High-frequency trading (HFT) is the practice of using high-speed computerized systems to search for minor differences in price of stocks that can be exploited for small financial gains. HFT has increased dramatically over the last decade. In the US and Europe, it now accounts for nearly one-half of all trades.

HFT is an effective way to synchronize prices in financial markets, making the values of related securities change concurrently. Price synchronization leads to increased efficiency: prices are more accurate and transaction costs are reduced. During times of stress, however, localized errors quickly propagate through the financial system if safeguards are not in place.

In “High-Frequency Trading Synchronizes Prices in Financial Markets”, Austin Gerig of Oxford University shows how HFT synchronization is actually quite similar to the way flocks of birds or schools of fish synchronize their movements. In animal groups, synchronized behaviour facilitates information transfer between individuals, increasing the accuracy of decisions and allowing fewer resources to be allocated to information gathering. In a school of fish, for example, by synchronizing their behaviour, fish can scan their environment using “many eyes”, which allows them to quickly evade threats or move towards potential food sources.

Financial markets works in a similar way. In markets, the state of the economy is monitored by a large number of investors who quickly broadcast any changes to each other via price movements. By synchronizing prices, HFT allows the “many eyes” of different investors to function as one coherent group, which results in price trajectories that look like the motions of schooling fish (See Figure)

HFT systems operate with minimal human supervision and have been blamed for a number of unusually violent swings that have taken place in the stock market. In “Abrupt rise of new machine ecology beyond human response time”, the authors make a pretty compelling case that fast trading systems have caused a fundamental change in the behaviour of the stock market, a transition to a new all-machine phase:

(…) far from simply generating faster versions of existing behaviour, we show that this speed-up can generate a new behavioural regime as humans lose the ability to intervene in real time. Analysing millisecond-scale data for the world’s largest and most powerful techno-social system, the global financial market, we uncover an abrupt transition to a new all-machine phase characterized by large numbers of sub-second extreme events

This shift leads to sudden changes in the value of stocks that aren’t necessarily linked to any underlying financial factors. In most cases, the change seems to be transient, and stocks return to their former value rapidly. What’s not at all clear is what triggers these ultra-fast extreme events. In the markets, it is not always easy to the see the sharks and the hungry heron in the beach!