Secrets of the Stock Market's Biggest Winners
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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.
What about corporate America? According to a New York Times survey of business leaders, almost half of the respondents believe that the U.S. could face a recession by the end of 2019. And if not in 2019, then in 2020. (Source: “A jarring new survey shows CEOs think a recession could strike as soon as year-end 2019,” Business Insider, December 17, 2018.)
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.

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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]

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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%.
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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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.
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