[THE VIEW]AI High-Frequency Trading and Investor Protection

IEX in the U.S. Continues to Introduce
Financial Safety Trading Technologies
to Block High-Frequency Traders

Long ago, when it came to stock trading, people would imagine scenes of visiting securities firms to conduct transactions or shouting around to exchange trading-related information. The current situation, where trading is easily done in front of a computer or via a mobile phone, shows that technological advancements have brought significant changes not only to our daily lives but also to financial transactions.

The advancement of technology has changed not only the methods of trading but also the execution of strategies. When good information about a certain company is newly revealed, the stock price of that company generally rises, so buying at the lowest possible price before the stock price goes up remains a useful strategy. In the 18th century Amsterdam Stock Exchange, stocks traded on the London Stock Exchange were also traded, and it was natural that if the London Stock Exchange stocks rose, the same stocks would rise on the Amsterdam Stock Exchange as well. In the 18th century, newspapers containing stock price information were sent to Amsterdam by ship, and there are records that horses were kept waiting at the port to get to the exchange faster.

One might think such things no longer happen today, but that is not necessarily the case. High-frequency traders or algorithmic traders use programs that enable faster analysis and quicker processing of trade orders by computers. There is even a trend of locating servers close to the exchange servers.

Unlike Korea, the U.S. stock market operates multiple exchanges simultaneously rather than a single exchange. The New York Stock Exchange and NASDAQ, which we know, are just some of them. Investors sometimes send orders to other exchanges to ensure that trades are generally executed at the best available price, regardless of which exchange registered with the Securities and Exchange Commission they trade on.

High-frequency traders profit by observing orders moving from one exchange to another and then sending signals faster to other exchanges to execute trades or modify quotes. Such actions by high-frequency traders disadvantage slower investors, dampen investment sentiment, and cause liquidity reduction issues.

In response, the U.S. National Stock Exchange, Investors Exchange (IEX), made headlines by installing a coil on its servers that forcibly delays incoming signals by 350 microseconds to block high-frequency traders. However, as this alone became insufficient, IEX developed the ‘Quote Volatility Index (CQI)’ system using various statistical methods and machine learning to predict price volatility, and from 2020 introduced a modified limit order trading method called ‘Discretionary Limit (D-Limit) trading.’ This method uses artificial intelligence (AI) algorithms to predict price fluctuations and adjust quotes so that investors can trade at more favorable prices.

Through these innovations, IEX, which had less than 1% market share in 2014, now consistently accounts for more than 2% of the total trading volume in the U.S. stock market and enjoys relatively better liquidity compared to other exchanges, generating significant profits. As trading strategies diversify with technological advancements, countermeasures in financial markets to address their side effects are also continuously evolving.

Seonggyu Park, Professor at Willamette University, USA