Secrets of the Stock Market's Biggest Winners
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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%.
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]
From October 6–10 the Dow Jones Industrial Average (DJIA) closed lower in all five sessions. Volume levels were record-breaking. The DJIA fell over 1,874 points, or 18%, in its worst weekly decline ever on both a points and percentage basis. The S&P 500 fell more than 20%.[36] The week also set 3 top ten NYSE Group Volume Records with October 8 at #5, October 9 at #10, and October 10 at #1.[37]

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.
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.

What Causes a Stock Market Crash?


The Times of London reported that the meltdown was being called the Crash of 2008, and older traders were comparing it with Black Monday in 1987. The fall that week of 21% compared to a 28.3% fall 21 years earlier, but some traders were saying it was worse. "At least then it was a short, sharp, shock on one day. This has been relentless all week."[34] Business Week also referred to the crisis as a "stock market crash" or the "Panic of 2008".[35]
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.
By the end of the weekend of November 11, the index stood at 228, a cumulative drop of 40% from the September high. The markets rallied in succeeding months, but it was a temporary recovery that led unsuspecting investors into further losses. The Dow Jones Industrial Average lost 89% of its value before finally bottoming out in July 1932. The crash was followed by the Great Depression, the worst economic crisis of modern times, which plagued the stock market and Wall Street throughout the 1930s.

What Is Its Black Fridays Real Name?


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.
Consider hiring a fee-only financial advisor to kick the tires on your portfolio and provide an independent perspective on your financial plan. In fact, it’s not uncommon for financial planners to have their own financial planner on their personal payroll for the same reason. An added bonus is knowing there’s someone to call to talk you through the tough times.
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What Caused Black Friday?


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.)
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.
By the end of the weekend of November 11, the index stood at 228, a cumulative drop of 40% from the September high. The markets rallied in succeeding months, but it was a temporary recovery that led unsuspecting investors into further losses. The Dow Jones Industrial Average lost 89% of its value before finally bottoming out in July 1932. The crash was followed by the Great Depression, the worst economic crisis of modern times, which plagued the stock market and Wall Street throughout the 1930s.
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.

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.
Meanwhile, those who are most concerned with corporate coffers, the chief financial officers (CFOs), are the least optimistic about the U.S. economy and, by extension, the stock market. Almost half (48.6%) of CFOs surveyed believe that the U.S. will fall into a recession in 2019, and a whopping 82% of them believe that a recession will occur in 2020. (Source: “Recession Considered Likely By Year-End 2019,” Duke CFO Global Business Outlook, last accessed March 14, 2019.)

Research at the New England Complex Systems Institute has found warning signs of crashes using new statistical analysis tools of complexity theory. This work suggests that the panics that lead to crashes come from increased mimicry in the market. A dramatic increase in market mimicry occurred during the whole year before each market crash of the past 25 years, including the recent financial crisis. When investors closely follow each other's cues, it is easier for panic to take hold and affect the market. This work is a mathematical demonstration of a significant advance warning sign of impending market crashes.[19][20]
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