High-Frequency Trading in the Foreign Exchange Market
High-frequency trading uses algorithms to spot and take advantage of a variety of market inefficiencies. They use properties of orders such as age or size to identify sub-optimal prices and make a profit.
These opportunities often last for half the time it takes to blink. So, traders have to be fast to spot them.
High-Tech Algorithms
In high-frequency trading, computers process information at extremely fast speeds. The aim is to gain an edge over other traders by transferring orders into and out of the market milliseconds before competitors do. This is a complex operation and requires sophisticated software.
This software is usually written in languages like Python, R, Matlab and C. It has to be fault-tolerant and scalable because there is always a chance that the system will be attacked by malicious agents who want to disrupt the flow of trades. The speed required for high-frequency trading also makes it difficult to backtest systems as the results would not be representative of live trading conditions.
While some critics claim that the algorithms used in high frequency trading are designed to first trick, and then take advantage of the market, others argue that the technology is a necessary tool to keep markets efficient. For instance, by routing orders directly to trading venues with ultra-low latency, HFT firms can avoid the slow response times of middlemen and make more profits.
In addition, HFT firms create a lot of liquidity by trading millions of shares each day. This liquidity is a valuable service and they get paid for it by receiving discounted transaction fees from trading venues. However, these benefits are based on volume and the returns per trade are tiny, so firms need to complete a large number of trades to benefit.
High-Speed Trading
High-frequency trading involves making a large number of small trades, often at very high volume. These traders use complex algorithms that consider market data and a wide range of indicators to determine whether or not to make a trade. The trades are typically executed in nanoseconds and can lead to profits of a fraction of a cent or more.
However, this type of trading has become increasingly expensive as firms compete for ultra-low latency, which is the time it takes for data to reach a trader’s computer from the exchange. Firms also pay for co-location services, which is a facility where they can rent space in a trading venue’s data centre or server to get access to this information at an even faster speed.
Many critics of high-frequency trading say that it gives big institutions with the resources to make such trades an unfair advantage over smaller organizations and individual investors. They point to a practice called electronic front-running, in which high-speed traders spot orders on one exchange and then quickly buy shares on other exchanges to profit from the order. They say this is illegal, but it is difficult to regulate because the stock market does not actually exist as a single entity.
Some proposals to combat this include imposing a tiny fee on financial transactions, known as a Tobin tax. This would be a very slight charge on each trade, but it could render most high-frequency trading unprofitable.
High-Volume Trading
The high-volume trading part of high-frequency trading refers to the fact that these algorithms can make a huge number of trades – millions, in fact – at a rate that would be impossible for human traders. These trades are made by sophisticated software running on major machines – and it’s not cheap!
It takes big money to run such a system, and the profit margins are razor thin. But the fact that it’s all done by computer means there are very few barriers to entry.
As a result, there are now several very large HFT firms operating in the market. These firms typically characterise themselves as market makers, providing a counterparty for incoming orders. This can help reduce the overall bid-ask spread, which in turn lowers indirect costs for final investors.
Arbitrage is another strategy that can be used by HFTs. This involves buying and selling assets on different exchanges to take advantage of price discrepancies. Some believe that this can help equilibrate the market by making it more aware of mispriced assets.
There are some concerns that high-frequency trading is harming the quality of market prices, especially in the forex market. The fact is that these traders are making millions of trades at a time, and even small changes can have an impact on the prices of individual currency pairs. However, most observers agree that the benefits of HFT far outweigh the negatives.
Dark Pools
As the name suggests, dark pools are trading platforms that do not make their trade data public. They allow large traders to place orders without impacting the market as a whole. This private trading has been growing in popularity because of the benefits that it offers. One of these benefits is that it allows large investors to avoid competition from other traders who are also trying to buy or sell the same shares in the market. Another benefit is that it helps to keep prices stable in a volatile market.
However, some people worry that dark pools could lead to inefficiencies in the market. For example, they may create an uneven playing field for small and medium-sized investors. They may also limit the quality of price discovery, because they can hide information from other users. Finally, they may drain liquidity from exchanges, which can cause them to lose value.
Despite these concerns, dark pool trading remains popular with institutional traders. It gives them the ability to execute large orders at a low cost, and it allows them to bypass the servers that feed high-frequency trading algorithms with crucial trade data. In addition, it is not necessary to buy or sell from an official exchange to use a dark pool. Therefore, many institutions are using them to lower their transaction costs and improve the efficiency of the marketplace.
