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All you need to know about High Frequency Trading

Hello friends traders!

Surely, many of you have heard about the concept of "High Frequency Trading" more than once. High-frequency trading has become a very popular topic over the last ten years and has provided significant market improvements. These improvements relate to lower volatility, improved market stability, improved transparency and lower costs for traders and investors.

Today I have prepared for you a lot of information about what High Frequency Trading is all about, regarding the use of HFT systems in modern financial markets, various HFT strategies, history and development prospects of this trading area. Let's get started!

Market changes over the past decades

First, let's look at the history of the development of modern markets in order to understand the prerequisites for the appearance of hft. Over the past couple of decades, the demand for computer technology among consumers has led to a significant drop in the prices of equipment for trade. As a result of the application of advanced technologies and subsequent investments in software, trading platforms have become much more affordable and powerful. In addition, an increase in terminal fault tolerance, an increase in the reliability of order execution, and the provision of platforms for connecting and developing proprietary software have led to an increasing complexity of the trading process.

The figure above illustrates the main directions of the financial services market in the 70s of the last century. Here's what happens to the market today:

In the 70s, the main participants in financial markets were organizations and individual large participants, which currently occupy leading positions. Basically, these were various funds - pension, mutual funds, hedge funds. They were also joined by private traders, market makers and various intermediaries.

Transaction costs were very high, and securities turnover was quite low. There was also a high probability of errors in the processing of orders, since they were all processed manually. Most of the traders in those days relied primarily on their own experience and intuition, rather than on technical or fundamental analysis due to the complexity of the calculations.

Now let's take a look at the markets today. New entrants successfully compete with financial tycoons, because today high technology, complex mathematical calculations and the construction of accurate models of market processes no longer seem like something fantastic.

Various funds use the latest economic and financial theories, as well as the latest mathematical tools for more accurate forecasts of price behavior in financial markets, which lead to more efficient trading. Market makers, brokers and hedge funds explore the microstructure of markets and the latest technology in developing automated hft strategies to ensure low transaction costs, taking on a significant market share from traditional dealers. Funds involved in statistical arbitrage also use quantitative algorithms, including high-frequency ones.

Markets are currently very democratic. Due to the proliferation of low-cost technologies, anyone can trade in real markets, place applications and, thereby, participate in the formation of asset prices, which used to be a purely privilege for dealers. At the same time, automation of the trading process virtually eliminates the possibility of errors in the execution of trading operations. Strong competition between new participants and old players has also led to a decrease in margin requirements for brokers.

This is how the trading process took place in the 70s:

  1. Brokers call their customers by offering them their trading ideas about buying / selling certain securities;
  2. If the client was able to persuade, he gives an oral trading order directly by phone. Brokers were sitting in trading floors, and the noise from the site often interfered with the exact execution of the client’s order;
  3. After receiving the order, the broker either executes the order, if it is large enough, or waits for a suitable pack of orders of sufficient volume to execute, which will be executed all at the same price. Thus, the smaller the client, the worse the execution price he receives;
  4. So, after a sufficient volume of applications has accumulated, the broker makes a deal;
  5. Further, representatives of the exchange, called "specialists", processed orders. It is no secret to anyone that it was customary to manipulate prices in orders and the lion's share of the remuneration such people received precisely through the execution of transactions;
  6. The broker notifies the client about the execution of his order, collects commissions and bonuses.

Nowadays, customers are sometimes better informed about market analysis and equipped with more modern equipment than brokers themselves. The area of ​​competence of brokers has also significantly narrowed. Here is a modern broker-client interaction algorithm:

  1. The client conducts research, develops trading strategies and algorithms;
  2. The client through an electronic network places an order that almost instantly hits the broker's server;
  3. The client selects the optimal mechanism for the execution of his order (pending, market order);
  4. Information about the order in automatic mode is executed on the corresponding trading platform;
  5. The trading platform automatically confirms the execution of the client’s order;
  6. The broker automatically sends a confirmation to the client about the transaction and receives a small commission for his services. In 1997, the Merrill Lynch transaction fee was $ 70. Today, Interactive Brokers takes around $ 0.35.

Steve Swanson was a typical 21-year-old computer geek. It was in the summer of 1989, and he had just earned a math degree at Charleston College. In clothes, he was attracted to t-shirts and slippers, and on television - the series Star Trek. He spent most of his time in the garage of Jim Hawkes, a statistics professor at the college where Steve studied. There he programmed algorithms in order to become the first company in the world conducting high-frequency trading in the future, and will be called Automated Trading Desk. Hawks was haunted by the obsession that stocks could be profitable using price prediction formulas developed by his friend David Whitcomb, who taught economics at Rutgers University. Swenson's task was to turn Whitcomb's formulas into machine code.

A satellite dish mounted on the roof of the Hawks garage caught signals carrying information about quotation updates, receiving which the system could predict the behavior of prices in the markets within the next 30-60 seconds and automatically bought or sold shares. The system was named BORG, short for Brokered Order Routing Gateway, Brokerage Team Routing Gateway. The name bore a reference to the Star Trek series, and more precisely to the evil alien race, capable of absorbing entire species, turning them into parts of a single cybernetic mind.

One of the first victims of BORG was market makers from exchange rooms who manually filled out cards with information about buying and selling shares. ATD not only knew better who was giving a more attractive price. The new system carried out the process of buying and selling shares in a second. By today's standards, this is a turtle speed, but then no one could surpass it. As soon as the stock price changed, ATD computers began to trade on terms that the rest of the market had not yet had time to adjust, and a few seconds later they sold or bought shares at ATD at the "right" price.

On average, fewer pennies per share came from ADT, but the company worked with hundreds of millions of shares per day. As a result, the firm managed to move from Hawks' garage to a modern $ 36 million business center in the marshy suburb of Charleston, South Carolina, about 650 miles from Wall Street.

By 2006, the company was trading approximately 700-800 million shares per day, representing over 9 percent of the total US stock market. And she had competitors. A dozen other large electronic trading companies entered the scene: Getco, Knight Capital Group, Citadel grew out of the trading floors of the commodity and futures exchanges in Chicago and the New York stock exchanges. High-frequency trading began to gain momentum.

Major World Exchanges

The largest stock exchanges in the world are in a state of fierce competition and depend too much on the interests of investors who expect constant growth in profits. As a result, exchanges are forced to look for innovative marketing solutions and ways to stand out among competitors. Let's see what allows the world's leading exchanges to grow.

Australian Securities Exchange (Australian Securities Exchange - Asx)

The main objective of the Australian Stock Exchange (ASX) is to maintain a dominant position in the Australian securities market. In addition, ASX is committed to listing companies in Southeast Asia. Low costs and consistently high sales figures make the Australian Securities Exchange competitive in the global financial system.

In 2005, ASX provided brokers with the opportunity to trade anonymously. The initiative has helped to significantly increase the liquidity of securities - in particular, shares included in the S&P and ASE index, which account for more than three quarters of the total market value.

Among ASX's other initiatives is the opening of a secondary market, similar to the London Stock Exchange's Alternative Investment Market (AIM), for companies with a market capitalization below Australian $ 100 million (such as two-thirds on the Australian Stock Exchange).

German Stock Exchange (Deutsche Börse)

The German Stock Exchange seeks to differentiate itself by creating a unique portfolio of services that encompasses the entire chain of exchange processes, such as trading in securities and derivatives, settling and closing deals, providing up-to-date market information, developing and operating electronic trading systems. Thanks to its process-oriented business model, Deutsche Börse creates an efficient capital market: issuers benefit from low capital costs and investors benefit from high liquidity and low transaction costs.

Euronext European Stock Exchange

The Euronext European Stock Exchange (now part of the world's largest NYSE Euronext Exchange) was formed as a result of the large-scale merger of the stock exchanges of Amsterdam, Brussels and Paris, and subsequently expanded so much that it was able to include the Lisbon stock exchange, LIFFE and the London financial derivatives exchange.

Euronext was created with the aim of dividing the spheres of influence in Europe and joint control of the three original securities markets. Contrary to the agreements, Paris has taken the lead in most areas of Euronext's business. Now the exchange uses the original French electronic trading system. In addition, most major French privatizations are taking place on Euronext.

Euronext is pursuing a strategy of diversification and expansion, adding new products and services, and striving to strengthen its influence internationally. Euronext analysts have developed a “Technology Improvement Program” similar to the one on the London Stock Exchange. The new electronic platform will help Euronext significantly increase the speed and number of simultaneously executed transactions.

Hong Kong Stock Exchange (The Hong Kong Stock Exchange, HKEX)

The Hong Kong Stock Exchange (HKEX) is inextricably linked to China's booming economy. The main advantages of HKEX are its geographical proximity to mainland China, relatively soft corporate governance and the favor of the Chinese government, which is conducting the privatization of state enterprises here.

Chinese companies trust the Hong Kong Stock Exchange and prefer it to Western and American competitors. Listing securities on the Hong Kong Stock Exchange is more convenient, cheaper and easier culturally.Listing standards at HKEX are high, but the requirements for companies are far from as stringent as in the US, as the exchange management has repeatedly stated.

Currently, only securities of companies registered in Hong Kong, China, Bermuda or Cayman Islands can be included in the stock exchange list. However, the marketing strategy of the Hong Kong Stock Exchange involves changing the rules to include shares in companies from other countries in the Asia-Pacific region (for example, from Australia) and reduce dependence on China.

London Stock Exchange (LSE)

The London Stock Exchange spends a considerable amount of money on the Technology Road Map, a large-scale program to modernize trading mechanisms. One of the last successful steps in this direction was the introduction of a new system of storage and transmission of market data Infolect, which allowed to reduce the average transaction speed to two milliseconds (which is about 15 times less than previously required).

Like Euronext and NASDAQ, the London Stock Exchange seeks to expand its influence in the world. LSE focuses on China, India and Russia. The strategy of attracting foreign companies to the listing procedure really works - in 2006 several large Russian private enterprises placed their shares on the London Stock Exchange. Management also decided to open an additional office in Hong Kong in October 2004 to compete with US exchanges in the fight for Chinese business.

US Stock Exchange NASDAQ

NASDAQ is the largest electronic stock exchange in the United States, judging by the number of closed transactions with securities and the presence of companies that are leaders in their industry - for example, Microsoft, Intel, Google, Oracle, Nokia, K-Swiss, Carlsberg, are sold on this exchange. Starbucks and Staples. Despite the fact that initially NASDAQ positioned itself as a "exchange for growing companies", today you can encounter some of the highest requirements for applicants to be listed.

The world's first electronic stock market, NASDAQ has sought to become a leader in trading technology. The speed of conclusion of transactions was reduced to a record low of one millisecond.

New York Stock Exchange (NYSE Euronext)

NYSE Euronext positions itself as a world leader among stock exchanges. The most liquid stocks, the highest listing standards and blue chips (securities of the largest companies with stable income) allow the New York Stock Exchange to maintain its unofficial gold status.

Like all major world stock exchanges, NYSE Euronext seeks to expand its influence outside the United States and overcome the competition of local exchanges that have grown over the past few years in large cities (for example, in Milan or Mumbai).

In order to gain access to shares in companies outside the United States, in June 2005, the New York Stock Exchange proposed the merger of Euronext, one of the largest securities exchanges in Europe. The merger, which was approved by Euronext shareholders, entered into force in the first quarter of 2007 and allowed for the first time to create an “intercontinental” securities market, and the total value of companies from the exchange list was about 26 trillion. dollars.

Singapore Stock Exchange (SGX)

The Singapore Stock Exchange has gained a niche in the Asian stock market. Here are the largest companies from the countries of the Asia-Pacific region (except for Japanese, Korean and state Chinese enterprises that prefer to put their shares up for sale on domestic exchanges). SGX is an extremely attractive trading platform for countries that do not have globally recognized exchanges. In addition, the Singapore Stock Exchange has succeeded in attracting private Chinese capital.

In order to maintain its competitive advantage, the Singapore Stock Exchange seeks cooperation with smaller regional exchanges and, thereby, expands its global network of trading floors. In mid-January 2007, SGX became the only Asian exchange to officially announce its desire to acquire a 26% stake in the Bombay Stock Exchange. The other three bomb-stock exchanges, NASDAQ, the London Stock Exchange, and Deutsche Börse are based in North America and Europe.

Japan Exchange Group, Inc

The Japanese Stock Exchange strives for regional leadership and competition in the global market and positions itself as a "prestigious place to place securities." Significant advantages of Japan Exchange are the sale of securities with high liquidity and the introduction of cutting-edge information technologies in the trading process.

The exchange is a member of the Federation of Stock Exchanges of Asia and Oceania. Japan Exchange Group, Inc appeared as a result of the merger of the Tokyo Stock Exchange and the Osaka Stock Exchange in 2012. Prior to this, the Tokyo Stock Exchange was the main player in the Japanese stock market (it absorbed Osaka).

Moscow Exchange

The Moscow Exchange was formed in December 2011 as a result of the merger of two major Russian exchange groups - MICEX and RTS. The exchange structure resulting from the merger was able to trade all major categories of assets.

Currently, the Moscow Stock Exchange is the largest exchange in Russia and Eastern Europe. In addition, the share of post-trading services is increasing on the Moscow Exchange, which, in the opinion of management, may attract new issuers and investors. Armed with the experience of American competitors, MB began to provide risk management services and supply business information to investors. Modernization of trading mechanisms is underway, the speed of transactions in the derivatives market is increasing.

What is high frequency trading

The term "hft" includes a wide range of operations from algorithmic trading. High-frequency trading is a fairly closed area. It is very difficult to find information on how hft firms work. However, some information can still be obtained from the list of open vacancies, advertisements and individual Internet articles. hft is also very different from other forms of algorithmic trading. It is built solely on technical solutions and a huge number of calculations. After the start of trading according to a certain algorithm, there are almost no adjustments to its work (as long as it remains profitable), which is very different from low-frequency system trading, in the process of which people often make their adjustments.

Working in such an environment is highly competitive and can often break people. Many months of research overnight become irrelevant if the exchange working scheme changes, a new legislative framework appears, or if competitors can start processing data at higher speeds. Therefore, such work is suitable for well-disciplined people with several higher technical education, able to work under pressure, who value independence and a highly professional team.

Despite the fact that the activities of hft-traders are often criticized, only certain types of hft-trading create chaos in the modern financial market. The line between algorithmic trading, electronic market-making and harmful hft-trading is rather blurred and high-frequency trading often means electronic trading. In fact, the phenomenon of hft trading in itself is neither good nor bad, but the devil is in the details.

In order to clearly represent the possibilities of HFT trading, it is worth considering in more detail some types of market activity.

Algorithmic / system trading is the common name for the process of applying programmable systems that use a specific mathematical model to automatically complete transactions. A person creates a program on a computer for a specific financial strategy based on this criterion and manages the developed system from this computer. hft-trading is a type of algorithmic trading, but not all algorithmic trading can be considered high-frequency.

In 2011, the Commodity Futures Trading Commission (CFTC) admitted that it was not trying to find the exact definition of high-frequency trading. Instead, she proposed seven key attributes of HFT trading:

  • Using systems that implement extremely fast placement, cancellation and change of an order in less than 5 milliseconds or with a practically minimal delay;
  • The use of computer programs or algorithms to automate the decision-making process, during which the placing, execution, direction and execution of orders are determined by the system and do not require human intervention in the case of each individual order or transaction;
  • Use of colocation services, direct access to the market or a dedicated data channel offered by exchanges and other organizations in order to reduce network and other delays;
  • Very short time frames for opening and closing a position;
  • High daily turnover of the securities portfolio and / or a high proportion of applications submitted in relation to the number of transactions;
  • Placing a large number of orders that are canceled immediately or within a few milliseconds;
  • The end of the trading day in a position as close to zero as possible (without holding large unhedged positions at night).

History of hft strategies

Now many complain that high-frequency traders who use mathematical algorithms have an unfair advantage over those whose algorithms are not so good, or that their (hft-traders) trading systems are faster than other players.

This discontent is emphasized by one more significant historical fact: any technology that increases the speed of information flow was immediately adopted by the community of traders both in Europe and in the United States. Traders used all the well-known vehicles to carry out transactions faster and put less effort into it. They were among the first to master speed boats, faster crews and private courier services.

In the late 1830s, a broker from Philadelphia, William Bridges, had a personal signal station between New York and Philadelphia, broadcasting stock market news to him and his patrons (and no one else). The signals were transmitted using an “optical telegraph”, which consisted of a series of shields on a support mounted on a hill that could be seen through a telescope. Messages indicate that they could transmit stock market information to anywhere from New York to Philadelphia in 10-30 minutes. In the 1830s, this was high-speed trading.

It is not surprising that complaints began to come from speculators from New York who were not involved in this system and, until that time, had enjoyed a significant advantage. When the system was shut down after the telegraph appeared in 1846, a local newspaper report wrote that "speculators who contributed to the creation of the telegraph were responsible for many ingenious moves in the Philadelphia stock and commodity markets. Undoubtedly, speculators paid well to its creators."

Unfortunately, the organized community of traders did not strive much for openness. At the initial stage of its existence, the NYSE (New York Stock Exchange, then known as the New York Stock and Exchange Board) did not allow the public to listen to trading sessions (the sessions were inaccessible to the public until 1869).Competing traders (over-the-counter traders working literally from the outside) who intended to sell trading information on the NYSE were furious that they could not be near the exchange. In 1837, the NYSE found that over-the-counter traders drilled a hole in the brick wall of the exchange building in order to eavesdrop on the course of trading.

While the public was pondering how to get ahead of fast horses, a new technology appeared on the arena that turned trading into a field of truly high speeds: the telegraph, which came into use after 1844. He was the greatest invention of his time. It took time to produce newspapers, and for the most part they were published at regular intervals. But the telegraph worked constantly, and it could be used for personal communication.

As expected, the use of the telegraph to transmit "secret knowledge" caused outrage. Several inventors of the first telegraphs were forced to stop their experiments, warning that they could be prosecuted for distributing information faster than mail. Leading inventor of the telegraph Samuel Morse supported the introduction of the telegraph into mass production for personal and public purposes, in particular, to protect it from use for speculation.

Forty years later, the telegraph was still the main instrument of stock speculators. In 1887, the president of Western Union said that 87% of the company's revenues came from speculators in the stock and commodity markets and those who made races.

The stock ticker, which appeared in 1867, became the next greatest electronic device, immediately mastered by the community of traders. Until its appearance, exchange transactions, as a rule, were carried out with the help of “runners” - boys who ran from the exchange pit to brokerage houses. He had a huge superiority over the telegraph for several reasons: traders no longer needed to be physically in the stock pit, his appearance reduced transaction costs, he helped to disseminate information continuously, in real time, and his invention reduced the number of annoying intermediaries like telegraph companies and newspaper editors. It is not surprising that journalists and editors were worried that the introduction of a ticker would force them out of the lucrative trade in financial news.

The first stock pit was patented by Ruben S. Jennings in 1878. He designed the pit so that traders can see and hear other traders in the best way. Therefore, there were several steps in the pit. The trader at the highest step had the best overview, there was an advantage in the ability to easily see and hear colleagues - all this made it possible to carry out transactions faster.

To get an advantage in speed, it was necessary to be physically above other traders, therefore, growth began to play an important role in reducing delays. Therefore, former basketball players often became traders before: they were easier to notice. Already at the end of the twentieth century, some traders in pits wore high heels to be taller and carry out transactions faster.

This led, for example, to falls due to a lack of balance when walking in high heels. As a result, the Chicago Exchange was even forced in November 2000 to decide on setting the maximum height of the heel and / or platform to two inches (a little more than 5 centimeters), and, for example, the London Metal Exchange still has the rule that deals can only be concluded while sitting.

The introduction of such standards was one way to balance the odds on the trading floor in terms of speed of work in the exchange room, but in the end there was always someone who was ahead of the competition.Those traders who were most successful in terms of reducing delays in trading made money on the inefficiencies of the then existing system, in which, for example, growth could give a big advantage.

As a result of their work, these inefficiencies were gradually eliminated - somewhere by the introduction of regulatory rules, somewhere by the very course of history - for example, the computerization of exchanges in itself made the desire to be physically superior to all simply irrelevant.

This went on, with the invention of the telephone (first tested by Bell in 1876, by 1878 there was already a telephone in the NYSE pit), with the creation of airmail, a computer in the 1950s, punch cards in the 1960s, with the first appearance of electronic trading, when in 1971, the Nasdaq exchange started its work, and algorithmic trading in the 1990s. The same disputes arose: someone received information earlier than the others, and some could bid, because they had a faster ship, horse, carriage, telegraph line, computer communication, algorithm.

In 1967, Edward Thorpe, a professor of mathematics, published The Beat the World. The author described the method by which it was possible to make money in the stock markets. The system invented by him was so good that some trading houses had to change the rules of trade.

Later in Britain, the development of mathematicians brought new methods of analysis and the belief that in the future computer systems could make a real revolution in predicting market fluctuations. Then a completely new branch in science arose - quantitative analysis.

In 1989, with the advent of newer technologies and computer systems, the idea of ​​high-frequency trading was born as a method of using high-performance systems to earn money on trading exchanges. The author of this idea is Steve Swanson.

He worked on the analysis of the movement of quotations on exchanges 30 seconds before the transaction. Then he and his partners David Whitcomb and Jim Hawks founded the first and only at that time automated trading company - AutomatedTradingDesk. While all participants in the financial market worked via telephone, the order processing speed through AutomatedTradingDesk was one second. So the hft story began. As a result, now 70% of transactions on Wall Street these days are carried out by high-frequency algorithms.

Today, trading is usually carried out using electronic servers in data centers, where computers exchange offers to buy and sell by sending messages over the network. This transition from trading in the exchange’s operational building to electronic platforms was especially beneficial for hft companies that invested a lot of money in the infrastructure necessary for trading.

Despite the fact that the place and participants in the trade outwardly changed greatly, the goal of traders, both electronic and ordinary, has remained unchanged - to acquire an asset from one company or trader and sell it to another company or trader at a higher price. The main difference between a traditional trader and an hft-trader is that the latter can trade faster and more often, and the holding time for a portfolio of such a trader is very low. One operation of the standard hft-algorithm takes a millisecond, which traditional traders cannot compare with, since just blinking a person takes about 300 milliseconds.

Hft as an evolution of classic trade

Brokers who spoke out loudly against hft were inclined to rely on technical analysis when deciding when to enter or exit a position. Technical analysis was one of the earliest methods that have become popular with many traders and in many ways is a direct precursor to modern econometrics and other hft methods.

Technical analysts who came into fashion in the early 1910s sought to identify recurring price patterns.Many methods used in technical analysis measure current price levels relative to a moving average price or a combination of moving averages and standard price deviation (Bollinger Bands).

For example, a technical analysis indicator such as MACD uses three exponential moving averages to generate trading signals. Advanced technical analysts look at prices in conjunction with current market events or market conditions to get a better idea of ​​where prices can move on.

Technical analysis flourished in the first half of the 20th century, when trading technology was in its infancy, and the complexity of trading strategies was much lower than today. The speed of dissemination of information and quotes including was surprisingly low. Bidding the previous day appeared in the newspaper the next morning. In the post-war years, technical analysis turned into a self-fulfilling prophecy.

If, for example, enough people believed that a head and shoulders figure appeared on a particular instrument, a huge number of traders began to place sales orders, realizing the prediction in this way. Currently, classical technical analysis works well only on timeframes from D1 and higher. And yet, many methods and indicators of technical analysis are used by quanta to build high-frequency trading strategies.

It has been scientifically proven that investors tend to trust more strategies that have worked in the past. This follows from common sense - what worked before is likely to continue to work further. As a result, vehicles operating in the past month are also likely to work in the next month, forming a kind of trading trend that can be detected using simple technical indicators based on the moving average, as well as more complex quantitative tools. Quite often, quanta use the Bollinger band indicator in their strategies to track the current market condition.

Another type of analysis, Fundamental Analysis, emerged on the stock market in the 1930s. Traders have noticed that future cash flows, such as dividends, affect market price levels. Graham and Dodd (1934) were the earliest traders using this approach, which remains popular to this day. Fundamental analysis developed over much of the 20th century. In equity markets, fair prices are still often determined based on projections of future company returns.

In the forex market, the most common macroeconomic models are used to calculate fair prices based on inflation information, trade balances of various countries and other economic indicators. Derivatives are traded primarily through advanced econometric models, which include the statistical properties of price movements of underlying instruments. Various aspects of the application of fundamental analysis are also used in the construction of hft systems. The news release date and time is usually known in advance, and the information necessary for making a decision is disclosed during the news announcement.

It is perfectly clear that in a similar situation, systems that react most quickly to changes receive maximum profit. In fact, speed has become the most obvious aspect of competition. To speed up the process of execution of transactions, traders began to use more and more powerful computers and apply more and more advanced technologies.

Modern period

By 2012, there was a trend towards a decrease in the effectiveness of hft and its market share. Since 2009, in just three years, the profits from high-frequency trading have decreased 5-fold from $ 5 billion to 1.25 billion. In 2014, the book “Flash Boys: The High-Frequency Revolution on Wall Street” was published, which describes in detail the history and mechanisms of hft as a financial fraud and market development.The product has become a bestseller, its author is Michael Lewis. In 2016, due to low volatility, most of the smaller hft companies began to leave the market. Their profit has become incomparable with what it was in 2009-2010.

Successful implementation of the hft system requires signal-generating algorithms, algorithms that optimize the execution of orders, risk management algorithms, portfolio optimization, and so on. The figure below illustrates a survey of traders conducted by Automated Trader in 2012. Here is how traders answered about the purpose for which they use automated trading systems:

hft systems cover almost the entire range of decisions that are made by the trader - from the selection of trading instruments to the best execution of orders.

And yet, even today, not all markets are suitable for high-frequency trading. According to Aite Group's researchb, the stock markets have the largest percentage of algorithmic participants who make up more than 50% of trading volumes. In second place are futures (over 40%). The share of algorithmic traders in the Forex market, in option markets and fixed-income securities markets is noticeably lower.

Algorithmic trading has been shown to outperform human trading in several key metrics. Aldridge (2009), for example, shows that algorithmic funds consistently outperform traditional ones. Aldridge (2009) also shows that algorithmic tools are ahead of the classical ones in income during periods of crisis.

An interesting study was conducted by the Central Bank for the Russian stock market and the USDRUB currency pair. According to him, 50 hft algorithms work on this currency pair, providing more than half the volume of orders.

This may be due to the lack of emotions inherent in algorithmic trading systems compared to people controlled by emotions. In addition, computers are superior to people in such basic tasks as collecting information and quickly analyzing a wealth of data and news. Physiologically, the human eye cannot capture more than 50 data points per second. In modern films, the human eye is exposed to only 24 frames per second. And even then, most of the static images displayed on successive frames seem to us to be continuously moving objects.

For comparison, the current price stream includes sharply changing quotes, the number of which can easily exceed 1000 per second for one financial instrument. All this information needs to be managed in a timely manner, processed, made various calculations and made trading decisions based on them.

In the spring of 2017, Credit Suisse analysts published a report on "the real role of hft trading in the modern ecosystem of the financial market." The document talks about how high-frequency trading has changed the situation on world exchanges. Here are four main findings from the study.

Trading volumes increased

The development of high-frequency trading technologies has had the largest, most noticeable and time-consuming effect on trading volumes. According to Credit Suisse, the volume of trading that falls on the operations of trustees and investors, both active and passive, in the US stock market has not changed much over the past ten years (3-4 billion shares per day).

At the same time, the total trading volume on US exchanges in the period after the crisis of 2008 more than doubled, and it was precisely in these years that hft-trading was particularly active.

This fact has negative consequences. For example, the topic of "fake" activity of trading robots is widely discussed, which can submit a lot of applications, and then immediately cancel them, in the hope of influencing the price. However, in general, Credit Suisse analysts believe that "most of the hft-activity helps to connect the people acting in the financial market, reducing the time for counterparty expectations."

The difference in prices for the purchase and sale of shares has changed

In theory, the smaller the spread, the better for the market. The development of hft has had an impact here. The size of the spreads of shares of large companies decreased, while smaller ones, on the contrary, increased. This suggests that more often high-frequency traders are interested in more liquid stocks of well-known companies.

According to a Credit Suisse report, stock spreads change in accordance with volatility, and the spread of spreads between the most and least liquid stocks has seriously increased since 2009. That is, now the spreads of shares of large and small companies are no longer moving in one direction.

Stocks of large and small companies are volatile at different times of the day

Increased volatility of stocks of large and small companies in recent years is observed in different periods of the trading day. For example, at the beginning of trading, the price of shares of not the largest companies is actively changing. This is due to the fact that it takes more time to determine the fair (at the moment) price of such shares. However, by the end of the trading session, on the contrary, such stocks behave more calmly than securities of large organizations.

On the contrary, for shares of large companies that are actively traded on the market, price fluctuations are sometimes observed when they change many times quickly inside the spread at the end of the trading day. Analysts also attribute both of these phenomena to hft.

The number of noticeable surge in stock prices of large companies decreased

As a rule, hft trading strategies are aimed at making profit from market inefficiencies, and not at participating in large price movements. This results, among other things, in the reduction of large fluctuations in prices of well-known companies with which high-frequency traders more often perform operations.

Execution speed

Often an extra millisecond can lead to the fact that instead of profit, the trader receives a loss, because someone else was ahead of his trading robot. The pursuit of speed and the financial results at stake have led to the active development of various technologies to reduce delays in trade. Here are some of the approaches used to increase performance.

Direct access to the exchange

To trade on the exchange, an investor needs to conclude an agreement with a broker that provides access to trading. Typically, such companies also develop their own trading systems, which process customer applications before sending them to the core of the exchange system. However, in a situation where everyone can decide a few milliseconds, the scheme "user - brokerage system - exchange" is not suitable for everyone.

To remove the superfluous link in the form of a brokerage system, the technology of direct access to the exchange (DMA, direct market access) was created. Its essence lies in the fact that the application is placed directly in the trading system of the exchange, bypassing the infrastructure of the broker.

Direct access is a technology of high-speed access to exchange platforms, in which the application is placed directly in the exchange trading system, bypassing the broker's trading system. All this allows to significantly reduce the time of delivery of the application to the exchange and obtaining information about its condition.

With this organization of the trading process, the trader can count on a significant gain in time. For example, with a direct connection to the stock and currency markets of the Moscow Exchange, the processing time of an application is reduced to 0.5 ms, and in the FORTS and Standard markets it does not exceed 3 ms. When using the brokerage system, applications are processed within a period of 5-10 ms to 150-500 ms, depending on the brokerage system, the type of market, and the connection method. Through brokerage systems, orders are processed 10-100 times slower than with a direct connection (although this trader is quite suitable for many traders).

It is still a matter of very small time intervals from the point of view of a person, but for some trading strategies, such a difference can be critical and affect their overall performance.Naturally, the use of direct access technology is more expensive, often significantly, and is suitable only for those who perform a large number of operations per day and are willing to pay for their speed.

Despite the fact that technically, thanks to direct access to the exchange, traders can perform trading operations bypassing the broker, documented access is still carried out precisely through broker companies. That is, in order to be able to directly trade on, say, the stock market of the Moscow Exchange, an investor needs to conclude an agreement with a broker and purchase the direct access to the exchange service from him already.

Placement of equipment near the exchange

If you continue to move along the chain of reducing the time to complete operations, it becomes obvious that you need to place the trading robot not only logically, but physically as close as possible to the servers with the core of the exchange trading system.

Direct access to the exchange allows you to logically bring the trading system closer to the core of the exchange, but it is obvious that you can get even greater gain in speed by placing it physically closer to this endpoint. As a rule, exchanges provide the service of equipment colocation in their data centers. In this case, the trading system can be launched on a server that is actually in the same rack with the exchange core servers.

The robot can be placed both on a separate server, which can be racked in a data center (this service is called Colocation), and on a virtual machine (Hosting), which, in turn, runs along with the virtual machines of other clients on a server also installed in the data center , near the exchange servers. Hosting services are provided, as a rule, only by large brokers who have their own racks in data centers.

Placing in the exchange colocation zone allows you to connect trading robots directly to the exchange core. Also in this zone, it is possible to obtain Market Data using the FAST protocol, which we will talk about a little later. The advantage of using the free colocation zone is the fact that this option is much cheaper. But if we talk about the pursuit of speed, high-frequency traders choose the fastest option, despite the fact that it can sometimes be the most expensive.

Placing in the exchange colocation zone has obvious advantages: virtual machines and servers are connected directly to the exchange core, while from the free zone the connection is through intermediate servers. In addition, receiving data via the FAST protocol and a dedicated channel for connecting to the market are available only from the exchange collocation zone.

One way to significantly reduce infrastructure costs is to place the robot in a free colocation zone. The services provided in it are almost similar to the services of the exchange colocation zone. However, free cheese happens only in a mousetrap - you will have to pay several milliseconds to increase the speed of transaction processing for the relative cheapness of the robot.

In addition, since the interfaces for creating direct connection software initially did not imply any graphical options for displaying trading information, the ability to synchronize orders and positions formed on a direct connection with a broker trading system in real time is practically a necessary thing to control trading operations. Therefore, many brokers try to provide their clients with such opportunities.

All this, in comparison with the usual access to the exchange through brokerage systems, costs money, and quite large. However, for those investors who have reached a certain level of income, such expenses make sense. According to representatives of the exchange, the owners of robots that won the contest "Best Private Investor" in 2011 spent on services related to direct access from 100 to 500 thousand rubles a month.However, taking into account the fact that some traders (although there were not so many of them) managed to reach a profitability of over 8000% and earn millions of rubles a month, and, taking into account all the commissions of the broker and the exchange, these expenses quickly paid off.

Hardware Acceleration (FPGA)

In the past few years, the use of FPGAs to reduce the delays in the operation of trading applications has spread among algorithmic traders. Using modern FPGAs, you can implement various aspects of high-speed trading systems. For example, the processing of market data can be entirely carried out on the FPGA without transferring them to the processor of the machine.

The use of programmable hardware allows you to get a serious gain in processing speed and reduce latency, but there are some difficulties. First of all, these include the complexity of developing and supporting trading applications using FPGAs. To interact with hardware, traders need to learn not only high-level programming languages, but also the so-called hardware description languages ​​(HDL). Also, do not forget about the need for additional expenses for the equipment itself.

New data transfer technologies

The most important component of success in high-frequency trading is data transfer speed. Market players are actively looking for various ways to optimize it, which leads to the development of technologies such as data transmission using microwave radiation. Despite certain disadvantages (instability to rain and fog, limited bandwidth), it makes it possible to send data directly. In other words, you don’t need to lay fiber-optic cable through the mountains, you can simply install antennas on the towers and find the shortest distance between point A and B. Thus, applications can be transmitted by air faster than fiber-optic.

Such technologies are quite expensive, but the possible financial return on their use is so great that many hft companies invest millions in building their own microwave networks.

However, the use of microwaves for data transmission is not the only innovation. As the Wall Street Journal wrote back in 2014, the next technological breakthrough in this area could be the creation of data networks using lasers. According to reporters, hft-companies have already agreed to create a similar network to work with the Nasdaq exchange.

Varieties of protocols and connection methods

In general, the direct access scheme is as follows: a server with a trading robot is connected to an intermediate server, which is located as close as possible to the core of the exchange trading system. Special software is installed on this server - the so-called gateways, which are used to transfer orders and market information directly to the trading system. At the same time, various protocols and connection methods are used to perform operations and obtain data.

Currently, exchanges offer developers the following protocols for direct access to exchange markets:

ProtocolMarketsAvailable features
ASTS BridgeStock, CurrencyTrade + obtaining all market data. 100% support for all operations.
Plaza IIUrgentTrade + obtaining all market data. 100% support for all operations.
FixStock, Currency, Urgent, OTCTrading operations in the main trading modes (without support of negotiation transactions), Trade Capture (only stock and currency), Drop Copy.
FastStock, Currency, UrgentObtaining anonymous market data.
Information and Statistics Server (ISS)AllObtaining anonymous market data through the web services of the exchange.

ASTS Bridge

The exchange gateway is Bridge. Gateway, which I also really want to translate as a gateway, is another story, it is more of an access server. The gateway is the native protocol of the ASTS trading and clearing system, which has existed since 1998 (previously the solution was called TEAP (TCP / IP version) or TEServer (RS-232 version, no longer supported)). Many developers know the protocol under the name MTESRL, by the name of the corresponding DLL. Due to the nativeness of this protocol, its main feature is the support of all transactions and all market data from all markets operating on the ASTS trading and clearing system.

The use of this protocol is recommended primarily for those who need access to clearing data and operations (viewing their positions, obligations, risk parameters, setting various limits, transferring securities and money between accounts, and so on), as well as participating in tenders in modes of negotiated transactions (that is, not quick anonymous trading in a glass, but direct conclusion of transactions with a specific counterparty). The API is provided as a dynamic library - in 32- and 64-bit versions for Windows and Linux.

The connection architecture is as follows: the dynamic library falls into the package of software developed by you, this package is installed on a server that has network access to the so-called server part of the gateway. The server part is a kind of proxy server located at the broker and connected to the exchange infrastructure via dedicated network channels.

In the case of hft-trading, when your software is installed in the data center of the exchange under colocation conditions, an intermediate link in the form of the server part of the gateway is no longer required - you are connected directly to the exchange Gateways.

An interesting feature of the gateway protocol is the support of "interfaces". An interface is a versioned collection of tables and transactions available to the user, with the appropriate structure and data types. Almost every time the trading and clearing system is updated, new opportunities appear for users who require modification of the table structure or change of the transaction format. The presence of versioned interfaces allows users who are not ready for changes to stay on the old version of the interface and not modify their software.

Protocol Plaza II

For direct connection, native protocols are used. These protocols arose even before the unification of the MICEX and RTS exchanges into the Moscow Exchange. So, in the markets related to the RTS exchange (FORTS - futures and options, Standard), the Plaza II protocol is used to directly perform operations and receive data in the connection mode.

To connect using this protocol, the exchange provides the CGate API. On the one hand, this allows bidders to implement full-fledged functionality for accessing trades, including clearing functionality for limiting sections, setting restrictions on instruments and viewing market maker obligations. On the other hand, this allows clients of bidders to implement their own high-speed robots with a minimum set of functions (submit an application or withdraw an application). The API is provided as a set of dynamic libraries - in 32- and 64-bit versions for Windows and Linux.

With almost every release of the derivatives market, the exchange makes changes and improvements to its own program code, which is transmitted to customers as an API. To the user, this looks like a new distribution with new versions of libraries inside. In addition to the code itself, the structure of the data given to users changes periodically with the release.

FIX Protocol

Protocol FIX (Financial Information eXchange) - a protocol for the exchange of financial information, which is the world standard for the exchange of data between participants in exchange trading in real time. It is supported by the largest global stock exchanges, including the Moscow Exchange and all Forex brokers.

The creation of the FIX protocol was initiated by a number of US financial institutions in 1992 - brokers and investment funds wanted to speed up the process of trading on the exchange. At that time, a significant part of trading operations was carried out using a telephone, and the FIX protocol allowed translating interactions into electronic form.

As a result, an open standard for the transmission of information in electronic form was born, which is not controlled by any of the large organizations. Today, FIX has become an industry standard that is used by financial market participants from different countries to communicate their products.

Currently, the protocol is defined at two levels - sessions (work on data delivery) and applications (description of data content). There are two versions of the protocol syntax - traditional, of the form Tag = Value and in XML format (FIXML).

Work on creating syntax in XML format began in 1998, and the first version of FIXML appeared in January 1999. At the beginning of the path of the XML version of FIX, only the DTD syntax determination mechanism was used. Further, the W3C organization developed a new mechanism - XML ​​Schema, which forced FIX developers to adapt the standard to use this syntax variant.

This step made it possible to improve the XML version of the FIX protocol, in particular, users were able to add attributes and contextual abbreviations to messages. The basic organization of an XML schema assumes the existence of data types used in fields that are contained in a separate file. FIX fields are defined in a special shared file, and components and FIXML syntax elements in special component files. FIXML messages are defined using special files that indicate a category.

FAST Protocol

In November 2004, then-CEO of Acrhipelago Holding financial holding Mike Kormak, at a FIX community conference called FPL (FIX Protocol Limited) in New York, announced that the current version of the protocol could not cope with the increased amount of financial information generated in the stock market. When transferring large amounts of data using FIX, there were significant delays in their processing, which caused losses to traders and deprived them of the opportunity to develop existing trading strategies.

The classic Tag = Value message format used by FIX was too cumbersome to process quickly. Soon after this speech, the first steps were taken to rectify the situation.

When creating the FAST protocol, the developers aimed to achieve the possibility of transferring large amounts of data, avoiding delays in receiving information. The protocol was developed by a FIX community working group called the Market Data optimization working group (mdowg), which was formed in 2004.

In 2005, the experts of the group presented a pilot project (proof of concept) of the protocol, and a year later the first version of FAST 1.0 was released. Subsequently, several updates were released, and at present most protocol players use protocol version 1.2.

According to the FIX protocol standard, each message has the format Tag = Value SOH, where Tag is the number of the transmitted field, Value is its value, and SOH is the delimiter character. The FAST protocol eliminates redundancy using a template that describes the entire message structure. This method is called implicit tagging, because FIX tags are only implied in the transmitted data.

ISS

This protocol is somewhat out of the general row, as it covers a segment of tasks related not to transactions, but to work with exchange data. In essence, this is an exchange web services API implemented according to the Restful concept. It makes it possible to obtain general market information, such as quotes, deals, indices, volumes, trading results and so on, using the http / https protocol. The service is available only through the Internet, so minimizing delays in receiving data is not applicable to it.

This protocol is used to display stock quotes on websites (including all data on moex.com website is transmitted from there), download trading results for analytics, draw graphs on various demo panels and scoreboards and in any other applications running via the Internet.

For those traders who do not use to trade robots, there is the opportunity to trade on a direct connection using the more familiar trading terminal. However, the software that works with the broker trading system does not work on direct-connect exchange protocols, so separate programs are created for it.

In addition, due to the fact that direct connection technologies are open, investors can independently develop software for themselves.However, since these programs ultimately have almost direct access to the core of the trading system, the exchange introduced a procedure for certification of trading solutions from third-party developers in order to eliminate the possibility that the "furious robot" put all the system on the spot. This procedure goes through the development of individual investors, as well as software created by special companies on order.

What do stock exchange data centers look like

NYSE Euronext is a data center located in Mahwah, New Jersey. The area of ​​the halls for the colocation of traders' servers is about 18 thousand square meters - the area of ​​the building itself is more than 120 thousand square meters. The Data Center Knowledge published some photos of this data center.

Object management center - it combines the interfaces of building management systems (BMS) and infrastructure management of the data center itself (DCIM). It is here that specialists sit who monitor the temperature and humidity modes, the status of power supplies and other elements in each server room.

And this is what the “hot corridor” looks like, into which the air emitted by the servers enters:

The long main corridor of the data center allows you to feel the huge scale of the object.

Equinix is ​​one of the world's largest data center and colocation players. One of its facilities is the building of a former eyeglass factory in Secaucus New York State with an area of ​​more than 100,000 square meters, converted into a modern data center. Its services are used by such exchanges as NASDAQ, BATS, CBOE, and that's how it looks.

On both sides of the long main corridor of the data center are lattices; these grilles and racks are connected by a cable that runs through the yellow suspended cable channels.

A 12-meter-high ceiling provides ample space for several levels of cable channel placement, filling the upper part of the Equinix data center, which has separate channels for connecting, carrier and power cables.

Uninterruptible power supply (UPS) hall at the Equinix NY4 data center, powered by a 26 megavolt-ampere substation. The equipment consists of an uninterruptible power system with a capacity of 30 megawatts, which supports the operation of a computing installation in the event of a power failure.

In the event of a power outage, the equipment of the NY4 data center is equipped with these 18 Caterpillar spare diesel generators of 2.5 megawatts each, which together provide 46 megawatts of emergency electricity, sufficient to provide a complete supply of energy for the equipment, as well as refrigeration units and UPS systems. During Hurricane Sandy, these generators kept equipment running for a full week.

The cooling system in NY4 is equipped with huge pipes through which chilled water flows to the equipment, as well as to a plate heat exchanger (on the right), which acts as a refrigerator in the winter and allows you to save energy, which under normal conditions would be spent on the operation of refrigeration units.

Currently, the largest Russian exchange platform, Mosbirzha, offers traders the opportunity to place their equipment in the Moscow data center M1. The data center was commissioned in 2006, its total area is 3850 square meters, of which 2400 square meters are allocated for server rooms (load capacity of 5-8 kW per rack). All of these racks about 950 pieces.

In order to maintain the required temperature (22 ± 4 degrees) and humidity (45 ± 10%) conditions, supply and exhaust ventilation systems and precision industrial air conditioners are installed in the server rooms.

Server racks are located on the principle of hot and cold corridors, closing the latter eliminates the mixing of hot air emitted by the equipment with cold air coming from the air conditioners.

Uninterruptible power supplies are designed for a longer operating time of all equipment than is necessary for starting diesel generator sets and switching to autonomous power supply of the data center.

In 2014, the Moscow Exchange management decided to move to the DataSpace1 data center. The data center was commissioned in July 2012. Its total capacity is 1062 racks - 12 machine rooms, each with an area of ​​up to 255 square meters.

6 independent power supply circuits are organized in the data center; each engine room is supplied with electricity from 2 independent circuits.

Chillers and dry air coolers are installed according to the N + 1 distributed redundancy scheme, cold air is supplied under the floor.

The perimeter of the building and the interior are equipped with an 8-level security system, which includes various components of access control and surveillance.

Exchanges and HFT traders pay great attention to building their own trading infrastructure. Today, in the stock market, success and failure are often separated by fractions of a second, and therefore the software and hardware that provide financial applications should work extremely reliably.

The load level is so great that it is not easy to cope with - it requires serious investment from data center service providers. Otherwise, situations may arise, similar to what happened in August 2015 at the CenturyLink data center - during a serious market move, the infrastructure for HFT-trading worked in an intensive mode, which the ventilation system (HVAC) could not handle. As a result, many servers not only overheated, but physically burned out.

Varieties of hft platforms

Currently, most traders and brokers create their hft-systems using popular software and hardware technologies. This allows us to describe the algorithms with the help of many high-level programming languages ​​that are familiar to many, and you can quickly change them if necessary. However, the pursuit of speed leads to the fact that unpredictable response time of software systems becomes an obstacle to successful trading. Let's look at existing software and hardware approaches to creating hft-systems.

High Frequency Software Platforms

There are a fairly large number of companies offering software for high-frequency trading (for Western exchanges, for example, Mantara, Ulink and QuantHouse). When using them, most of the delays are due to the operation of the operating system on which the software is running, as well as the network stack. To combat this, users can use high-performance network cards (such as those from Solarflare or Myricom) that speed up certain parts of the network stack.

Custom hardware HFT platforms

The relatively high delays of software trading platforms forced industry representatives to look for alternative approaches to reducing delays using special hardware. As a rule, things like ASICs are not considered in hft-trading, because they lack the flexibility to subsequently reconfigure or work with new protocols. GPUs also cannot offer significant performance. The FPGA (Field-Programmable Gate Arrays) technology has become a suitable tool for gaining flexibility and achieving the required performance.

FPGA can be used to speed up financial applications in various ways. One of them is called Hybrid Computing and is used, for example, in risk management models, calculating option prices and modeling portfolios. When applied, the speed of the system can increase by three orders of magnitude.

FPGAs are often used to create modern online trading systems. This iron is given the tasks of processing Ethernet, IP, UDP connections and decoding the FAST protocol.FPGA parallelism allows you to achieve a significant increase in speed compared to exclusively software tools. The architecture of the system described in this work looks like this:

This approach complements conventional multi-core processors with FPGA coprocessors. Typically, communication with the CPU is via high-speed connectors like FrontSide Bus (FSB), PCI Express, or QPI. Trading modules themselves in this case are written in high-level programming languages.

Another way to use programmable logic to speed up is to use the so-called Smart NIC. This usually refers to a combination of high-speed network interfaces, host PCI, memory, and FPGA interfaces. Here FPGA acts as a NIC controller, acting as a bridge between the host computer and the network and allowing you to integrate software logic directly along the data path. Thus, Smart NIC can operate as a trading platform under the control of the host machine's CPU.

With the help of modern FPGAs, you can implement any aspect of hft applications. Incoming market data can be entirely processed on the FPGA without the need to send it to the processor. The incoming network data is fed directly to a customized, highly optimized system through the MAC and PHY iron blocks. Moreover, in fact, the necessary information can be extracted even before the complete receipt of the package. Thus, the use of FPGA can achieve a significant reduction in overall delay.

The use of FPGA has its drawbacks in comparison with traditional approaches to the development of trading systems. The root of the problem is the higher complexity of the development flow for FPGA. A significant part of financial system developers and traders are not familiar with this technology and they lack the knowledge and expertise to implement hardware-oriented development.

Development and testing of new hardware solutions due to a lower level of abstraction is a more complex and lengthy process compared to the usual writing of a trading robot. All of this is illustrated in the figure below:

To avoid this, some FPGA-based hft-platforms have special high-level environments that allows you to create trading systems without the need for hardware description languages ​​(HDL).

The architecture of modern graphics cards is based on a scalable array of streaming multiprocessors. One such multiprocessor contains eight scalar processor cores, a multi-threaded instruction module, and a shared memory located on the chip (on-chip).

When a C program using the CUDA extensions calls the GPU kernel, copies of that kernel or threads are numbered and distributed to available multiprocessors, where they are already running. For such numbering and distribution, the core network is divided into blocks, each of which is divided into different threads. Threads in such blocks are executed simultaneously on available multiprocessors. To manage a large number of threads, the SIMT module (single-instruction multiple-thread) is used. This module groups them into "bundles" of 32 threads. Such groups are executed on the same multiprocessor.

In financial analysis, many measures and indicators are used, the calculation of which requires serious computing power. A measure called the Hurst exponent is used in time series analysis. This value decreases if the delay between two identical pairs of values ​​in the time series increases. Initially, this concept was used in hydrology to determine the size of a dam on the Nile River in the conditions of unpredictable rains and droughts.

Subsequently, the Hurst indicator began to be applied in the economy, in particular, in technical analysis to predict trends in the movement of price series.The following is a comparison of the performance of calculating the Hurst exponent on the CPU and GPU (acceleration rate β = total computation time on the CPU / total computation time on the GeForce 8800 GT GPU):

Experiments show that the use of graphics processors can lead to a significant increase in the performance of financial analysis. At the same time, the speed gain compared to using an architecture with a CPU can reach several tens of times. At the same time, you can achieve even greater productivity gains by creating GPU clusters - in which case it grows almost linearly. That is why GPU and FPGA technologies are used heavily in the construction of hft-systems.

What is a stock glass

Exchange Cup (eng. DOM, Depth of Market) is a list with a digital indication of the current applications for the purchase or sale of a stock market asset at the prices set by the participants. This indicator reflects the mood of bidders and is one of the most important tools for a trader. It also has other names - a glass of orders, a book of orders (Order Book), the depth of the market (Depth of Market), the second level (Level 2), a glass of a trading terminal (Open Book) - in other words, this is a table displaying information about the data submitted by sellers and current bidders.

During the trading session, the exchange platform collects thousands of applications from all participants every second and brings them together. Moreover, the order book is just a form of visualization of the limit orders closest to the current price.

An analysis of the stock market makes it possible to objectively assess the levels of supply and demand at the current moment of trading on the instrument of interest. Adherents of technical analysis use the book of orders to identify the line of least resistance for the movement of the price of an asset. Also, with the help of a glass, you can make short-term forecasts that are effectively used in scalping.

It is believed that with the rapid disappearance of bids in one direction, the price will soon move there. The main difference between a glass and price charts is that it does not provide a visual display of market data. It only displays incoming bids that are close to the market and the execution of which will in some way affect further pricing.

An increase or decrease in the price of an exchange instrument is determined by the distribution of supply and demand for it. In turn, supply and demand are dependent on the steps that are taken by active market participants. Any of the financial markets is a two-way auction. Suppose someone decided to sell 10 lots of a certain asset. To do this, a buyer should appear who is ready to buy the proposed amount of the asset at the stated price. Thus, a transaction occurs between the seller and the buyer, of which a large number of transactions on the exchange every second.

There are three types of exchange applications. Market buy / sell orders are executed at the best market value in the desired volume. Limit orders - ordinary orders, including the required asset, its price, as well as the desired volume. Conditional - these are all applications that require compliance with the conditions set by the market participant, excluding limit ones.

The stock market shows only limit orders. Transactions on the market are not visible, as they are executed instantly at the best prices. Conditional orders are not displayed due to the fact that they expect the onset of the required conditions under which they will become limit or market.

Applications that reflect the depth of the market are also divided into small, medium and large. Such a division is conditional and is performed relative to the average daily trading volumes for an instrument on a specific exchange platform. For example, if the average volume of transactions on futures on the RTS index is 1 million contracts per session, then an order for 2-5 thousandcontracts can be attributed to large applications, and it needs to be closely monitored.

In addition to dividing into types and volumes, applications are also subdivided according to their strategic purpose into aggressive and passive. Orders for purchase / sale, which are statically placed on prices that are next to each other in value, do not move, but protect a price mark and do not show aggression, they call passive. Market depth shows passive orders when the market approaches powerful graphic levels of support or resistance. As a result of the confrontation between bulls and bears, the level will be broken or quotes will rebound from it. Orders submitted from the market (market orders) are called aggressive.

Typically, such orders are the engine of prices. There are also aggressive bids of a different kind: they are limited, but at the same time they demonstrate a steady movement behind changing prices. Such orders tend to suddenly appear in the stock market and, when the market jumps in any direction, constantly strive for current value, pushing prices. Such movement of orders is capable of long-term maintenance of the direction of the market.

Often passive and aggressive orders are in interaction with each other, and a glass of prices reflects this interaction. When a support level is broken, it becomes a resistance line. At the same time, you can see the following situation in the glass: the concentration of passive orders is overcome, then an aggressive seller enters the game, placing orders at the nearest Ask levels.

Thus - now, to turn the market up, it will be necessary to break through the resistance, which many traders began to actively guard. Passive density is also used to set stop loss. If after opening a position a large seller appears, and the price moves down, then a stop order can be put safely 1-2 points higher than the price of this seller. If a large order is “eaten up” by the market, it is better to close the deal, because inertia is likely to pull quotes up.

Main categories of hft strategies

The more a trader knows about the activities of other market participants, the easier it is for him to make a decision and make money on it. For all this, a technical analysis is used, which includes data on prices, transaction conditions and trading volumes, which can be found in the stock market. A separate robot does this, and this data is used to configure trading algorithms.

Market making

A trader makes a profit due to the spread - the difference between supply and demand. The larger the spread, the more profit will result. The essence of this strategy is to increase competition between traders and investors, narrowing the spread in various assets. Such a strategy is widespread among large investment firms. It allows you to improve the quality and attractiveness of the trading platform. This type of strategy provides an increase in market liquidity and new areas for trade.

Liquidity is the ability to sell securities quickly and without significant losses. Popular stocks already have good liquidity. Investors who want to buy or sell a low-liquid share often have difficulty finding a counterparty willing to offer a reasonable price. The essence of the passive market-making strategy is to place a huge number of Limit orders on both sides of the price (slightly below the market when buying, higher when selling).

As a result, market liquidity is ensured, which makes it easier for private traders to complete transactions. Profit from hft trading in this case is formed due to the difference in prices of supply and demand. It is on this difference that the tweeter makes money. In addition, market makers often receive additional payment from trading floors for increasing liquidity.Moreover, the algorithm itself may not earn or even lose a little, while the trader will earn on payments from trading floors and, as a result, will be in the black.

This strategy is to increase competition between investors and traders and narrow the spreads in different assets by placing orders on either side of the price spread. Consequently, the new “territories” are the most beneficial for such strategies. Moreover, the larger the price spread of an asset, the more profit the strategy will bring as a result. Thus, the liquidity of the instrument on the site increases, the spreads narrow, which attracts new investors to the trading floor.

Frontranning

The basis of the algorithm is the speed of conclusion of a transaction upon detection of favorable conditions. The work of the algorithm can be divided into two periods - monitoring of all conditions for placing an application and the action when the application is already in operation.

First, an analysis is made for all large bids (demand prices) above a given condition, and if the system finds such a volume, then the robot places an order one step above this order. If the order is removed, then the application submitted by the robot is canceled, and monitoring continues. If the volume moves, then the robot also moves, while maneuvering to be one step ahead.

The calculation here is made on the fact that, before a large application is fully satisfied, the price will bounce several times from this volume.

Ignition pulse

The strategy of the ignition pulse, or the ignition of the momentum (momentum ignition), is used by traders to provoke bidders to quickly complete trading operations. At a time when there is rapid market movement, the difference between the prices of bids for sale and purchase in the market is expanding rapidly. This creates favorable conditions for profit.

For example, the purchase price of a share is $ 200, and the sale price is $ 200.01, and then the purchase price changes to $ 199 and the sale price becomes already $ 200 per share. In such circumstances, it turns out that the sale price becomes the previous purchase price, and the execution of the last remaining orders in the queue for the purchase of $ 200 will allow the trader to resell the stock at $ 200. The goal of directional strategies is to profit by predicting the directional movement of securities prices. In this they differ from other types of strategies, assuming unhedged risks.

In some cases, hft traders themselves try to provoke market participants to quickly complete trading operations, leading to sharp price fluctuations. The essence of the principle, called "spoofing", is the manipulation of algorithms and manual traders who are forced to conduct aggressive trading. In addition, when using this strategy, the player can cause a further price movement due to the set stop-losses. Spoofing is considered an illegal strategy, but it is difficult to detect and prove.

Statistical Arbitration

A neutral market strategy that makes a profit in any situation of inequality on the exchange. The strategy is based on the search for discrepancies between prices, through the receipt of various news affecting the financial market.

The Hft algorithm monitors prices and trading volumes on various exchanges in anticipation of significant events in search of abnormal behavior. According to it, a trader even before the official news appears reacts to deviations and concludes a deal. The essence of the strategy of earning hft-traders through arbitrage operations is to find discrepancies between prices of the same financial instruments in different markets.

Statistical arbitrage aims to profit from the formation of price inequalities between related trading floors. hft-traders try to find correlations between related financial instruments (for example, between a stock and futures on it) and earn income on the imbalance between them.

This is a market-neutral strategy that makes a profit in any given situation on the exchange - the market goes down, up or stands still, based on the effect of high correlation of asset prices. The instruments in this strategy are option contracts, bonds, forward and futures contracts, derivative financial instruments. This type of arbitration uses mathematical modeling methods and can be applied at any time intervals.

Arbitration of Delays

It aims to generate income through the earning of data on financial instruments. To have an advantage in time, traders place machines with algorithms as close as possible to the exchange servers, ideally in the same machine room.

The financial instruments used at different trading floors are interconnected, and price fluctuations on one exchange affect all others. During trading, all information cannot be moved instantly, for example, between the exchanges of Chicago and New York, 1,200 km. In time, it is about 5 milliseconds. Trading robots on the New York site receive information with a delay.

Arbitration of delays (latency arbitrage) is aimed at generating income by the hft-trader due to earlier receipt of data. For this purpose, servers with trading software are located in exchange data centers (colocation) near equipment used to host exchange system cores. As a result, hft-traders receive important information a moment earlier than other market participants.

Liquidity detection

With this strategy, high-frequency robots try to detect large or hidden bids from conventional platforms and from automated systems even before the start of trading. To this end, robots send small bids to the market, track the time of their execution, thus tracking when there should be a major transaction.

Trade by tape

This strategy tracks all events on the stock markets, such as sales and price quotes. This helps to gather a lot of important information. Monitoring of all information (certain stocks) and all significant events (company news, reporting and macroeconomic data output) allows us to calculate the abnormal behavior of sales volume and stock prices. As a result, the high-frequency robot is able to determine the “patterns” in advance of all the collected and analyzed information before the official news.

Exchange crash due to hft algorithms

The incident occurred on May 6, 2010. On that day, the Dow Jones index fell 990 points in 5 minutes for no reason. This created a panic in the market and a decline in quotations. As it became known later, at that time the market share of hft-traders amounted to 70%, and it was enough for them to close their positions so that the market collapsed.

Since their work scheme is in many respects similar, this is exactly what happened from 14:42 to 14:47 on May 6. The above events caused a strong resonance in society. The media disseminated criticism, there were many protests against financiers, politicians who gathered commissions and hearings in order to ban high-frequency trading or tax it. Nevertheless, all this turned out to be futile, and hft-trading only strengthened its position in the market.

Another case occurred on October 15, 2014, when the yield on treasury bonds fell by a quarter percent within a few hours. The fall occurred completely unexpectedly and, judging by indirect evidence, was a consequence of the work of the hft-strategy.

In addition, despite the fact that high-frequency traders generate a large number of applications for the purchase and sale of financial instruments, in reality, not all of them lead to increased liquidity. Trading robots generate a large number of orders, which in reality do not lead to transactions, or transactions are not carried out with real shares, but with ETF exchange funds.

Who uses HFT

Only developed investment structures and funds can afford the content of high-frequency trading programs. Private investors and traders are far from a similar industry, it is not available to them. With rare exceptions, prop-trading companies working with hft on their own funds are also found. In general, all users of high-frequency trading can be divided into four categories:

  • Independent proprietary trading companies;
  • Affiliates of brokers;
  • Hedge funds;
  • Large banks, investment structures.

This state of affairs is associated with several factors:

  • The need for high production capacities;
  • Mandatory optimization of the trading structure and installation of the hft server close to the exchange gateways using the FIX / FAST protocol;
  • Implementation of high-level programming languages ​​C ++, Java, etc .;
  • Large investments.

All this taken together is inaccessible to the ordinary trader, regardless of his financial capabilities or desire. Many describe this infrastructure as a monopoly in the stock market, which also requires corporate ties and a special position. This is not surprising, since hft-companies receive information about all transactions in the market much earlier, and, as a result, have a huge advantage over other market participants.

Will high frequency trading disappear?

High-frequency trading has existed for a long time and in recent years has encountered a number of problems: physical boundaries, rising infrastructure costs, competition, reduced profits and increased regulation. Because of all this, the share of hft in total trade is steadily declining in the western market. However, high-frequency trading still accounts for more than half of all transactions in the US and Europe.

The influence of high frequency trading was wide and probably lasting. The infrastructure and practice of hft may become indispensable attributes for the financial industry of the future, as high-frequency trading improves the quality of markets not only for institutional investors, but also for retail.

High-frequency trading algorithms are speed-oriented, mainly because most of them use arbitrage or passive investment strategies to generate their income. Higher trading volumes and liquidity are the most significant, long-term and noticeable effects on equity markets today. Total US stock trading has doubled since the advent of high-frequency trading.

The ultra-high trading volume leaves no options for players looking for tiny profits from millions of transactions, so the growth in volumes has significantly changed the balance of power in the market. So hft algorithms increase liquidity due to passive market-making.

This feature of high-speed traders plays an important role when there is a significant outflow of liquidity from ordinary suppliers during market shocks caused by important macroeconomic news, political events, or natural disasters.

The profits of most hft players require extremely high levels of volatility of preferred assets. On the other hand, stock price volatility is the main building block of the market. Therefore, high volatility is undesirable for large institutional investors and companies. It can lead to an increase in the perceived risk of shares in the company, and therefore to an increase in the weighted average cost of capital - the cost of providing each source of financing for the company.

Ultra-high trading volumes resulting from high-frequency trading affect the dynamics of price changes during the trading day and can reduce stock volatility, since hft players provide liquidity to the market and allow large traders to complete their transactions without significantly affecting stock prices, indirectly reducing price deviations .

The argument that this liquidity is a kind of fake can be refuted by the fact that strategies in the high-frequency trading market do not benefit from the movement of stock prices. They create income from the difference in purchase and sale prices and discounts provided by the electronic system of transactions of purchase and sale (ECN).

High-frequency traders disclose the largest and most liquid assets, constantly provide liquidity and actually form the market, therefore, we can say that hft reduces the difference in purchase and sale prices for companies with large capitalization and contributes to faster market pricing.

The increased liquidity effect may allow traditional institutional investors to more easily adjust their portfolios to reflect their fundamental views on company performance. In this way, hft can reduce the transaction costs that institutional investors face and helps bring market prices closer to their fundamental value.

Not everyone likes high-frequency trading, but it clears the market of irrational investors. Due to the HFT, they are unable to withstand lightning-fast price changes.

In relation to hft, the financial world is divided into two camps: those who think that markets have benefited from this technology, and those who claim that high-frequency trading is beneficial only to a handful of academics supported by venture funds, and trading floors that have gained advantages over retail investors .

But after almost 10 years of rapid technological development, dozens of cases of market collapse and increased trading speed, high-frequency trading can be seen as a natural outcome of attempts to make financial markets more efficient, bring them closer to theoretical purity and enable them to immediately reflect any new information.

There will always be two points of view at hft, but it must be taken into account that in 5-7 years, high-frequency trading will be closely connected with artificial intelligence and machine learning. Recent improvements in high-frequency trading have significantly changed the course of trading processes in the markets, but it is unclear whether this effect will be positive or negative.

How to make money using hft systems

Most investors probably never saw the equity of a high-frequency strategy. There are objective reasons for this: due to the typical performance of such strategies, firms using them have little need to attract outside capital. In addition, hft algorithms have capacity limitations, which is very important for institutional investors. Therefore, it is interesting to observe the investor's reaction to the profitability of the hft strategy, which he sees for the first time. Accustomed to the Sharpe ratio in the range 0.5-1.5 or up to 1.8, with a successful set of circumstances, he is amazed that such strategies show the values ​​of the coefficient expressed in double-digit numbers.

To illustrate, the figure above shows a performance graph for one of these hft strategies, which trades about 100 times a day with the E-mini S & P500 futures contract (including a night session). Note that the statistical advantage of the algorithm is not very high - on average 55% of profitable trades and profit per contract about half a tick are common characteristics of most high-frequency strategies. But due to the large number of transactions, they lead to significant profits. At this frequency, exchange commissions are small, the tariff is about $ 0.1 per contract.

However, the additional costs associated with the use of the strategy are hidden from us: payment for market data, a software platform and an Internet connection, which provides obtaining large amounts of data and speed for tracking microstructural signals, and managing the placing of orders with the best priority. Without this infrastructure, strategies are unlikely to be profitable.

We will slightly lower our requirements and consider an intraday strategy with the number of transactions approximately equal to 10 per day, at 15-minute bars. Although this is not an ultra-high frequency, nonetheless, the algorithm is high enough to be sensitive to delays. In other words, you cannot implement such a strategy without high-quality market data and a trading platform with minimal execution delays of 1 millisecond.

With the same probability of profitable transactions as in the first strategy, a lower frequency of transactions makes the profit per contract more than 1 tick, while the equity line is much less smooth, which reflects the Sharpe ratio of only about 2.7.

The most important characteristic of hft algorithms is the probability of execution of limit orders. Strategies most often use limit or IOC (if they are not immediately executed, then cancel) orders, only a certain percentage of which will be executed. When receiving the right signals, profit increases in direct proportion to the number of transactions, which, in turn, depend on the probability of execution. A probability of 10% to 20% is usually sufficient to guarantee profitability (although this also depends on signal quality). The low probability of execution, which usually happens when trading through widely offered trading terminals, will destroy the profitability of any high-frequency strategy.

How to become a quantum in an hft company

Developing algorithms for hft is a knowledge-based activity. At a minimum, you will need mathematics and economics, and only then specific programming languages ​​and technologies. The need for fast work of algorithms leads to the fact that in the financial market the main programming languages ​​are C, C ++ and Java. Experience in optimizing package processing, working with databases, and using the scripting languages ​​Python and MATLAB are also appreciated, with the help of which primary testing and development of trading strategies are performed.

Most high-frequency trading companies are small. Their modest staff usually numbers about 20-25 people. This is due to the fact that employees of such firms follow a well-defined entrepreneurial culture and a meritocratic outlook on life. At the interview, you, as a candidate, will be asked what innovations you can bring to the organization.

Given the fact that the bonus fund is common to all (although it is distributed taking into account the different weights of an employee), you will need to demonstrate the ability to generate income that (explicitly or implicitly) exceeds your salary and bonus. Otherwise, you simply do not make sense to hire. That is, in order to even begin to consider you as a candidate for a position, you need to show skills that no one else has in the organization.

On the other hand, there is a chance to create a place for yourself. People in the company may not even look for new employees, but if they realize that you have rich experience in a certain field, they can open a vacancy for you. A meritocratic approach in hft firms usually allows sufficient autonomy in projects. Therefore, if you want to work in an initiative environment side by side with extremely smart and talented people, then probably hft will suit you.

Working hours in this area are above average. 60-70 hours a week is not uncommon, especially when the project deadline is close. However, intense intellectual work and monetary compensation usually outweigh the workload. This lifestyle is not for everyone.

Keep in mind that HFT is a purely technical field. It attracts the most prominent candidates in the field of mathematics, physics, computer science and electrical engineering, most often during their postgraduate studies or after several years of work in any highly specialized field of industry.Despite its high pay, working in hft-firms will require significant costs in terms of training and investment.

Usually people come to hft firms after:

Graduate studies. Most hft-firms hire candidates after graduate school in a specific direction relevant to the company's tasks. Such an approach is the simplest, since according to the doctoral dissertation, publications or the status of the university it is easier to determine the candidate's abilities. Therefore, if you really want to make a career in the field of hft, research in the field of low latency systems for transmitting information can be a good help. Also, there are frequent cases of selection of distinguished students from the last courses of the most popular technical universities (MIT, Stanford, Cambridge, Imperial) with their subsequent training for a specific position.

Gaining experience in the high-tech industry. Experts in specific areas where minimal data transmission delays are required (for example, in telecommunications) are usually hired for their knowledge of the subject area. However, it is worth noting that, as a rule, for normal work in their field, in any case, they need an extensive technical base. Scientists working on projects related to high-performance computing (for example, in the CERN data center or other national laboratories with supercomputers) are in high demand due to their experience in working with big data.

Experience on the stock exchange. Demanded are those who know how the work of the exchange is organized "from the inside." This is explained by the fact that such people are most likely to help in creating new algorithms that advantageously use the information architecture of a particular exchange.

One of the most common misconceptions is the firm belief that to gain a place in the hft field, extensive knowledge of finance is required. Most hft-firms do not pay attention to the availability of knowledge in the field of finance, given the sufficient level of technical competence of the candidate in other areas necessary for the organization.

Job responsibilities at hft-firms are very diverse. Almost every employee is forced to have a higher technical education and the ability to conduct independent research in this area (he should know the theoretical material well). Since hft is essentially a technology sport, most should also have knowledge in computer engineering, electrical engineering, or experience working with low latency data transmission in other areas, such as telecommunications.

There is also now a demand for knowledge and experience working with a certain type of software, such as graphic processors (GPUs) and user-programmable matrices (FPGAs).

By and large, any subject area that can somehow reduce delays in bidding or increase the speed of algorithmic calculations will find its place in the HFT. Examples of such areas are:

Schemes of the work of stock exchanges. Among those engaged in high-frequency trading, the basis of skills is extensive knowledge in organizing the work of stock exchanges. Knowing how the application book works, as well as all the intricacies of technology on a particular exchange, can play into your hands.

Processor architecture. High-frequency trading involves a significant number of operations in a relatively short period of time. Keep in mind that increasing the speed of these operations in any way will do you a plus. It is useful to have knowledge of processor architectures and hardware, especially systems other than x86 architecture (such as GPUs and FPGAs).

Networks with minimal delays in transmitting information. One of the main sources of data transfer delays in trading is the network stack.HFT firms value experience in optimizing packet processing, writing custom network modules, and using the Infiniband high-speed switched serial bus.

Understanding the laws. Knowledge of such legal acts as the "Regulation of the National Bank System" (Regulation NMS) of the United States of America and the EU directive "On financial instrument markets" is necessary in HFT operations.

Kernel optimization. The main objective of optimization is to reduce delays and increase the speed of operations. Therefore, today there are frequent cases of rewriting the core software to speed up the process. Many HFT firms value their experience in modifying the Linux kernel.

Online Algorithms. Speaking of delays in performing operations, I did not go into details of the operation of HFT algorithms. Often, these algorithms include "repeating" operations with arithmetic mean, error, and linear regression. Therefore, the analysis of the results of previous calculations in time is very important.

Programming languages. Despite the fact that most UHFT firms have switched to specialized hardware (for direct processing of information and network exchange), in cases less dependent on delays, trading firms can use multithreading of C, C ++ and Java languages ​​(with a special garbage collector). Some trading firms value their experience with such languages ​​and parallel computing.

As you can see, these skills are often technical in nature and require an academic degree or several years of work with certain technologies on an industrial scale. If you have experience with the above things, then you have a chance to prove yourself in an interview with an hft-firm.

As with most finance jobs, it’s worth looking for a job through employment agencies. The largest hft firms are located mainly in New York and London. Chicago also has a large number of organizations involved in high-frequency trading. Recruiters are usually knowledgeable in the subject area and are able to answer whether your experience is suitable for the requirements of this position. Note that the bar is very high! Most likely, you will have to do your best to find a job, which can take a lot of your time.

Despite the fact that you can apply directly to the company, the most difficult is the process of finding companies engaged in high-frequency trading. Usually, if you are popular in your highly specialized field, the organization will try to hire you on its own. This can play into your hands if you really want to work in this company, publish your research, participate in conferences and just seriously improve your track record.

Conclusion

So, today we have opened the veil into a rather secretive, but very interesting world of high-frequency trading. Not all types of hft trading are useful, there are toxic trading systems, but mostly hft is good. It is quite difficult, almost unrealistic, to enter the hft business on your own, so traders unite to organize private companies. Nevertheless, it is already quite difficult for them to compete with large companies. The competition in this area is so great that if you want to engage in hft, you should look for a quantum job in a large fund. But for a successful interview you must have a lot of useful skills and excellent higher education (or better several), so this path is very difficult.

Also, do not trust the sellers of advisers if they claim that they have developed an hft-algorithm for one of the Forex trading terminals - the probability that these are not scammers is practically excluded. The same goes for arbitration, as a special case of hft.No matter how modern the terminal is, with the scheme of connecting to the trading platform through a broker, your speed of transactions will be uncompetitive and, even if you manage to earn something, it will happen in a very short period of time. The forex market already has a large number of professional hft systems using expensive equipment and systems developed by a whole staff of employees.

However, at the moment there are markets in which there is almost no competition. For example, cryptocurrency exchanges, like securities exchanges or many forex trading platforms, provide access to trading through their api. This market is still very young and very slow technologies are used on it. For example, the average time per transaction on a typical crypto exchange is so far about a second - as at the very beginning of the formation of the hft direction. And if you want to engage in hft trading, try your luck, then this market can be a great launching pad. It will definitely develop, exchanges will update their equipment and speeds will increase. In the meantime, you have a chance to enter this business first, while large professionals have not come to the cryptocurrency markets. Some types of hft systems are already used in the cryptocurrency markets, and their owners receive super-profits, but competition is still very low.

I hope this information was useful to you, and you will draw the right conclusions. Even if you are not going to deal with hft systems, this article will allow you to understand the big picture. If you decide to try to write / create your hft system, I recommend that you pay attention to emerging markets, for example, cryptocurrency.

Watch the video: High Frequency Trading (November 2019).

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