Many experts believe that high-frequency trading creates an excessively high load on the financial market infrastructure. Auto trading systems can place multiple orders per second for each instrument, with only a small fraction of these orders resulting in trades. Thus, the exchange infrastructure is loaded, most of the time working idle. Also, automated trading systems are associated with the risks of software, hardware or human errors. For example, ATS played a significant role in the short-lived fall in the US stock market in 2010, when high-frequency liquidity providers abruptly halted operations. Then algorithmic and high-frequency trading became the subject of numerous proceedings initiated by the SEC and the CFTC. Another example is the so-called Knightmare on the New York Stock Exchange, which happened on August 1, 2012.
At that time, the updated algorithmic engine of Knight Capital Group, due to errors in the settings, placed buy orders for $3.5 billion in 45 minutes, and sell orders for $3.15 million. Due to incorrect actions of the software, the market for some assets moved more than on 10%. Knight Capital's net loss was $460 million. The next day, the company filed for bankruptcy. In 2012, the European Parliament discussed the introduction of significant restrictions or even a complete ban on high-frequency trading.
Despite many proposals in both the EU and the US, few countries have introduced legal restrictions on high-frequency trading. One of the first was Italy, which on September 2, 2013 introduced a tax directed against high-frequency traders. Thus, transactions lasting less than half a second were subject to a fee of 0.02%. At the same time, many researchers are convinced that automated trading improves market liquidity and reduces trading costs. .