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The crash on October 19, 1987, a date that is also known as Black Monday, was the climactic culmination of a market decline that had begun five days before on October 14. The DJIA fell 3.81 percent on October 14, followed by another 4.60 percent drop on Friday, October 16. On Black Monday, the Dow Jones Industrials Average plummeted 508 points, losing 22.6% of its value in one day. The S&P 500 dropped 20.4%, falling from 282.7 to 225.06. The NASDAQ Composite lost only 11.3%, not because of restraint on the part of sellers, but because the NASDAQ market system failed. Deluged with sell orders, many stocks on the NYSE faced trading halts and delays. Of the 2,257 NYSE-listed stocks, there were 195 trading delays and halts during the day.[27] The NASDAQ market fared much worse. Because of its reliance on a "market making" system that allowed market makers to withdraw from trading, liquidity in NASDAQ stocks dried up. Trading in many stocks encountered a pathological condition where the bid price for a stock exceeded the ask price. These "locked" conditions severely curtailed trading. On October 19, trading in Microsoft shares on the NASDAQ lasted a total of 54 minutes.

There is no numerically specific definition of a stock market crash but the term commonly applies to steep double-digit percentage losses in a stock market index over a period of several days. Crashes are often distinguished from bear markets by panic selling and abrupt, dramatic price declines. Bear markets are periods of declining stock market prices that are measured in months or years. Crashes are often associated with bear markets, however, they do not necessarily go hand in hand. The crash of 1987, for example, did not lead to a bear market. Likewise, the Japanese bear market of the 1990s occurred over several years without any notable crashes.

What Happens When the Stock Market Crashes?


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The mathematical description of stock market movements has been a subject of intense interest. The conventional assumption has been that stock markets behave according to a random log-normal distribution.[9] Among others, mathematician Benoît Mandelbrot suggested as early as 1963 that the statistics prove this assumption incorrect.[10] Mandelbrot observed that large movements in prices (i.e. crashes) are much more common than would be predicted from a log-normal distribution. Mandelbrot and others suggested that the nature of market moves is generally much better explained using non-linear analysis and concepts of chaos theory.[11] This has been expressed in non-mathematical terms by George Soros in his discussions of what he calls reflexivity of markets and their non-linear movement.[12] George Soros said in late October 1987, 'Mr. Robert Prechter's reversal proved to be the crack that started the avalanche'.[13][14]
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