Foreign exchange market

he foreign exchange market (currency, forex, or FX) trades currencies. It lets banks and other institutions easily buy and sell currencies. The purpose of the foreign exchange market is to help international trade and investment. A foreign exchange market helps businesses convert one currency to another. For example, it permits a U.S. business to import European goods and pay Euros, even though the business's income is in U.S. dollar

stack exchanges of world

Stock market downturn of 2002

The stock market downturn of 2002 (some say "stock market crash" or "the Internet bubble bursting") is the sharp drop in stock prices during 2002 in stock exchanges across the United States, Canada, Asia, and Europe. After recovering from lows reached following the September 11, 2001 attacks, indices slid steadily starting in March 2002, with dramatic declines in July and September leading to lows last reached in 1997 and 1998. The dollar declined steadily against the euro, reaching a 1-to-1 valuation not seen since the euro's introduction.

Chinese correction

The Chinese Correction was the global stock market plunge of February 27, 2007 which wiped out hundreds of billions of market value. After rumors that governmental Chinese economic authorities were going to raise interest rates in an attempt to curb inflation and that they planned to clamp down on speculative trading with borrowed money, the SSE Composite Index of the Shanghai Stock Exchange tumbled 9%, the largest drop in 10 years.

The plunge in Asian markets sent ripples through the global market as the world reacted to the 9% meltdown in the Chinese stock market. The Chinese Correction triggered drops and major unease in nearly all financial markets around the world.

After the Chinese market drop, the Dow Jones Industrial Average in the United States dropped 416 points, or 3.29% from 12,632 to 12,216 amid fears for growth prospects, then the biggest one-day slide since the September 11, 2001 terrorist attacks. The S&P 500 saw a comparable 3.45% slide. Sell orders were made so fast that a second analysis computer had to be used, causing an instantaneous 200 point drop at one point in the Dow Industrials.

Every Generation Has Its Crash

From financing the War of 1812 to today's internet and biotechnology companies, Wall Street has played a very significant role in both the American economy and its welfare. In the 19th and early 20th century, the American economy would go through repetitive periods of boom and bust, and on numerous occasions, specific names on Wall Street would be actively involved. Figures such as Cornelius Vanderbilt, Daniel Drew, Jay Gould, J.P. and Jack Morgan in their heydays controlled vast economic fortunes, and with the touch of a hand, could bring Wall Street to its knees.

The gold corner of 1869 was such an example. With the aid of Jim Fisk and Daniel Drew, Jay Gould decided to corner the gold market of the United States. There was only one problem. The U.S. Treasury had approximately $100 million worth of gold secured at Fort Knox, and any attempt to corner the gold market would require the Treasury to stay away. Gould's vast political connections (one of whom was the President, Ulysses Grant) ensured that. By the time they had accumulated all the gold they had intended to (Gould alone bought $7 million), the premium on gold was 160%. This forced the short-sellers to cover, which stabilized the price of gold at about that price. Gould sold all his holdings at the top of the market and made a profit of $10 million. The Treasury did not intervene until several days later, and the fallout was great. Several firms on Wall Street failed, and the stock market collapsed as a result -- which in turn caused numerous brokerage firms to fail.

The panic of 1907 brought out a single savior -- not the Treasury, nor the Federal Reserve (which did not exist then), but J.P. Morgan. The stock market had a very high valuation going into 1907. From March to October, the stock market fell continuously, and in late October, the impending failure of the Knickerbocker Trust Company caused a run on its already depleted funds. The company was left to fail, but Morgan, along with other well-known bankers, provided the funds necessary (>$25 million) to prop up the other major trust institutions. At the same time, the Treasury was propping up the stock market with its own funds. When they ran out, they had to ask Morgan for help. Morgan provided a further $25 million. Without his aid, the NYSE would have to shut down.

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.[23][24] 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 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. 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.

Research at the Massachusetts Institute of Technology suggests that there is evidence the frequency of stock market crashes follows an inverse cubic power law.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. In 1963, Mandelbrot proposed that instead of following a strict random walk, stock price variations executed a Lévy flight. 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.Their conclusion was that stock market returns are more volatile than a Gaussian distribution but less volatile than a Lévy flight.

Researchers continue to study this theory, particularly using computer simulation of crowd behaviour, and the applicability of models to reproduce crash-like phenomena.