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Finance
There are two different approaches to finding fault with the efficient market hypothesis. The first approach is to attack the assumptions -- for example noting that there are high degrees of information asymmetry. Indeed, this should be the case because even if the asset is priced fairly, not all investors know this for a fact based on their own analysis -- their knowledge is just an extension of their belief in efficient markets. In essence, rather than come to a rational conclusion about the value of the asset, they simply trust that the other market participants have already done so.
The other approach to refuting the efficient market hypothesis is to demonstrate that investors are not actually rational. A good place to start is to look at the rise of program trading. Program trading is when institutions use computer programs to trade securities. The analysts will input certain parameters into the program -- for example selling a stock if it reaches a certain level, or buying....
This usually begins with a proper, rational analysis. Let's say you believe that Apple is overvalued once it reaches $600. The problem with the program is that the inputs can be outdated, but an even bigger problem occurs when programs start to move markets. At 43.1% of the NYSE last year, this is common (NYSE, 2013).
It is not hard to see that once a program begins to move markets, other investors might also engage in buying or selling of that security, based on the movements. Many investors are willing to make their decisions less on careful analysis and more on response to the movements. Technical traders will often buy or sell based on a stock price crossing a certain threshold. Day traders will, too -- EMH depends on fairly valuing the present value of future cash flows and day traders have no interest in sticking around for said cash flows. Either way, one of the things that happens with program trading in particular and with institutional trading in general is that market…
References
NYSE. (2013). Program trading averaged 43.1% of the NYSE during Dec 16-20. New York Stock Exchange. Retrieved May 1, 2014 from http://www.nyse.com/press/1387194756904.html
Sias, R. (1996). Volatility and the institutional investor. Financial Analysts Journal. Vol. 52 (2) 13-20.
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