Secrets of the Stock Market's Biggest Winners
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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.
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.
The crash followed an asset bubble. Since 1922, the stock market had gone up by almost 20 percent a year. Everyone invested, thanks to a financial invention called buying "on margin." It allowed people to borrow money from their broker to buy stocks. They only needed to put down 10-20 percent. Investing this way contributed to the irrational exuberance of the Roaring Twenties.
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?


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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.

Who Is to Blame for the Great Depression?


The mid-1980s were a time of strong economic optimism. From August 1982 to its peak in August 1987, the Dow Jones Industrial Average (DJIA) grew from 776 to 2722. The rise in market indices for the 19 largest markets in the world averaged 296 percent during this period. The average number of shares traded on the NYSE(New York Stock Exchange) had risen from 65 million shares to 181 million shares.[26]

Is Buying on Margin a Good Idea?


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]

What Happened in the Year 1929?


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.
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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