From experience we know that investors may 'temporarily' move financial prices away from their long term aggregate price 'trends'. (Positive or up trends are referred to as bull markets; negative or down trends are referred to as bear markets.) Over-reactions may occur—so that excessive optimism (euphoria) may drive prices unduly high or excessive pessimism may drive prices unduly low. Economists continue to debate whether financial markets are 'generally' efficient.
According to optiontips.in one interpretation of the efficient-market hypothesis (EMH), only changes in fundamental factors, such as the outlook for margins, profits or dividends, ought to affect share prices beyond the short term, where random 'noise' in the system may prevail. (But this largely theoretic academic viewpoint—known as 'hard' EMH—also predicts that little or no trading should take place, contrary to fact, since prices are already at or near equilibrium, having priced in all public knowledge.) The 'hard' efficient-market hypothesis is sorely tested by such events as the stock market crash in 1987, when the Dow Jones index plummeted 22.6 percent—the largest-ever one-day fall in the United States.
However, a 'soft' EMH has emerged which does not require that prices remain at or near equilibrium, but only that market participants not be able to systematically profit from any momentary market 'inefficiencies'. Moreover, while EMH predicts that all price movement (in the absence of change in fundamental information) is random (i.e., non-trending), many studies have shown a marked tendency for the stock market to trend over time periods of weeks or longer. Various explanations for such large and apparently non-random price movements have been promulgated. For instance, some research has shown that changes in estimated risk, and the use of certain strategies, such as stop-loss limits and Value at Risk limits, theoretically could cause financial markets to overreact. But the best explanation seems to be that the distribution of stock market prices is non-Gaussian (in which case EMH, in any of its current forms, would not be strictly applicable).
In one paper the optiontips.in draw an analogy with gambling.In normal times the market behaves like a game of roulette; the probabilities are known and largely independent of the investment decisions of the different players. In times of market stress, however, the game becomes more like poker (herding behavior takes over). The players now must give heavy weight to the psychology of other investors and how they are likely to react psychologically.
However, a 'soft' EMH has emerged which does not require that prices remain at or near equilibrium, but only that market participants not be able to systematically profit from any momentary market 'inefficiencies'. Moreover, while EMH predicts that all price movement (in the absence of change in fundamental information) is random (i.e., non-trending), many studies have shown a marked tendency for the stock market to trend over time periods of weeks or longer. Various explanations for such large and apparently non-random price movements have been promulgated. For instance, some research has shown that changes in estimated risk, and the use of certain strategies, such as stop-loss limits and Value at Risk limits, theoretically could cause financial markets to overreact. But the best explanation seems to be that the distribution of stock market prices is non-Gaussian (in which case EMH, in any of its current forms, would not be strictly applicable).
In one paper the optiontips.in draw an analogy with gambling.In normal times the market behaves like a game of roulette; the probabilities are known and largely independent of the investment decisions of the different players. In times of market stress, however, the game becomes more like poker (herding behavior takes over). The players now must give heavy weight to the psychology of other investors and how they are likely to react psychologically.
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