The stock market crash of 1987 revealed the role of financial and technological innovation in increased market volatility. In automatic trading, also called program trading, human decision-making is taken out of the equation, and buy or sell orders are generated automatically based on the price levels of benchmark indexes or specific stocks. Leading up to the crash, the models in use tended to produce strong positive feedback, generating more buy orders when prices were rising and more sell orders when prices began to fall.
After the crash, exchanges implemented circuit breaker rules and other precautions that slow down the impact of trading irregularities. This allows markets more time to correct similar problems in the future. For example, if stocks dove by even 7% today, trading would be suspended for 15 minutes.
While program trading explains some of the characteristic steepness of the crash (and the excessive rise in prices during the preceding boom), the vast majority of trades at the time of the crash were still executed through a slow process, often requiring multiple telephone calls and interactions between humans.
With the increased computerization of the markets today, including the advent of high-frequency trading (HFT), trades are often processed in milliseconds. As a result of incredibly rapid feedback loops among the algorithms, selling pressure can mount within moments, and huge losses can be experienced in the process.