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Stock market crashes are social phenomena where external economic events combine with crowd behavior and psychology in a positive feedback loop where selling by some market participants drives more market participants to sell. Generally speaking, crashes usually occur under the following conditions:[1] a prolonged period of rising stock prices and excessive economic optimism, a market where P/E ratios (Price-Earning ratio) exceed long-term averages, and extensive use of margin debt and leverage by market participants. Other aspects such as wars, large-corporation hacks, changes in federal laws and regulations, and natural disasters of highly economically productive areas may also influence a significant decline in the stock market value of a wide range of stocks. All such stock drops may result in the rise of stock prices for corporations competing against the affected corporations.
Since the crashes of 1929 and 1987, safeguards have been put in place to prevent crashes due to panicked stockholders selling their assets. Such safeguards include trading curbs, or circuit breakers, which prevent any trade activity whatsoever for a certain period of time following a sharp decline in stock prices, in hopes of stabilizing the market and preventing it from falling further.
Since the crashes of 1929 and 1987, safeguards have been put in place to prevent crashes due to panicked stockholders selling their assets. Such safeguards include trading curbs, or circuit breakers, which prevent any trade activity whatsoever for a certain period of time following a sharp decline in stock prices, in hopes of stabilizing the market and preventing it from falling further.
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]
In 1907 and in 1908, the NYSE fell by nearly 50% due to a variety of factors, led by the manipulation of copper stocks by the Knickerbocker company.[21] Shares of United Copper rose gradually up to October, and thereafter crashed, leading to panic.[22][23] A number of investment trusts and banks that had invested their money in the stock market fell and started to close down. Further bank runs were prevented due to the intervention of J. P. Morgan.[24] The panic continued to 1908 and led to the formation of the Federal Reserve in 1913.[25]

Can the FDIC Run out of Money?


Investing in the stock market is inherently risky, but what makes for winning long-term returns is the ability to ride out the unpleasantness and remain invested for the eventual recovery (which, historically speaking, is always on the horizon). You’ll be able to do that if you know how much volatility you’re willing to stomach in exchange for higher potential returns.
For example, the United States has a set of thresholds in place to guard against crashes. If the Dow Jones Industrial Average (DJIA) falls 2,400 points (threshold 2) before 1:00 p.m., the market will be frozen for an hour. If it falls below 3,600 points (threshold 3), the market closes for the day. Other countries have similar measures in place. The problem with this method today is that if one stock exchange closes, shares can often still be bought or sold in other exchanges, which can cause the preventative measures to backfire.

What Is the Largest Single Day Drop of Dow?


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Since the crashes of 1929 and 1987, safeguards have been put in place to prevent crashes due to panicked stockholders selling their assets. Such safeguards include trading curbs, or circuit breakers, which prevent any trade activity whatsoever for a certain period of time following a sharp decline in stock prices, in hopes of stabilizing the market and preventing it from falling further.
On Black Monday, the Dow Jones Industrial Average fell 38.33 points to 260, a drop of 12.8%. The deluge of selling overwhelmed the ticker tape system that normally gave investors the current prices of their shares. Telephone lines and telegraphs were clogged and were unable to cope. This information vacuum only led to more fear and panic. The technology of the New Era, previously much celebrated by investors, now served to deepen their suffering.
No definitive conclusions have been reached on the reasons behind the 1987 Crash. Stocks had been in a multi-year bull run and market P/E ratios in the U.S. were above the post-war average. The S&P 500 was trading at 23 times earnings, a postwar high and well above the average of 14.5 times earnings.[29] Herd behavior and psychological feedback loops play a critical part in all stock market crashes but analysts have also tried to look for external triggering events. Aside from the general worries of stock market overvaluation, blame for the collapse has been apportioned to such factors as program trading, portfolio insurance and derivatives, and prior news of worsening economic indicators (i.e. a large U.S. merchandise trade deficit and a falling U.S. dollar, which seemed to imply future interest rate hikes).[30]

How Long Did the Stock Market Crash of 1987 Last?


The following day, Black Tuesday, was a day of chaos. Forced to liquidate their stocks because of margin calls, overextended investors flooded the exchange with sell orders. The Dow fell 30.57 points to close at 230.07 on that day. The glamour stocks of the age saw their values plummet. Across the two days, the Dow Jones Industrial Average fell 23%.
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