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Stock market crash

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A stock market crash is a sudden dramatic decline of stock prices across a significant cross-section of a stock market, resulting in a significant loss of paper wealth. Crashes are driven by panic as much as by underlying economic factors. They often follow speculative stock market bubbles.

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 exceed long-term averages, and extensive use of margin debt and leverage by market participants.

There is no numerically specific definition of a stock market crash but the term commonly applies to steep double-digit percentage losses in a stock market index over a period of several days. Crashes are often distinguished from bear markets by panic selling and abrupt, dramatic price declines. Bear markets are periods of declining stock market prices that are measured in months or years. While crashes are often associated with bear markets, they do not necessarily go hand in hand. The crash of 1987, for example, did not lead to a bear market. Likewise, the Japanese Nikkei bear market of the 1990s occurred over several years without any notable crashes.

Wall Street Crash of 1929

Main article: Wall Street Crash of 1929
Crowd gathering on Wall Street after the 1929 crash.

The economy had been growing robustly for most of the Roaring Twenties. It was a technological golden age as innovations such as radio, automobiles, 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 with the use of leverage through margin debt.

On August 24, 1921, the Dow Jones Industrial Average stood at a value of 63.9. By September 3, 1929, it had risen more than sixfold, touching 381.2. It would not regain this level for another twenty-five years. By the summer of 1929, it was clear that the economy was contracting and the stock market went through a series of unsettling price declines. These declines fed investor anxiety and events soon came to a head on October 24 (known as Black Thursday) and October 29 (known as Black Tuesday).

On Black Tuesday, the Dow Jones Industrial Average fell 38 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, much celebrated by investors previously, now served to deepen their suffering.

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 glamour stocks of the age saw their values plummet. Across the two days, the Dow Jones Industrial Average fell 23%.

By the end of the weekend of November 11, the index stood at 228, a cumulative drop of 40 percent from the September high. The markets rallied in succeeding months but it would be a false recovery that led unsuspecting investors into further losses. The Dow Jones Industrial Average would lose 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.

Trading curbs

Main article: Trading curb

Trading curbs, also known as "circuit breakers", are a trading halt in the cash market and the corresponding trading halt in the derivative markets triggered by the halt in the cash market, all of which are affected based on substantial movements in a broad market indicator.[2]

United States

There are three thresholds each of which represents different level of decline in terms of points in Dow Jones industrial average.

  • In the event where threshold 1 is breached, the first halt is triggered. If that point is reached before 2 p.m., the market would shut down for an hour. If threshold 1 is breached between 2 p.m. and 2:30 p.m., the halt will last 30 minutes. No trading stops will take place if threshold 1 is breached after 2:30 p.m.
  • If threshold 2 is breached before 1 p.m., the market would close for two hours. If such a decline took place between 1 p.m. and 2 p.m., there would be a one-hour pause. The market would close for the day if stocks sank to that level after 2 p.m.
  • In the event where threshold 3 is breached, the market would close for the day, regardless of the time.

The thresholds are computed at the beginning of each quarter to establish a specific point value for the quarter.

For the second quarter of 2011, threshold 1 is 1200 points, threshold 2 is 2400 points, and threshold 3 is 3600 points.[3]

The rules would halt trading on the major securities and futures exchanges in a coordinated cross-market halt if the circuit breaker is enacted.[4]

France

In France, daily price limits are implemented in cash and derivative markets. Securities traded on the markets are divided into three categories according to the number and volume of daily transactions and price limits vary depending on the category to which the security belongs. For instance, for the more liquid category, when the price movement of a security exceeds 10% from the quoted price at the close of the previous market day, quotation is suspended for 15 minutes. After 15 minutes, transactions are resumed. If the price then goes up or down by more than 5%, transactions are again suspended for 15 minutes. The 5% threshold may apply once more before transactions are halted for the rest of the day. When transactions are suspended in the cash market on a given security, due to undue price movement, transactions on the option based on the underlying security are also suspended. Further, when more than 35% of the capitalization of the CAC­40 Index is unable to be quoted, the calculation of the CAC­40 Index is suspended and the index is replaced by a trend indicator. When less than 25% of the capitalization of the CAC­40 Index is able to be quoted, quotations on the derivative markets are suspended for half an hour or one hour when additional margin deposits are requested.[2]

Mathematical theory and stock market crashes

The mathematical characterisation of stock market movements has been a subject of intense interest. The conventional assumption has been that stock markets behave according to a random Gaussian or "normal" distribution.[5][6] Among others, mathematician Benoît Mandelbrot suggested as early as 1963 that the statistics prove this assumption incorrect.[7] Mandelbrot observed that large movements in prices (i.e. crashes) are much more common than would be predicted in a normal distribution. Mandelbrot and others suggest that the nature of market moves is generally much better explained using non-linear analysis and concepts of chaos theory.[8] 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.[9] George Soros said in late October 1987, 'Mr. Robert Prechter's reversal proved to be the crack that started the avalanche'.[10][11]

Research at the Massachusetts Institute of Technology suggests that there is evidence the frequency of stock market crashes follows an inverse cubic power law.[12] 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.[13] In 1963, Mandelbrot proposed that instead of following a strict random walk, stock price variations executed a Lévy flight.[14] 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.[15] Researchers continue to study this theory, particularly using computer simulation of crowd behaviour, and the applicability of models to reproduce crash-like phenomena.

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.[16][17]

The study Switching processes in financial markets published in the Proceedings of the National Academy of Sciences reveals a general empirical law quantifying market behavior near bubbles and crashes.[18][19]

The Hindenburg Omen, developed by physics professor Jim Miekka, is a controversial indicator that is believed by many to predict stock market crashes.

A recent phenomenon, known as the RR Reversal, has also been well documented in recent years - where a rapidly increasing stock experiences an inexplicable and sudden pullback to the magnitude of 10 - 40% within a month.

See also

Examples

References

  1. ^ Galbraith, J. The Great Crash 1929, 1988 edition, Houghton Mifflin Co. Boston, p.xii-xvii
  2. ^ a b Riskinstitute.ch
  3. ^ NYSE.com
  4. ^ IHT.com
  5. ^ Malkiel, Burton G. (1973). A Random Walk Down Wall Street (6th ed.). W.W. Norton & Company, Inc. ISBN 0393062457.
  6. ^ Fama, Eugene F. (1965). "Random Walks In Stock Market Prices". Financial Analysts Journal. 21 (5): 55–59. doi:10.2469/faj.v21.n5.55. Retrieved 2008-03-21. {{cite journal}}: Unknown parameter |month= ignored (help)
  7. ^ The (Mis-)Behavior Of Markets
  8. ^ 'Father of Fractals' takes on the stock market
  9. ^ Soros, G. Alchemy of Finance, Wiley Investment Classics. 2003
  10. ^ Marketwatch.com
  11. ^ Thomas Jr, Landon (October 13, 2007). "The Man Who Won as Others Lost". The New York Times. Retrieved May 24, 2010.
  12. ^ Stock trade patterns could predict financial earthquakes
  13. ^ Didier Sornette, Professor of Geophysics
  14. ^ The variation of certain speculative prices
  15. ^ Scaling behaviour in the dynamics of an economic precursors and replicas." Journal de Physique I France 6, No.1, pp. 167–175.
  16. ^ Predicting economic market crises using measures of collective panic arXiv:1102.2620v1 [q-fin.ST]
  17. ^ Possible Early Warning Sign for Market Crashes
  18. ^ Switching processes in financial markets
  19. ^ Blueprint of a trend: How does a financial bubble burst?

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<Aharon, D.Y., I. Gavious and R. Yosef, 2010. Stock market bubble effects on mergers and acquisitions. The Quarterly Review of Economics and Finance, 50(4): p. 456-470. >

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