Stock markets

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Posted by bender 02/27/2009 @ 19:02

Tags : stock markets, markets, finance

News headlines
Surprise drop in housing data checks market's rise - The Associated Press
About three stocks rose for every two that fell on the New York Stock Exchange, where volume came to 1.35 billion shares. In a positive sign for Wall Street, one measure of the market's uneasiness fell again after sliding 8.7 percent Monday....
Exchange-Traded Funds Offer Passage to India - Wall Street Journal
By JOHN SPENCE Investors looking to grab a piece of the action in India's stock market may want to think about exchange-traded funds and notes. The Indian stock market surged 17% Monday after the Congress party scored a victory in the general election,...
India stock markets to resume trade at 0625 GMT - Reuters
NEW DELHI, May 18 (Reuters) - Trade on India's Bombay Stock Exchange and National Stock Exchange will resume at 11:55 am (0625 GMT), officials said, after a two-hour halt was triggered by sharp opening rises following a sweeping election victory for...
Asian markets trade firm on Wall Street cues, easing concerns over ... - RTT News
(RTTNews) - Asian markets are trading with strong gains on Tuesday, with participants picking up stocks on positive cues from Wall Street and on hopes of a global economic recovery. The splendid surge in the Indian stock market on Monday following the...
Don't Get Euphoric About a Falling VIX - Barron's
The fear gauge, as the Chicago Board Options Exchange's Market Volatility Index (VIX) is known on Wall Street, is hovering at a critical level that could indicate increased investor confidence about the stock market. VIX was recently at about 29.34....
Och Stores Up Cash as Funds Brace for Stock Losses - Bloomberg
By Katherine Burton and Saijel Kishan May 19 (Bloomberg) -- Daniel Och had about 35 percent of his $20 billion of hedge-fund assets in cash during the first quarter because he suspects global stock markets will start falling again....
Hong Kong leads the pack in Asian stock market surge - Malaysia Star
Such was the investors' voracious appetite for Asian equities it was only matched by the intensity of the sell-off on the region's stock markets last year. But while the run-up over the past two months had made share prices neither cheap nor expensive...
US gold falls on stop-loss orders, stock gains - Reuters
Lower oil prices combined with deflationary forces should present headwind to further gains in gold, following recent rise on safe-haven buying and weaker stock markets - James Steel, chief commodities analyst at HSBC. * Diminished risk appetite and...
Dow posts biggest point gain in over a month - San Jose Mercury News
By Sara Lepro and Tim Paradis AP NEW YORK — Reassuring news about housing and banking on Monday persuaded investors to return to the stock market. The Dow Jones industrial average shot up 235 points, making up three-quarters of last week's losses....
TREASURIES-Some narrow losses as safety bid ebbs - Reuters
"There's real confusion about whether the stock market's gains over the last two months constitute a bear market bounce or not." Stiles said the "groupthink" on the stock market's advance since March 9 was that the gains added up to a bounce for a...

Stock market bubble

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A stock market bubble is a type of economic bubble taking place in stock markets when price of stocks rise and become overvalued by any measure of stock valuation.

The existence of stock market bubbles is at odds with the assumptions of efficient market theory which assumes rational investor behaviour. Behavioral finance theory attribute stock market bubbles to cognitive biases that lead to groupthink and herd behavior. Bubbles occur not only in real-world markets, with their inherent uncertainty and noise, but also in highly predictable experimental markets. In the laboratory, uncertainty is eliminated and calculating the expected returns should be a simple mathematical exercise, because participants are endowed with assets that are defined to have a finite lifespan and a known probability distribution of dividends. Other theoretical explanations of stock market bubbles have suggested that they are rational, intrinsic, and contagious.

The two most famous bubbles of the twentieth century, the bubble in American stocks in the 1920s and the Dot-com bubble of the late 1990s were based on speculative activity surrounding the development of new technologies. The 1920s saw the widespread introduction of an amazing range of technological innovations including radio, automobiles, aviation and the deployment of electrical power grids. The 1990s was the decade when Internet and e-commerce technologies emerged.

Other stock market bubbles of note include the Nifty Fifty stocks in the early 1970s, Taiwanese stocks in 1987 and Japanese stocks in the late 1980s.

Stock market bubbles frequently produce hot markets in Initial Public Offerings, since investment bankers and their clients see opportunities to float new stock issues at inflated prices. These hot IPO markets misallocate investment funds to areas dictated by speculative trends, rather than to enterprises generating longstanding economic value.

Emotional and cognitive biases (see behavioral finance) seem to be the causes of bubbles. But, often, when the phenomenon appears, pundits try to find a rationale, so as not to be against the crowd. Thus, sometimes, people will dismiss concerns about overpriced markets by citing a new economy where the old stock valuation rules may no longer apply. This type of thinking helps to further propagate the bubble whereby everyone is investing with the intent of finding a greater fool. Still, some analysts cite the wisdom of crowds and say that price movements really do reflect rational expectations of fundamental returns. Large traders become powerful enough to rock the boat, generate stock market bubbles.

To sort out the competing claims between behavioral finance and efficient markets theorists, observers need to find bubbles that occur when a readily-available measure of fundamental value is also observable. The bubble in closed-end country funds in the late 1980s is instructive here, as are the bubbles that occur in experimental asset markets. For closed-end country funds, observers can compare the stock prices to the net asset value per share (the net value of the fund's total holdings divided by the number of shares outstanding). For experimental asset markets, observers can compare the stock prices to the expected returns from holding the stock (which the experimenter determines and communicates to the traders).

In both instances, closed-end country funds and experimental markets, stock prices clearly diverge from fundamental values. Nobel laureate Dr. Vernon Smith has illustrated the closed-end country fund phenomenon with a chart showing prices and net asset values of the Spain Fund in 1989 and 1990 in his work on price bubbles. At its peak, the Spain Fund traded near $35, nearly triple its Net Asset Value of about $12 per share. At the same time the Spain Fund and other closed-end country funds were trading at very substantial premiums, the number of closed-end country funds available exploded thanks to many issuers creating new country funds and selling the IPOs at high premiums.

It only took a few months for the premiums in closed-end country funds to fade back to the more typical discounts at which closed-end funds trade. Those who had bought them at premiums had run out of "greater fools". For a while, though, the supply of "greater fools" had been outstanding.

A rising price on any share will attract the attention of investors. Not all of those investors are willing or interested in studying the intrinsics of the share and for such people the rising price itself is reason enough to invest. In turn, the additional investment will provide buoyancy to the price, thus completing a positive feedback loop.

Like all dynamical systems, financial markets operate in an ever changing equilibrium, which translates into price volatility. However instable is this balance, a self-adjustment (negative feedback) takes place normally: when prices rise more people are encouraged to sell, while fewer are encouraged to buy. This puts a limit on volatility. However, once positive feedback takes over, the market, like all systems with positive feedback, enters a state of increasing disequilibrium. This can be seen in financial bubbles where asset prices rapidly spike upwards far beyond what could be considered the rational "economic value", only to fall rapidly afterwards.

Investment managers, such as stock mutual fund managers, are compensated and retained in part due to their performance relative to peers. Taking a conservative or contrarian position as a bubble builds results in performance unfavorable to peers. This may cause customers to go elsewhere and can affect the investment manager's own employment or compensation. The typical short-term focus of U.S. equity markets exacerbates the risk for investment managers that do not participate during the building phase of a bubble, particularly one that builds over a longer period of time. In attempting to maximize returns for clients and maintain their employment, they may rationally participate in a bubble they believe to be forming, as the risks of not doing so outweigh the benefits.

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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.

This downturn can be viewed as part of a larger bear market or correction, after a decade-long bull market had led to unusually high stock valuations. In fact, some Internet companies (Webvan, Exodus Communications, and Pets.com) went bankrupt. Others (Amazon.com, eBay, and Yahoo!) went down dramatically in value, but remain in business to this day and have generally good long term growth prospects. An outbreak of accounting scandals (Enron, Arthur Andersen, Adelphia, and WorldCom) was also a factor in the speed of the fall, as numerous large corporations were forced to restate earnings (or lack thereof) and investor confidence suffered. The September 11 attacks also contributed heavily to the stock market downturn, as investors became unsure about the prospect of terrorism affecting the United States economy.

The International Monetary Fund had expressed concern about instability in United States stock markets in the months leading up to the sharp downturn. The technology-heavy NASDAQ stock market peaked on March 10, 2000, hitting an intra-day high of 5,132.52 and closing at 5,048.62. The Dow Jones Industrial Average, a price-weighted average (adjusted for splits and dividends) of 30 large companies on the New York Stock Exchange, peaked on January 14, 2000 with an intra-day high of 11,750.28 and a closing price of 11,722.98. In 2001, the DJIA was largely unchanged overall but had reached a secondary peak of 11,337.92 (11,350.05 intra-day) on May 21.

The downturn may be viewed as a reversion to average stock market performance in a longer-term context. From 1987 to 1995, the Dow rose each year by about 10%, but from 1995 to 2000, the Dow rose 15% a year. While the bear market began in 2000, by July and August 2002, the index had only dropped to the same level it would have achieved if the 10% annual growth rate followed during 1987-1995 had continued up to 2002.

After falling for 11 of 12 consecutive days closing below Dow 8000 on July 23, 2002, the market rallied. The Dow rose 13% over the next four trading days, but then fell sharply again in early August. On August 5, the NASDAQ fell below its July 23 low. However, the markets rose sharply over the rest of the week, and eventually surpassed Dow 9000 during several trading sessions in late August. After that, the Dow dropped to a four-year low on September 24, 2002, while the NASDAQ reached a 6-year low. The markets continued their declines, breaking the September low to five-year lows on October 7 and reaching a bottom (below Dow 7200 and just above 1100 on the NASDAQ) on October 9. Stocks recovered slightly from their October lows to year-end, with the Dow remaining in the mid-8000s from November 2002 to mid-January 2003. The markets reached a final low below Dow 7500 in mid-March 2003.

As of September 24, 2002, the Dow Jones Industrial Average had lost 27% of the value it held on January 1, 2001: a total loss of 5 trillion dollars. It should be noted that the Dow Jones had already lost 9% of its peak value at the start of 2001, while the Nasdaq had lost 44%. At the March 2000 top, the sum in valuation of all NYSE-listed companies stood at $12.9 trillion, and the valuation sum of all NASDAQ-listed companies stood at $5.4 trillion, for a total market value of $18.3 trillion. The NASDAQ subsequently lost nearly 80% and the S&P 500 lost 50% to reach the October 2002 lows. The total market value of NYSE (7.2) and NASDAQ (1.8) companies at that time was only $9 trillion, for an overall market loss of $9.3 trillion.

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Stock market simulator

A stock market simulator is a program or application that attempts to reproduce or duplicate some or all features of a live stock market on a computer so that a player may practice trading stocks without financial risk.

Stock market simulators can be broken down into two major categories - financial market simulators, and fantasy simulators.

Financial market simulators allow users to generate a portfolio based on real stock entries, but with fantasy money. Most of the currently active financial simulators use a delayed data feed of between 15 and 20 minutes to ensure that users cannot use their data to trade actively on a competing system. The purpose behind such a system is to let a person practice with fantasy funds in a real-world context so they can determine whether or not they would gain money investing by themselves.

Fantasy simulators trade shares or derivatives of real world items or objects that normally would not be listed on a commodities or market exchange, such as movies or television shows. Some simulators focus on sports and have been linked to active betting and wager based systems.

Most of the online stock simulators run on either Java, JavaScript, ASP or php with a mysql database. Some of them are open source, and others are proprietary with the code being sold as valuable prediction market software. Such is the example with the HSX Virtual Specialist. This technology has been sold to major film studios such as MGM and Lion's Gate Films, as well as to the Popular Science team for use in their PPX system.

Stock Market simulator engines can also be customized for other functions than just basic stock information tracking. The HSX engine has been modified to track popular science trends and also to track Youtube videos. Other applications that can be implemented with this software include popularity tracking and ranking from a set scale rather than an actual numerical value.

Stock market games are speculative games that allows players to trade stocks in a virtual or simulated stock market.

Stock market games exist in several forms but the basic underlying concept is that these games allow players to gain experience or just entertainment by trading stocks in a virtual world where there is no real risk. Some stock market games do not involve real money in any way. Players compete with each other to see who can predict the direction the stock markets will go next. Many stock market games are based on real life stocks from the Nasdaq, NYSE or other major market indexes.

Stock market games are often used for educational purposes to teach potential stock traders and future stock brokers how to trade stocks. A stock market game is a perfect way to learn how to trade stocks without the risk of losing real money. According to Global Stock Game, over 15,000 schools have used their stock simulation game to teach students.

Some Stock market games are not based on financial markets at all. These virtual stock markets are often based on things like sports or entertainment 'stocks'. Players are asked to invest in a particular sports team for example.If the team is doing well, the stock goes up and if the team is playing badly the stock value for that team falls. Stock market games are often built in to many other prediction games.

A video stock exchange is a predictive market which predicts the popularity of user generated video content. The exchange is modelled after real life stock markets. Real life company stocks are valued based upon predictions of future company earnings, while videostocks are valued based upon predictions of a video's future viewings.

The Videostocks are IPOed onto the site by traders and an initial IPO stock value is assigned by the automated market maker. The traders then buy and sell the stock according to the traders opinion of its future payout. Videostocks delist and payout videodollars to all share owners after a predefined short period of time. For example, a period of one week could be used as the basis for a stocks value with the payout being one videodollar for each 1000 views achieved on the video sharing site.

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Election stock market

Election stock markets (also referred to as election prediction markets) are financial markets in which the ultimate values of the contracts being traded are based on the outcome of elections. Participants invest their own funds, buy and sell listed contracts, earn profits and bear the risk of losing money. Election stock markets function like other futures exchanges, such as commodity exchanges for the future delivery of grain, livestock, or precious metals.

The main purpose of an election stock market is to predict the election outcome, such as the share of the popular vote or share of seats each political party receives in a legislature or parliament. Efficient markets are very good at reflecting all available information, often reflecting information faster than opinion polls, which take several days to complete and process. Traders also have a strong financial incentive to reflect their true opinion about the election outcome regardless of their political preferences.

Election stock markets are also used for research and teaching purposes. Researchers can study trader behavior and market operations. Election stock markets also teach participants the fundamentals of trading, such as how to take a long or a short position. A list of related academic research papers appears below.

In North America, two universities have been operating election stock markets for over a decade. The University of Iowa's Tippie College of Business has been operating the Iowa Electronic Markets . The Iowa markets primarily track presidential and congressional elections. In Canada, the University of British Columbia's Sauder School of Business has been operating the UBC Election Stock Market. The UBC markets track federal and provincial elections in Canada. The Iowa and UBC markets are non-profit operations for research purposes. These markets do not charge commissions or transaction fees. Investments are typically limited to USD 500 or CAD 1,000.

Privately run prediction markets have also emerged in recent years. Unlike their university counterparts, commercial prediction markets charge fees or commissions to cover their operating costs. Commercial markets may charge fees per transaction or commissions on net profits, and fees per transaction may be differentiated for price takers (those placing a market order) and price makers (those placing a limit order). Examples of commercial prediction markets include Intrade Prediction Markets and The Washington Stock Exchange; both track predictions for a a broad set of political events. Focusing more on sports events than politics, Tradesports also offers futures contracts for political events. Commercial prediction markets claim that they attract more investment and generate more trading volume than their academic counterparts as they don't limit a trader's capital investment. The prediction accuracy of commercial and academic election stock markets is an area of active research (see below).

Election stock markets typically cover the popular vote share of political parties or the seats share of political parties in a parliament. The seats distribution depends on the electoral system (such as first-past-the-post or proportional representation) that is used for the particular election. Predictions of seats distributions are therefore often more challenging than predictions of vote shares. The ultimate payoff in a votes share or seats share market is determined by the actual distribution of votes and seats as determined by the election. For example, if the Blue Party wins 32.3% of the popular vote, than the corresponding contract in the popular vote market would pay out 32.3 cents.

Election stock markets may also offer winner-take-all markets. In such markets only one contract will pay $1, and all other contracts pay $0. Winner-take-all markets are commonly used to predict outcomes such as the winner of a presidential election or the formation of a majority government by a particular party. Such markets may also be used to predict the outcome of a referendum.

Traders buy and sell contracts, which are typically quoted in 1/10-th of a cent corresponding to 1/10-th of a percentage point for the votes share or seats share of a political party. Traders make profits by buying undervalued contracts and selling overvalued contracts. If a trader expects the Blue Party to win 42.3% of the popular vote, the trader will find it profitable to buy a contract of the Blue Party if a seller offers it for less than 42.3 cents. The same trader will find it profitable to sell the same contract if another trader is willing to buy it for more than 42.3 cents.

A trader takes a long position by buying low and selling high. Consider an investor who considers the purchase of a contract in the Blue Party, which is currently offered for 39.3 cents in the market. The investor predicts that the Blue Party will win more than 41%, and buys a contract of the Blue Party for 39.3 cents. On election day the Blue Party wins 42.5% of the popular vote, and the trader realizes a profit of 3.2 cents, an 8.1% return on investment.

Contracts are put into circulation through the purchase of a unit portfolio. A trader purchases a set of all contracts in a particular market worth $1. Consider an election in which three parties compete, a Red Party, a Blue Party, and a Green Party. The share of popular votes for each party must sum to 100% by definition, so holding on to one contract for each of the three parties will always be worth $1 no matter what the election outcome. Buying unit portfolios allows trader to take a short position by selling contracts that they think are overvalued.

Consider a trader who has bought a unit portfolio consisting of one contract each for the Red Party, the Blue Party, and the Green Party, at a cost of $1. Believing that the contract for the Blue Party is overvalued at its current price, the trader sells one contract of the Blue Party for 30 cents. On election day the Red Party wins 55% of the vote, the Blue Party wins 25% of the vote, and the Green Party wins 20%. The trader now receives 75 cents in total for the Red Party and Green Party contracts, and has an additional 30 cents from the sale of the Blue Party contract. The trader has now $1.05 and has made a profit of 5 cents on an investment of $1.

Election stock markets typically cease trading the day before the election is held. The markets are liquidated after the election based on the election outcome. In markets for the popular vote share and the parliamentary seats share, each contract is valued precisely equal to the corresponding percentage share. In winner-takes-all markets, the winning contract pays $1, while the losing contracts pay $0.

Election stock markets are prediction markets for a particular purpose: elections. Even though election stock markets have been conducted for almost twenty years, the accuracy of these markets is nearly always judged by comparing the election stock market prediction (closing prices) on election eve with final pre-election polls and actual outcomes. Evidence that election stock markets perform remarkably well predicting election outcomes is found in a string of academic papers, mostly based on data from the Iowa Electronic Markets and the UBC Election Stock Market. Accuracy is typically measured as the average absolute forecast error for vote shares and seat shares. A more rigorous attempt to assess the performance of election stock markets is found in Berg et al. (2008); they report that for five recent elections covered by the Iowa Electronic Markets, the average absolute error in the market's prediction of the major-party presidential vote share across the 5 days prior to the election was 1.20 percentage points, while opinion polls conducted during that same time had an average error of 1.62 percentage points. Berg et al. (2008) also report evidence that election stock markets outperform polls for longer time periods before the election date.

Erikson and Wlezien (2008) challenge the view that election stock markets outperform polls. They argue that polls only measure preferences on the polling day, whereas election stock markets forecast the outcome on election day. When poll leads are discounted using statistical techniques, they find that poll-based forecasts outperform vote-share market prices.

A critical feature for the proper functioning of election stock markets is market liquidity. As prediction markets function through aggregation of beliefs and opinions into market prices, high trading volume and/or a continuous stream of new investments are essential for prices to provide an accurate forecast of the election outcome. Signs that liquidity is lacking in an election stock market include wide spreads (large differences between bid and ask prices) and arbitrage opportunities (where the sum of bid prices exceeds the value of a unit portfolio, or where the sum of ask prices is lower than the value of a unit portfolio). As election stock markets are opinion aggregators, the accuracy of such markets can be expected to increase with the number of market participants. Investment caps (as maintained by the Iowa Electronic Markets and the UBC Election Stock Market) level the trading opportunities among traders. Whether investment caps help with prediction accuracy has not yet been determined conclusively. However, without an investment cap, commercial election stock markets may be dominated by a small number of traders. The existence of transaction costs for investing and trading in commercial election stock markets may also reduce their efficiency.

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1973–1974 stock market crash

The 1973–1974 stock market crash was a stock market crash that lasted between January 1973 and December 1974. Affecting all the major stock markets in the world, particularly the United Kingdom, it was one of the worst stock market downturns in modern history. The crash came after the collapse of the Bretton Woods system over the previous two years, with the associated 'Nixon Shock' and United States dollar devaluation under the Smithsonian Agreement. It was compounded by the outbreak of the 1973 oil crisis in October of that year.

In the 694 days between 11 January 1973 and 6 December 1974, the New York Stock Exchange's Dow Jones Industrial Average benchmark lost over 45% of its value, making it the seventh-worst bear market in the history of the index. 1972 had been a good year for the DJIA, with gains of 15% in the twelve months. 1973 had been expected to be even better, with Time magazine reporting, just 3 days before the crash began, that it was 'shaping up as a gilt-edged year'. In the two years from 1972 to 1974, the American economy slowed from 7.2% real GDP growth to -2.1% contraction, while inflation (by CPI) jumped from 3.4% in 1972 to 12.3% in 1974.

Worse was the effect in the United Kingdom, and particularly on the London Stock Exchange's FT 30, which lost 73% of its value during the crash. From a position of 5.1% real GDP growth in 1972, the UK went into recession in 1974, with GDP falling by 1.1%. At the time, the UK's property market was going through a major crisis, and a secondary banking crisis forced the Bank of England to bail out a number of lenders. In the United Kingdom, the crash ended after the rent freeze was lifted on 19 December 1974, allowing a readjustment of property prices; over the following year, stock prices rose by 150%. However, unlike in the United States, inflation continued to rise, to 25% in 1975, giving way to the era of stagflation.

All the main stock indexes of the future G7 bottomed out between September and December 1974, having lost at least 34% of their value in nominal terms, and 43% in real terms. In all cases, the recovery was a slow process. Although West Germany's market was fastest to recover, returning to the original nominal level within eighteen months, even it did not return to the same real level until June 1985. The United Kingdom didn't return to the same market level until May 1987 (only a few months before the Black Monday crash), whilst the United States didn't see the same level in real terms until August 1993: over twenty years after the 1973–4 crash began.

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Source : Wikipedia