# As simple as random can be

A few weeks ago I was having a discussion about mathematical models for the prediction of the movements of the stock market. The question was whether there was any use to developing complex algorithms trying to predict these fluctuations. My friend (an economist) argued that while he admits the market value isn’t truly random, incorporating random variables may be the best model we have for it. It turns out that many mathematicians (and quants, economists who analyze market fluctuations using algorithms) have been using “random” models for their predictions. These range from sequences randomly drawn from log-normal distributions, to chaotic systems that may allow for the prediction of market crashes and other rare large movements. I was fascinated by the idea of randomness as a model for complex systems. It seemed particularly interesting to explore this in the context of biological processes, especially when the laws of thermodynamics have described that all physical phenomena drift towards the chaotic state of maximum entropy. Could randomness be a model for circuit wiring and function in the brain?

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