"Before long,
investors and portfolio managers began to tap the world’s premier math,
science, and engineering schools for talent. These academics brought to trading
desks sophisticated knowledge of AI methods from computer science and
statistics.
And they started
applying those methods to every aspect of the financial industry. Some built
algorithms to perform the familiar function of discovering, buying, and selling
individual stocks (a practice known as proprietary, or “prop,” trading). Others
devised algorithms to help brokers execute large trades—massive buy or sell
orders that take a while to go through and that become vulnerable to price
manipulation if other traders sniff them out before they’re completed. These
algorithms break up and optimize those orders to conceal them from the rest of
the market. (This, confusingly enough, is known as algorithmic trading.) Still
others are used to crack those codes, to discover the massive orders that other
quants are trying to conceal. (This is called predatory trading.)"
