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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.
Markets can also be stabilized by large entities purchasing massive quantities of stocks, essentially setting an example for individual traders and curbing panic selling. However, these methods are not only unproven, they may not be effective. In one famous example, the Panic of 1907, a 50 percent drop in stocks in New York set off a financial panic that threatened to bring down the financial system. J. P. Morgan, the famous financier and investor, convinced New York bankers to step in and use their personal and institutional capital to shore up markets.

Research at the Massachusetts Institute of Technology suggests that there is evidence the frequency of stock market crashes follows an inverse cubic power law.[15] This and other studies such as Prof. Didier Sornette's work suggest that stock market crashes are a sign of self-organized criticality in financial markets.[16] In 1963, Mandelbrot proposed that instead of following a strict random walk, stock price variations executed a Lévy flight.[17] A Lévy flight is a random walk that is occasionally disrupted by large movements. In 1995, Rosario Mantegna and Gene Stanley analyzed a million records of the S&P 500 market index, calculating the returns over a five-year period.[18] Researchers continue to study this theory, particularly using computer simulation of crowd behaviour, and the applicability of models to reproduce crash-like phenomena.
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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]
If you’ve gone with a “set it and forget it” strategy — like investing in a target-date retirement fund, as many 401(k) plans allow you to do, or using a robo-advisor — diversification already is built in. In this case, it’s best to sit tight and trust that your portfolio is ready to ride out the storm. You’ll still experience some painful short-term jolts, but this will help you avoid losses from which your portfolio can’t recover.
Research at the Massachusetts Institute of Technology suggests that there is evidence the frequency of stock market crashes follows an inverse cubic power law.[15] This and other studies such as Prof. Didier Sornette's work suggest that stock market crashes are a sign of self-organized criticality in financial markets.[16] In 1963, Mandelbrot proposed that instead of following a strict random walk, stock price variations executed a Lévy flight.[17] A Lévy flight is a random walk that is occasionally disrupted by large movements. In 1995, Rosario Mantegna and Gene Stanley analyzed a million records of the S&P 500 market index, calculating the returns over a five-year period.[18] Researchers continue to study this theory, particularly using computer simulation of crowd behaviour, and the applicability of models to reproduce crash-like phenomena.
On October 24, many of the world's stock exchanges experienced the worst declines in their history, with drops of around 10% in most indices.[38] In the US, the DJIA fell 3.6%, i.e. not as much as other markets.[39] Instead, both the US dollar and Japanese yen soared against other major currencies, particularly the British pound and Canadian dollar, as world investors sought safe havens. Later that day, the deputy governor of the Bank of England, Charles Bean, suggested that "This is a once in a lifetime crisis, and possibly the largest financial crisis of its kind in human history."[40]
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