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Information Cascades and the dot-com Bubble Burst

The boom and bust dynamics of the economy can be explained by rational human behavior, and it turns out that much of it has to do with information cascades. Web companies took advantage of the low interest rates in 1998–99 to increase their start-up capital amounts. These “dot-com” company’s planned to grow their business by harnessing network effects by operation at a net loss to build market share. In other words, these companies offered their services or end product for free with the expectation that they could build and retain a big enough user base to make profit at a later date.

A stock market bubble, is a self-perpetuating rise or boom in the share prices of stocks of a particular industry. A bubble occurs when speculators, people who have no interested in the success of a company but wish to make money from trading stock, note the fast increase in value and decide to buy in anticipation of further rises. This is a perfect example of an information cascade. Normally people will buy a stock because, based on their own information and research, they believe the stock to be undervalued. In this example, however, people were buying up stock simply because they saw others doing the same, and correctly guessed that the stock’s value would continue to rise, but incorrectly assumed the company’s profits would do the same.

Information cascades are considered inherently fragile, which makes sense seeing as they are usually based on incomplete information. Once more information is revealed, the cascade can fall apart in a big way. In 2000, information emerged indicating that dot-com companies were not performing as well as people had expected in 1998. This caused an “information avalanche” which had every buyer selling all of their shares in order to minimize the damage that could be caused to themselves. The rest is history. The market crashed with sites such as amazon’s stock prices being reduced to as little as $7 dollars a share. This is the power of information cascades, and is a good reason to act on your own information before blindly following a trend.


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December 2015