algorithms , the process of providing liquidity switched from humans to machines. This scenario also occurred in the forex markets where large bank dealers were replaced with smaller computerized algorithms. Although in many cases a human dealer is still needed especially for orders that are non-conventional, many liquidity providers in the capital market structure are computerized algorithms that are looking to exploit opportunities and provide liquidity.
It is important to understand that the underlying reason high frequency traders exist is the markets present opportunities to quickly turn a profit and therefore in many cases the algorithms will provide liquidity by consistently placing bids and offers in multiple currency pairs.
High frequency traders are heavy participants in the electronic auctions. An auction brings together buyers and sellers and the process helps explore a range of values until a fair value is discovered. So why is understanding an auction important for those trading the capital markets? The answer is that financial instruments, such as currency pairs, utilize auctions to trade.
Every day buyers and sellers around the world gather in a global electronic marketplace and continuously evaluate the price of an asset in an effort to find the current value at that specific point in time. The more bids and offers involved in an auction, the more likely it is for the auction process to achieve fair value.
High frequency trading strategies describe an algorithm that is trading thousands of times a day, to capture inefficiencies in the exchange rate of a currency pair or some other financial instrument. The concept is a relative term, describing how market participants use technology to gain information, and act upon it, in advance of the rest of the market.
In essence, high frequency traders are front running your order. If the price of a currency pair is off by even half of a pip, the high frequency trader will attempt to capture this inefficiency. High frequency traders initially appeared onto the equity market scene. New regulation allowed electronic exchanges to compete with one another, which left the door open for high frequency traders to step in and search for discrepancies in prices.
High frequency traders rely on extremely low latencies and use high speed connections in conjunction with trading algorithms to exploit inefficiencies created by these exchanges. Many HFT strategies revolve around searching for and sniffing out institutional order flows , by going through the multitude of electronic exchanges available to trade securities. These algorithms would detect a trade and attempt to transact the same trade before the order was filled at another electronic exchange.
These algorithms are front running many securities orders and are predicated on the idea that speed was of the essence.
Speed has become so important to the success of a high frequency operation, that these businesses invest enormous sums of money into building their low latency infrastructure. High frequency traders target low latency machinery in an effort to find the fastest computers available. For a high frequency trader, finding the path of least resistance in communication is the key to successful arbitrage.
So, a proximity war, among high frequency firms, has emerged and created competition for real-estate around a physical exchange location, especially in the equity space.
Why High Frequency Trading Expanded? In the National Market System NMS altered the regulations increasing the transparency for an automated visible market. Additionally, the EA can be set to use just a proportion of the account balance to make it easier to trade several EAs on one and the same account. Start and end times of the weekly trading period can be configured to the respective broker's trading hours.
It is also possible to force the EA to close open position before the weekend. However, the profitability largely depends on the high trading frequency, and draw down periods should be expected in the short term. A Monte-Carlo-Simulation, based on backtests , with a lot size of 0.
The developers grant an unrestricted right to return within 30 days of purchase which will be paid back through Avangate. The licence is valid for one, two or four live or demo accounts and includes support and updates. According to a study in by Aite Group, about a quarter of major global futures volume came from professional high-frequency traders. High-frequency trading is quantitative trading that is characterized by short portfolio holding periods  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 large volumes of information, something ordinary human traders cannot do. 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.
A "market maker" is a firm that stands ready to buy and sell a particular stock on a regular and continuous basis at a publicly quoted price. You'll most often hear about market makers in the context of the Nasdaq or other "over the counter" OTC markets. Market makers that stand ready to buy and sell stocks listed on an exchange, such as the New York Stock Exchange , are called "third market makers.
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. 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. These strategies appear intimately related to the entry of new electronic venues. The study shows that the new market provided ideal conditions for HFT market-making, low fees i. New market entry and HFT arrival are further shown to coincide with a significant improvement in liquidity supply.
The Michael Lewis book Flash Boys: A Wall Street Revolt discusses high-frequency trading, including the tactics of spoofing , layering and quote stuffing, which are all now illegal. 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.
Tick trading often aims to recognize the beginnings of large orders being placed in the market. 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. This strategy has become more difficult since the introduction of dedicated trade execution companies in the s which provide optimal trading for pension and other funds, specifically designed to remove the arbitrage opportunity.
Certain recurring events generate predictable short-term responses in a selected set of securities. 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. Index arbitrage exploits index tracker funds which are bound to buy and sell large volumes of securities in proportion to their changing weights in indices.
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 securities in advance of the trackers and sell them on to them at a profit. Company news in electronic text format is available from many sources including commercial providers like Bloomberg, public news websites, and Twitter feeds.
Automated systems can identify company names, keywords and sometimes semantics to trade news before human traders can process it. 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.
Another aspect of low latency strategy has been the switch from fiber optic to microwave technology for long distance networking. Especially since , there has been a trend to use microwaves to transmit data across key connections such as the one between New York City and Chicago.
High-frequency trading strategies may use properties derived from market data feeds to identify orders that are posted at sub-optimal prices. 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.
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. Members of the financial industry generally claim high-frequency trading substantially improves market liquidity,  narrows bid-offer spread , lowers volatility and makes trading and investing cheaper for other market participants.
An academic study  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; : 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. 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.
Economies of scale in electronic trading 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.