Secrets of the Stock Market's Biggest Winners
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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.

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.
The economy had been growing for most of the Roaring Twenties. It was a technological golden age, as innovations such as the radio, automobile, aviation, telephone, and the power grid were deployed and adopted. Companies that had pioneered these advances, like Radio Corporation of America (RCA) and General Motors, saw their stocks soar. Financial corporations also did well, as Wall Street bankers floated mutual fund companies (then known as investment trusts) like the Goldman Sachs Trading Corporation. Investors were infatuated with the returns available in the stock market, especially by the use of leverage through margin debt.

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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.

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]

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Thirty-two percent of Americans who were invested in the stock market during at least one of the last five financial downturns pulled some or all of their money out of the market. That’s according to a NerdWallet-commissioned survey, which was conducted online by The Harris Poll of more than 2,000 U.S. adults, among whom over 700 were invested in the stock market during at least one of the past five financial downturns, in June 2018. The survey also found that 28% of Americans would not keep their money in the stock market if there were a crash today.

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.

What Caused Stock Market Crash?


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.
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]
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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