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. Among others, mathematician Benoît Mandelbrot suggested as early as 1963 that the statistics prove this assumption incorrect. 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. 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. George Soros said in late October 1987, 'Mr. Robert Prechter's reversal proved to be the crack that started the avalanche'.
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.)
Despite fears of a repeat of the 1930s Depression, the market rallied immediately after the crash, posting a record one-day gain of 102.27 the very next day and 186.64 points on Thursday October 22. It took only two years for the Dow to recover completely; by September 1989, the market had regained all of the value it had lost in the 1987 crash. The Dow Jones Industrial Average gained six-tenths of a percent during the calendar year 1987.
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.
Which Degree Is Best for Stock Market?
The crash on October 19, 1987, a date that is also known as Black Monday, was the climactic culmination of a market decline that had begun five days before on October 14. The DJIA fell 3.81 percent on October 14, followed by another 4.60 percent drop on Friday, October 16. On Black Monday, the Dow Jones Industrials Average plummeted 508 points, losing 22.6% of its value in one day. The S&P 500 dropped 20.4%, falling from 282.7 to 225.06. The NASDAQ Composite lost only 11.3%, not because of restraint on the part of sellers, but because the NASDAQ market system failed. Deluged with sell orders, many stocks on the NYSE faced trading halts and delays. Of the 2,257 NYSE-listed stocks, there were 195 trading delays and halts during the day. The NASDAQ market fared much worse. Because of its reliance on a "market making" system that allowed market makers to withdraw from trading, liquidity in NASDAQ stocks dried up. Trading in many stocks encountered a pathological condition where the bid price for a stock exceeded the ask price. These "locked" conditions severely curtailed trading. On October 19, trading in Microsoft shares on the NASDAQ lasted a total of 54 minutes.
Why Was 1933 the Worst Year of the Depression?
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. 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).
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.