High-frequency traders seize the opportunity of a slight lag in prices, earning nearly $5 billion a year in global stock markets, a new study, amounting to a modest but significant tax on investors. The study, published by the Financial Conduct Authority (FCA) on Monday, reveals a controversial practice known as “delayed arbitrage” in which high-frequency traders seek to respond more quickly to new information that affects market movements than other traders.
High-frequency traders grab better prices before ordinary investors. Arbitrage also reduces the willingness of the other side of the deal to offer better prices, which can also cost retail participants.
This information can range from company news to economic data to price fluctuations in other stocks or markets. Electronic trading companies invest in cutting-edge technologies, such as a network of microwave antennas connected to exchanges thousands of miles apart, to process this information and execute transactions in a millionth of a second.
The FCA found that the average competition between electronic trading companies lasted only 79 microseconds (1 microsecond equals one millionth of a second), faster than the blink of an eye, and that only the fastest companies that executed the deal struck any benefit.
While each arbitrage contest has produced only a small victory for high-frequency traders, the FCA’s research tracked 2.2 billion such high-frequency trades in 43 trading days on the London Stock Exchange. In all, more than 20% of the total volume tracked by the FCA comes from these potential arbitrage contests.
“Overall, these actions add up to serious damage to liquidity,” the FCA’s study said. Our main estimate suggests that eliminating deferred arbitrage will reduce transaction costs by 17%. “
The study found that the negative result of this high-frequency trading increases the cost of buying and selling stocks for the average investor. The FCA’s research is focused on the UK, and the authors of the report say they hope “other researchers and regulators will be able to replicate our analysis of markets outside the UK stock market”.
“As far as we know, most regulators don’t currently get data from exchanges, and exchanges seem to store information data inconsistently to some extent. We hope that will change. “
The FCA’s study comes against the backdrop of a push by politicians in Europe and the United States, including independent Senator Bernie Sanders of Vermont and Senator Elizabeth Warren, Democrat of Massachusetts, to impose a financial transaction tax. One of the aims of this policy is to curb high-frequency trading.
The study could also push exchanges to restructure the market more to limit late arbitrage, for example by introducing an instant delay before trading, i.e. by setting a deceleration band.
How did high-frequency trading come from birth to rise?
In the 17th century, the Rothschilds succeeded in arbitrage across national borders on the same type of securities, using pigeons to deliver messages, so they always outperformed their competitors.
1983 – Bloomberg acquires a $30m investment from Merrill Lynch to build its first computer system to provide real-time market data, financial calculations and analysis to Wall Street financial firms.
1998 – The U.S. Securities and Exchange Commission authorizes electronic exchanges, paving the way for computerized high-frequency trading services that are more than 1,000 times faster than manual.
At the beginning of the 21st century, high-frequency trading had reached a second execution time, and by 2010 that rate had dropped to milliseconds and subtlety, reaching nanoseconds in 2012.
The 2010 U.S. stock crash – On March 6, 2010, $4.1 billion worth of electronic transactions triggered a flash crash in financial markets, the Dow Jones (28722.8496, 187.05, 0.66%) index plummeted 1,000 points in a single trading day, wiping nearly $100 million in market value. Until the market is on the road to recovery, it is still able to see a five-minute plunge of 600 points. The SEC and the Commodity Futures Trading Commission (CFTC) held HFT primarily responsible for the crash.
2011 – Nano-second trading technology is launched: A company called Fixnetix develops microchips that allow transactions to execute at a rate of nanoseconds. (1 nanoseconds s 0.000000001 seconds)
2012 – High-frequency trading accounts for about 70 percent of U.S. stock trading.
2012 – Many IT companies start investing millions of dollars in HFT technology. A new computer chip specifically introduced for HFT increases execution speed. 000000074 seconds; a $300 million transatlantic cable project is under construction, with the sole aim of reducing trading hours between New York and London by 0.006 seconds.
2013 – Economists argue about the riskiness of high-frequency trading since the flash crash of 2010. Michael Spence, a Nobel Prize-winning economist, argues that high-frequency trading should be banned.
In fact, high-frequency trading is not only a loss for ordinary shareholders in the stock market, but also in the foreign exchange market.
For example, the pound crash on 7 October 2016. The pound fell 6.1 per cent in two minutes. Industry insiders believe it was a massive sell-off triggered by “rogue” algorithmic trading. . . At the time, many news sites and social media were cingling for Brexit, and computer algorithms used it as a signal to sell the pound. Once the pound is on a downward trend, more high-frequency traders will join in, reinforcing this trend and eventually creating a strong short selling pressure in a short period of time.
In addition, on January 3, 2019, the foreign exchange market experienced an unusual fluctuation. Within minutes of Asian markets, the dollar suddenly plunged against the yen, even above 400 points at one point. It is difficult for the industry to draw conclusions about the factors that led to the January 3 crash, in part because trading activity in the foreign exchange market is taking place through many different platforms. However, it is not difficult to find the key factors in the event, including high-frequency algorithmic trading in a low-liquidity environment to amplify this “flash” event.